WO2023208069A1 - 一种解码、编码方法、装置及其设备 - Google Patents

一种解码、编码方法、装置及其设备 Download PDF

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WO2023208069A1
WO2023208069A1 PCT/CN2023/090956 CN2023090956W WO2023208069A1 WO 2023208069 A1 WO2023208069 A1 WO 2023208069A1 CN 2023090956 W CN2023090956 W CN 2023090956W WO 2023208069 A1 WO2023208069 A1 WO 2023208069A1
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current image
image area
pixel
adjustment
value
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French (fr)
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孙煜程
曹小强
陈方栋
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Hangzhou Hikvision Digital Technology Co Ltd
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Hangzhou Hikvision Digital Technology Co Ltd
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Priority to EP23795501.8A priority Critical patent/EP4518312A4/en
Priority to US18/860,278 priority patent/US20250301176A1/en
Priority to JP2024563448A priority patent/JP2025514248A/ja
Priority to KR1020247037644A priority patent/KR20250002469A/ko
Publication of WO2023208069A1 publication Critical patent/WO2023208069A1/zh
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
    • H04N19/88—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression involving rearrangement of data among different coding units, e.g. shuffling, interleaving, scrambling or permutation of pixel data or permutation of transform coefficient data among different blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/11—Selection of coding mode or of prediction mode among a plurality of spatial predictive coding modes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/117—Filters, e.g. for pre-processing or post-processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/157—Assigned coding mode, i.e. the coding mode being predefined or preselected to be further used for selection of another element or parameter
    • H04N19/159—Prediction type, e.g. intra-frame, inter-frame or bidirectional frame prediction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/593—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving spatial prediction techniques
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/80—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
    • H04N19/82—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation involving filtering within a prediction loop
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
    • H04N19/86—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression involving reduction of coding artifacts, e.g. of blockiness

Definitions

  • the present application relates to the field of coding and decoding technology, and in particular to a decoding and coding method, device and equipment.
  • Video images are transmitted after encoding.
  • Complete video encoding can include prediction, transformation, quantization, entropy coding, filtering and other processes.
  • the prediction process can include intra-frame prediction and inter-frame prediction.
  • Inter-frame prediction refers to using the correlation in the video temporal domain to predict the current pixel using pixels adjacent to the encoded image to achieve the purpose of effectively reducing video temporal redundancy.
  • Intra-frame prediction refers to using the correlation in the video spatial domain to predict the current pixel using the pixels of the encoded block of the current frame image to achieve the purpose of reducing video spatial domain redundancy.
  • Shallow coding is an image coding method characterized by simple prediction. Shallow coding is suitable for scenarios with high real-time requirements, small cache, and high parallelism requirements. However, in the encoding process using shallow coding, larger quantization step sizes often result in larger quantization errors, especially in flat areas. The overall deviation will lead to color blocks, resulting in subjective loss.
  • this application provides a decoding and encoding method, device and equipment, which improves encoding performance.
  • the present application provides a decoding method, which is applied to the decoding end.
  • the method includes: determining whether the reconstruction value of the current image area needs to be adjusted based on the characteristic information corresponding to the current image area; if it is determined that the reconstruction value of the current image area needs to be adjusted.
  • the reconstruction value adjustment the adjustment parameters corresponding to the current image area are obtained from the code stream corresponding to the current image area; and the reconstruction value of the current image area is adjusted based on the adjustment parameters.
  • the present application provides an encoding method, which is applied to the encoding end.
  • the method includes: determining whether the reconstruction value of the current image area needs to be adjusted based on the characteristic information corresponding to the current image area; if it is determined that the reconstruction value of the current image area needs to be adjusted.
  • the reconstruction value adjustment is to obtain the adjustment parameters corresponding to the current image area, and the adjustment parameters are used to adjust the reconstruction value of the current image area; the code stream corresponding to the current image area is encoded.
  • the adjustment parameters corresponding to the current image area includes: determining whether the reconstruction value of the current image area needs to be adjusted based on the characteristic information corresponding to the current image area; if it is determined that the reconstruction value of the current image area needs to be adjusted.
  • the reconstruction value adjustment is to obtain the adjustment parameters corresponding to the current image area, and the adjustment parameters are used to adjust the reconstruction value of the current image area; the code stream corresponding to the current image area is encoded.
  • the adjustment parameters corresponding to the current image area is to obtain the
  • the present application provides a decoding device.
  • the decoding device includes: a memory configured to store video data; a decoder configured to: determine whether it is necessary to modify the current image region based on the characteristic information corresponding to the current image region. Perform reconstruction value adjustment; if it is determined that the reconstruction value adjustment needs to be performed on the current image area, obtain the adjustment parameters corresponding to the current image area from the code stream corresponding to the current image area; based on the adjustment parameters, The reconstruction value of the current image area is adjusted.
  • the present application provides an encoding device.
  • the encoding device includes: a memory configured to store video data; an encoder configured to: determine whether it is necessary to encode the current image area based on characteristic information corresponding to the current image area. Perform reconstruction value adjustment; if it is determined that the reconstruction value adjustment needs to be performed on the current image area, obtain the adjustment parameters corresponding to the current image area, and the adjustment parameters are used to adjust the reconstruction value of the current image area. ; Encoding the adjustment parameter corresponding to the current image area in the code stream corresponding to the current image area.
  • the present application provides a decoding end device, including: a processor and a machine-readable storage medium.
  • the machine-readable storage medium stores machine-executable instructions that can be executed by the processor; the processor is configured to execute the The machine can execute instructions to implement the above decoding method.
  • the present application provides a coding end device, including: a processor and a machine-readable storage medium.
  • the machine-readable storage medium stores machine-executable instructions that can be executed by the processor; the processor is used to execute the The machine can execute instructions to implement the encoding method described above.
  • the present application provides a machine-readable storage medium on which computer instructions are stored.
  • the computer instructions are executed by at least one processor, the above-mentioned decoding method or encoding method is implemented.
  • a shallow coding method is proposed, which can be applied to real-time
  • the reconstruction value of the current image area can also be adjusted, so that the reconstructed pixels can be closer to the original pixels, bringing about better coding performance and Decoding performance improvement.
  • the quantization error is reduced, especially in flat areas, and the color block problem caused by the overall deviation can be reduced, which can reduce subjective loss. That is, the shallow coding method can achieve subjective losslessness and simple hardware implementation.
  • FIGS 1A to 1C are schematic diagrams of the working principle of intra prediction mode
  • Figures 2A to 2D are schematic diagrams of a shallow coding video coding framework
  • Figure 3 is a flow chart of an encoding method in an embodiment of the present application.
  • Figure 4 is a flow chart of a decoding method in an embodiment of the present application.
  • FIGS 5A to 5D are schematic diagrams of the division of image blocks in an embodiment of the present application.
  • FIGS 6A to 6J are schematic diagrams of the division of image blocks in an embodiment of the present application.
  • Figure 7A is a hardware structure diagram of a decoding terminal device in an embodiment of the present application.
  • Figure 7B is a hardware structure diagram of the encoding end device in an embodiment of the present application.
  • the first information may also be called second information.
  • the second information may also be called first information, depending on the context.
  • the word “if” as used may be interpreted as "when,” or "when,” or "in response to determining.”
  • Intra prediction Intra prediction
  • inter prediction inter prediction
  • IBC Intra Block Copy, intra block copy
  • Intra-frame prediction refers to using the pixels of the encoded block of the current image to predict the pixels of the current block based on the correlation in the video spatial domain, in order to achieve the purpose of reducing video spatial redundancy.
  • Intra-frame prediction specifies a variety of prediction modes, each prediction mode corresponds to a texture direction (except DC (Direct Current, DC) mode). For example, if the image texture is arranged horizontally, the horizontal prediction mode can be better Predict image information.
  • DC Direct Current, DC
  • Inter-frame prediction refers to, based on the correlation in the video time domain. Since the video sequence contains strong temporal correlation, using the pixels of adjacent encoded images to predict the pixels of the current image can effectively reduce the video temporal redundancy (temporal redundancy). redundancy) purpose.
  • the interframe prediction part of the video coding standard adopts block-based motion compensation technology. The main principle is to find the best matching block in the previously encoded image for each pixel block of the current image. This process is called motion estimation (Motion Estimation). ,ME).
  • Intra-frame block copy means that same-frame reference is allowed, and the reference data of the current block comes from the same frame.
  • the block vector of the current block can be used to obtain the predicted value of the current block. For example, based on the feature that there are a large number of recurring textures in the same frame in the screen content, the block vector is used to obtain the predicted value of the current block. When predicting values, it can improve the compression efficiency of screen content sequences.
  • Prediction pixel refers to the pixel value derived from the encoded and decoded pixels.
  • the residual is obtained through the difference between the original pixel and the predicted pixel, and then the residual transformation, quantization and coefficient coding are performed.
  • Inter-frame predicted pixels refer to the pixel values of the current block derived from the reference frame. Since the pixel positions are discrete, interpolation operations are required to obtain the final predicted pixels. The closer the predicted pixel is to the original pixel, the smaller the residual energy obtained by subtracting the two, and the higher the coding compression performance.
  • Intra prediction mode In intra coding, intra prediction mode is used for motion compensation, that is, intra prediction is used The mode obtains the predicted value of the current block.
  • the intra prediction mode is a mode that uses the reconstructed value and predicted value of the current frame for prediction.
  • the intra prediction mode may include but is not limited to DC mode, bilinear mode, angle prediction mode (such as horizontal angle prediction mode, vertical angle prediction mode, etc.).
  • angle prediction mode such as horizontal angle prediction mode, vertical angle prediction mode, etc.
  • angle prediction mode There is no limit to the angle prediction mode, and it can be any angle, such as 33 types. Angle mode or 65 angle modes, etc.), IBC mode, ISC (Intra String Copy, intra-frame string copy) mode, Planar mode, point-by-point prediction mode, etc.
  • DC mode and angle prediction mode can be seen in Figure 1A.
  • DC mode is suitable for large flat areas.
  • the average value of the surrounding pixels of the current block is used as the prediction value of the current block.
  • the angle prediction mode points to the current block at a certain angle.
  • the values of surrounding pixels are used as the predicted values of the current block.
  • a) is a schematic diagram of the DC mode, and the average value of the 16 reference pixels on the upper side of "D" is used as the predicted value of "D".
  • b) is a schematic diagram of angle prediction mode 1, indicating that the value of the reference pixel pointed by the angle is used as the prediction value of the current block.
  • c) is a schematic diagram of angle prediction mode 2
  • d) is a schematic diagram of angle prediction mode 3
  • e) is a schematic diagram of angle prediction mode 4
  • f) is a schematic diagram of angle prediction mode 5
  • g) is a schematic diagram of angle prediction mode 6.
  • the bilinear mode is the bilinear interpolation mode, as shown in Figure 1B.
  • the prediction process of the bilinear mode is as follows: first generate the predicted value of the lower right corner C position (the weighted average of the upper right corner reference pixel A and the lower left corner reference pixel B), and then generate The predicted value of the right boundary AC position (the weighted average of the predicted values of the upper right corner reference pixel A and the lower right corner C position), and then generates the predicted value of the lower boundary BC position (the weighted average of the lower left corner reference pixel B and the lower right corner C position predicted value) ), the remaining predicted values of other internal pixels (such as the predicted value of the X position) are generated by the weighted average of the predicted values produced by horizontal linear prediction and the predicted values produced by vertical linear prediction.
  • the predicted value generated by horizontal linear prediction is the weighted average of the predicted value of the reference pixel L at the corresponding position on the left and the position of the right boundary AC;
  • the predicted value generated by vertical linear prediction is the weighted average of the predicted value of the reference pixel T at the corresponding position on the upper side and the position of the lower boundary BC. average.
  • Planar mode (or Plane mode) is suitable for areas where pixel values change slowly. It uses two linear filters in the horizontal and vertical directions, and uses the average of the pixels in the two directions as the predicted value of the current block pixel. Planar mode is a gradient mode. Planar mode is an intra-frame prediction mode that uses reference pixels at different positions and different weight parameters to obtain predicted values.
  • ISC mode is to arrange the pixels in the current block into several one-dimensional pixel groups in a certain scanning order (generally horizontal raster scanning order or vertical raster scanning order), and each pixel group performs a similar motion estimation method to obtain the prediction of the pixel group. value.
  • the point-by-point prediction mode is shown in Figure 1C, which is a schematic diagram of four point-by-point prediction modes for a 16*2 pixel block.
  • Figure 1C is a schematic diagram of four point-by-point prediction modes for a 16*2 pixel block.
  • ⁇ is used to indicate that the predicted value of the current pixel is obtained by averaging the reconstructed values of the pixels on the left and right sides;
  • is used to indicate that the predicted value of the current pixel is obtained by averaging the reconstructed values of the pixels on the upper and lower sides;
  • > Used to indicate that the reconstructed value of the left pixel is directly used as the predicted value of the current pixel;
  • ⁇ is used to indicate that the reconstructed value of the upper pixel is directly used as the predicted value of the current pixel.
  • Rate-Distortion Optimization (RDO) principle There are two major indicators to evaluate coding efficiency: code rate and PSNR (Peak Signal to Noise Ratio, Peak Signal to Noise Ratio). The smaller the bit stream, the greater the compression rate. The larger the PSNR, the better the quality of the reconstructed image.
  • SAD refers to the sum of the absolute values of the differences between the reconstructed image block and the source image; ⁇ is the Lagrange multiplier. , R is the actual number of bits required for image block coding in this mode, including the total number of bits required for coding mode information, motion information, residuals, etc.
  • Code control Controls the stability of the code rate, generally by adjusting the quantization step size to achieve the purpose of code rate stability.
  • Shallow coding is an image coding method characterized by simple prediction. Shallow coding is suitable for application scenarios with high real-time requirements, small cache, and high parallelism requirements.
  • the compression efficiency of shallow coding is low, intra-frame prediction can be used, and the compression ratio is low (for example, generally less than 10 times). In the implementation process of shallow coding, it is generally required to be subjectively lossless and simple in hardware implementation.
  • Shallow coding video coding framework See Figure 2A, which is a schematic diagram of the video coding framework on the coding side. This video coding framework can be used to implement the processing flow of the coding side in the embodiment of the present application, that is, to implement shallow coding.
  • the schematic diagram of the video decoding framework on the decoding end is similar to Figure 2A, and will not be repeated here.
  • the video decoding framework can be used to implement the decoding end processing flow of the embodiment of the present application.
  • the video coding framework may include modules such as block partitioning, prediction, transformation, quantization, code control, entropy encoder, inverse quantization, inverse transformation, and reconstruction.
  • the video decoding framework can include modules such as block partitioning, prediction, transformation, quantization, code control, entropy decoder, inverse quantization, inverse transformation, reconstruction, etc.
  • the code control module belonging to the encoding end can also act on the decoding end.
  • the video decoding framework can include modules such as block partitioning, prediction, transformation, quantization, entropy decoder, inverse quantization, inverse transformation, and reconstruction. In this case, There is no code control module. On the decoding side, through the cooperation between these modules, the decoding side processing flow can be realized.
  • the code control technology is applied to a code control unit.
  • the code control unit is the scope of code control, which means that code control operations are performed on the range corresponding to the code control unit.
  • the code control unit can be several image blocks, or the code control unit can be several pixel rows, or the code control unit can be the entire Slice, or the code control unit can be several pixel blocks inside the Slice, or the code control unit can be are several pixel rows inside Slice, etc.
  • the above are just a few examples of the code control unit, and there is no limitation on the code control unit.
  • operations such as prediction, transformation, and quantization can be performed on the pixel blocks in each code control unit.
  • the mode selection of the prediction part is participated by the code control. After the pixel block is reconstructed, the reconstruction value adjustment operation can be performed.
  • the encoding end may include a prediction processing unit, a residual calculation unit, a transformation processing unit, a quantization unit, an encoding processing unit, an inverse quantization unit (which may also be called an inverse quantization unit), and an inverse transform processing unit (which may also be called an inverse quantization unit). It is an inverse transform processing unit), a reconstruction unit (also called a reconstruction unit) and a filter unit.
  • the encoding end may also include a buffer and a decoded image buffer, wherein the buffer is used to cache the reconstructed image blocks output by the reconstruction unit, and the decoded image buffer is used to cache the filtered image blocks output by the filter unit. Image block.
  • the input of the encoding end can be an image block of an image (which can be called the image to be encoded).
  • the image block can also be called the current block or the block to be encoded.
  • the encoding end can also include a segmentation unit (in the figure (not shown), the dividing unit is used to divide the image to be encoded into multiple image blocks.
  • the encoding end may encode the plurality of image blocks block by block to complete encoding of the image to be encoded, for example, performing an encoding process on each image block.
  • the prediction processing unit is used to receive or obtain image blocks (the current image block to be encoded of the current image to be encoded, which can also be called the current block, and the image block can be understood as the true value of the image block) and reconstructed image data, based on the The relevant data in the reconstructed image data is used to predict the current block and a prediction block of the current block is obtained.
  • the prediction processing unit may include an inter prediction unit, an intra prediction unit and a mode selection unit.
  • the mode selection unit is used to select an intra prediction mode or an inter prediction mode. If the intra prediction mode is selected, the frame The intra prediction unit performs the prediction process, and if the inter prediction mode is selected, the inter prediction unit may perform the prediction process.
  • the residual calculation unit is used to calculate the residual between the true value of the image block and the prediction block of the image block to obtain the residual block.
  • the residual calculation unit can subtract the prediction block from the pixel value of the image block pixel by pixel. pixel value.
  • the transform processing unit is used to transform the residual block, such as discrete cosine transform (DCT) or discrete sine transform (DST), to obtain transform coefficients in the transform domain.
  • DCT discrete cosine transform
  • DST discrete sine transform
  • the transform coefficients can also be called Transform residual coefficients that can represent the residual block in the transform domain.
  • the quantization unit is used to quantize the transform coefficients by applying scalar quantization or vector quantization to obtain a quantized transform system. number, the quantized transform coefficients may also be called quantized residual coefficients.
  • the quantization process can reduce the bit depth associated with some or all transform coefficients. For example, n-bit transform coefficients may be rounded down to m-bit transform coefficients during quantization, where n is greater than m.
  • the degree of quantization can be modified by adjusting the quantization parameter (QP). For example, with scalar quantization, different scales can be applied to achieve finer or coarser quantization. A smaller quantization step size corresponds to finer quantization, while a larger quantization step size corresponds to coarser quantization. The appropriate quantization step size can be indicated by the quantization parameter.
  • the encoding processing unit is used to encode the above-mentioned quantized residual coefficient and a part of the encoding parameters, output the encoded image data (ie, the encoding result of the current image block to be encoded) and the encoded encoding parameters in the form of an encoded bit stream, and then The encoded bitstream is transmitted to the decoder or stored for later transmission to the decoder or for retrieval.
  • the encoding processing unit can also be used to encode other syntax elements of the current image block, such as encoding the prediction mode to the code stream.
  • Coding algorithms include but are not limited to variable length coding (VLC) algorithm, context adaptive VLC (context adaptive VLC, CAVLC) algorithm, arithmetic coding algorithm, context adaptive binary arithmetic coding (CABAC) ) algorithm, syntax-based context-adaptive binary arithmetic coding (SBAC) algorithm, probability interval partitioning entropy (PIPE) algorithm.
  • VLC variable length coding
  • CABAC context adaptive binary arithmetic coding
  • SBAC syntax-based context-adaptive binary arithmetic coding
  • PIPE probability interval partitioning entropy
  • the inverse quantization unit is used to inversely quantize the above-mentioned quantized residual coefficient to obtain the inverse-quantized coefficient.
  • the inverse quantization is a reverse application of the above-mentioned quantization unit. For example, based on or using the same quantization step size as the quantization unit, the inverse quantization unit is used to obtain the inverse quantization coefficient.
  • the inverse quantized coefficients may also be called inverse quantized residual coefficients.
  • the inverse transformation processing unit is used to perform inverse transformation on the above-mentioned inverse quantized coefficients. It should be understood that the inverse transformation is a reverse application of the above-mentioned transformation processing unit.
  • the inverse transform may include an inverse discrete cosine transform (IDCT) or an inverse discrete sine transform (IDST) to obtain the inverse transform block in the pixel domain (or sample domain).
  • the inverse transform block may also be called an inverse transform inverse quantized block or an inverse transform residual block.
  • the reconstruction unit is used to add the inverse transform block (ie, the inverse transform residual block) to the prediction block to obtain the reconstructed block in the sample domain.
  • the reconstruction unit may be a summer, for example, the samples of the residual block.
  • the values i.e. pixel values
  • the reconstructed block output by the reconstruction unit can be subsequently used to predict other image blocks, for example, in intra prediction mode.
  • the filter unit (or simply "filter”) is used to filter the reconstructed block to obtain the filtered block, thereby smoothly performing pixel conversion or improving image quality.
  • the filter unit may be a loop filter unit, intended to represent one or more loop filters, for example, the filter unit may be a deblocking filter, a sample-adaptive offset (SAO) filter Or other filters, such as bilateral filters, adaptive loop filters (ALF), or sharpening or smoothing filters, or collaborative filters.
  • the filtered blocks output by the filtering unit can be subsequently used to predict other image blocks, for example, in inter prediction mode, without limitation.
  • FIG. 2C a schematic block diagram of a decoding end (which may also be referred to as a decoder) for implementing an embodiment of the present application is shown.
  • the decoder is configured to receive encoded image data (ie, an encoded bitstream, e.g., an encoded bitstream including image blocks and associated syntax elements), eg, encoded by the encoder, to obtain a decoded image.
  • the decoder includes a decoding unit, an inverse quantization unit, an inverse transform processing unit, a prediction processing unit, a reconstruction unit, and a filter unit.
  • the decoder may perform a decoding process that is generally reciprocal to the encoding process described for the encoder of Figure 2B.
  • the decoder may further include a buffer and a decoded image buffer, wherein the buffer is used to cache the reconstructed image block output by the reconstruction unit, and the decoded image buffer is used to cache the filtered image block output by the filter unit. Image block.
  • the decoding unit is configured to perform decoding on the encoded image data to obtain quantized transform coefficients and/or decoded encoding parameters (for example, the encoding parameters may include inter prediction parameters, intra prediction parameters, filter parameters, and/or other any one or more of the syntax elements).
  • the decoding unit is also configured to forward the decoded encoding parameters to the prediction processing unit, so that the prediction processing unit performs a prediction process according to the encoding parameters.
  • the inverse quantization unit may have the same function as the inverse quantization unit of the encoder, for inverse quantizing (i.e., inverse quantizing) the quantized transform decoded by the decoding unit coefficient.
  • the function of the inverse transform processing unit may be the same as the function of the inverse transform processing unit of the encoder, and is used to inversely transform the above-mentioned quantized transform coefficients (for example, inverse DCT, inverse integer transform, or a conceptually similar inverse transform process), thereby An inverse transform block (also called an inverse transform residual block) is obtained, which is the residual block of the current image block in the pixel domain.
  • An inverse transform block also called an inverse transform residual block
  • the prediction processing unit is configured to receive or obtain encoded image data (such as the encoded bit stream of the current image block) and reconstructed image data.
  • the prediction processing unit may also receive or obtain prediction related parameters and/or information about the decoding unit from, for example, the decoding unit.
  • the information of the selected prediction mode ie, the decoded coding parameters
  • the current image block is predicted based on the relevant data in the reconstructed image data and the decoded coding parameters to obtain a prediction block of the current image block.
  • the prediction processing unit may include an inter prediction unit, an intra prediction unit and a mode selection unit.
  • the mode selection unit is used to select an intra prediction mode or an inter prediction mode. If the intra prediction mode is selected, the frame The intra prediction unit performs the prediction process. If the inter prediction mode is selected, the inter prediction unit performs the prediction process.
  • the function of the reconstruction unit can be the same as that of the encoder, and the reconstruction unit is used to add the inverse transform block (i.e., the inverse transform residual block) to the prediction block to perform the transformation in the sample domain.
  • the reconstructed block is obtained, for example by adding the sample values of the inverse transform residual block and the sample values of the prediction block.
  • the filter unit is used to filter the reconstructed block to obtain a filtered block, which is a decoded image block.
  • the processing result for a certain link can also be output to the next link after further processing, for example, in interpolation filtering, motion vector derivation or filtering, etc.
  • further operations such as Clip or shift are performed on the processing results of the corresponding link.
  • Figure 2D is a schematic flow chart of encoding and/or decoding provided by the embodiment of the present application.
  • the encoding and decoding implementation includes process 1 to process 5, and the process 1 to process 5 can be executed by the above-mentioned decoder and/or encoder.
  • Process 1 Divide a frame of image into one or more parallel coding units that do not overlap with each other. There is no dependency between the one or more parallel coding units, and they can be independently encoded and decoded completely in parallel, such as the parallel coding unit 1 and the parallel coding unit 2 shown in Figure 2D.
  • each parallel coding unit it can be divided into one or more independent coding units that do not overlap with each other.
  • the independent coding units may not depend on each other, but they can share some parallel coding unit header information.
  • the width of an independent coding unit is w_lcu and the height is h_lcu. If the parallel coding unit is divided into an independent coding unit, the size of the independent coding unit is exactly the same as that of the parallel coding unit; otherwise, the width of the independent coding unit should be greater than the height (unless it is an edge area).
  • the independent coding unit can be fixed w_lcu ⁇ h_lcu, w_lcu and h_lcu are both 2 to the N power (N ⁇ 0).
  • the size of the independent coding unit is: 128 ⁇ 4, 64 ⁇ 4, 32 ⁇ 4, 16 ⁇ 4, 8 ⁇ 4, 32 ⁇ 2, 16 ⁇ 2 or 8 ⁇ 2 etc.
  • the independent coding unit may be fixed 128 ⁇ 4. If the size of the parallel coding unit is 256 ⁇ 8, the parallel coding unit can be equally divided into 4 independent coding units; if the size of the parallel coding unit is 288 ⁇ 10, the parallel coding unit can be divided into: first and second lines. Two 128 ⁇ 4+1 32 ⁇ 4 independent coding units; the third row is two 128 ⁇ 2+1 32 ⁇ 2 independent coding units. It is worth noting that the independent coding unit can include three components of brightness Y, chroma Cb, and chroma Cr, or three components of red (red, R), green (green, G), and blue (blue, B). Or the three components of brightness Y, chroma Co, and chroma Cg can also include only one of them. If the independent coding unit contains three components, the sizes of the three components can be exactly the same or different, depending on the input format of the image.
  • each independent coding unit it can be divided into one or more coding units that do not overlap with each other.
  • Each coding unit within the independent coding unit can depend on each other. For example, multiple coding units can be pre-coded with mutual reference/ decoding.
  • the independent coding unit and the independent coding unit have the same size (that is, the independent coding unit is only divided into one coding unit), then Its size can be all the sizes described in process 2.
  • the independent coding unit is divided into multiple non-overlapping coding units, examples of feasible divisions include: horizontal division (the height of the coding unit is the same as the independent coding unit, but the width is different, which can be 1/2, 1/4, 1/8, 1/16, etc.), vertically divided (the width of the coding unit is the same as that of the independent coding unit, but the height is different, which can be 1/2, 1/4, 1/8, 1/16, etc.), horizontal and vertical equal division (quadtree division), etc., preferably horizontal equal division.
  • the width of the coding unit is w_cu and the height is h_cu. Its width should be greater than its height (unless it is an edge area).
  • the coding unit can be a fixed w_cu ⁇ h_cu, w_cu and h_cu are both 2 N powers (N is greater than or equal to 0), such as 16 ⁇ 4, 8 ⁇ 4, 16 ⁇ 2, 8 ⁇ 2, 8 ⁇ 1 , 4 ⁇ 1, etc.
  • the coding unit may be fixed 16 ⁇ 4. If the size of the independent coding unit is 64 ⁇ 4, the independent coding unit can be equally divided into 4 coding units; if the size of the independent coding unit is 72 ⁇ 4, the coding unit can be divided into: 4 16 ⁇ 4+1 8 ⁇ 4.
  • the coding unit can include three components of brightness Y, chroma Cb, and chroma Cr (or three components of red R, green G, and blue B, or brightness Y, chroma Co, and chroma Cg), You can also include only one component. If it contains three components, the sizes of the components can be exactly the same or different, depending on the image input format.
  • process 3 can be an optional step in the encoding and decoding method, and the encoder/decoder can encode/decode the residual coefficients (or residual values) of the independent coding units obtained in process 2.
  • PG non-overlapping prediction groups
  • PG is also referred to as Group.
  • Each PG is encoded and decoded according to the selected prediction mode to obtain PG.
  • the predicted value constitutes the predicted value of the entire coding unit.
  • the residual value of the coding unit can be obtained based on the predicted value and original value of the coding unit.
  • Process 5 Based on the residual value of the coding unit, group the coding units to obtain one or more non-overlapping residual blocks (RB).
  • the residual coefficients of each RB are encoded and decoded according to the selected mode. , forming a residual coefficient stream. Specifically, it can be divided into two categories: transforming the residual coefficients and not transforming them.
  • the selected mode of the residual coefficient encoding and decoding method in process 5 may include but is not limited to any of the following: semi-fixed length encoding method, exponential Golomb encoding method, Golomb-Rice encoding method, truncated unary code encoding method, run-length encoding method, direct encoding of the original residual value, etc.
  • the encoder may directly encode the coefficients within the RB.
  • the encoder can also transform the residual block, such as DCT, DST, Hadamard transform, etc., and then encode the transformed coefficients.
  • the encoder can directly quantize each coefficient in the RB uniformly, and then perform binary encoding.
  • the RB can be further divided into multiple coefficient groups (CG), and then each CG is uniformly quantized and then binary encoded.
  • CG coefficient group
  • QG quantization group
  • the coefficient group and the quantization group may be the same.
  • the coefficient group and the quantization group may also be different.
  • the maximum value of the absolute value of the residual within an RB block is defined as the modified maximum (mm).
  • the number of coded bits of the residual coefficient in the RB block is determined (the number of coded bits of the residual coefficient in the same RB block is consistent). For example, if the critical limit (CL) of the current RB block is 2 and the current residual coefficient is 1, then 2 bits are needed to encode the residual coefficient 1, which is expressed as 01. If the CL of the current RB block is 7, it means encoding an 8-bit residual coefficient and a 1-bit sign bit.
  • the determination of CL is to find the minimum T value that satisfies all residuals of the current sub-block to be within the range of [-2 ⁇ (T-1), 2 ⁇ (T-1)]. If there are two boundary values -2 ⁇ (T-1) and 2 ⁇ (T-1) at the same time, T increases by 1, that is, T+1 bits are needed to encode all the residuals of the current RB block; if there is only -2 One of the two boundary values ⁇ (T-1) and 2 ⁇ (T-1), then encode a Trailing bit to determine whether the boundary value is -2 ⁇ (T-1) or 2 ⁇ (T-1); If any of -2 ⁇ (T-1) and 2 ⁇ (T-1) does not exist in all residuals, there is no need to encode the Trailing bit. For some special cases, the encoder can directly encode the original value of the image instead of the residual value.
  • shallow coding is an image coding method characterized by simple prediction.
  • Shallow coding is suitable for scenarios with high real-time requirements, small cache, and high parallelism requirements.
  • larger quantization step sizes often result in larger quantization errors.
  • the overall deviation will lead to color blocks, resulting in subjective loss.
  • the subjective loss in this application means that the human eye can detect the difference between the reconstructed image and the source image. This can be determined by alternately playing the reconstructed image and the source image at a specific frequency (for example, 8Hz) at a suitable observation distance. .
  • the embodiment of this application proposes a shallow coding filtering method, which can be applied to scenarios with high real-time requirements, small cache, and high parallelism requirements.
  • the current image After obtaining the reconstruction value of the current image area, the current image can be The reconstruction value of the region is adjusted to make the reconstructed pixels closer to the original pixels, thereby improving the encoding performance and decoding performance.
  • the quantization error is reduced, especially in flat areas, and the color block problem caused by the overall deviation is reduced, which can reduce subjective loss and improve subjective performance.
  • subjective losslessness and hardware implementation can be achieved Simple.
  • Embodiment 1 An encoding method is proposed in the embodiment of this application. See Figure 3, which is a schematic flow chart of the encoding method. The method can be applied to the encoding end (also called a video encoder). The method can include :
  • Step 301 Determine whether the reconstruction value of the current image area needs to be adjusted based on the characteristic information corresponding to the current image area.
  • an explicit method can be used to determine whether the reconstruction value of the current image area needs to be adjusted.
  • the feature information involved in the explicit method is called the first type of feature information.
  • the first type of feature information corresponding to the current image area can be obtained. If the first type of feature information corresponding to the current image area meets a specific condition (such as a first specific condition), it is determined whether the reconstruction value of the current image area needs to be adjusted. And based on the determination result, a flag bit corresponding to the adjustment control switch is encoded in the code stream corresponding to the current image area. The flag bit is used to indicate whether the reconstruction value adjustment of the current image area needs to be performed. If the first type of feature information corresponding to the current image area does not meet specific conditions, it is determined that there is no need to adjust the reconstruction value of the current image area, and the mark bit corresponding to the adjustment control switch is not encoded in the code stream corresponding to the current image area.
  • a specific condition such as a first specific condition
  • the mark bit corresponding to the adjustment control switch is encoded in the code stream corresponding to the current image area, and the mark bit is the third One value
  • the first value indicates that the reconstruction value of the current image area needs to be adjusted. If it is determined that there is no need to adjust the reconstruction value of the current image area, the mark bit corresponding to the adjustment control switch is encoded in the code stream corresponding to the current image area, and the mark bit is the second value, and the second value indicates that it is not necessary. Adjust the reconstruction value of the current image area.
  • the first value and the second value can be configured according to experience, and there is no restriction on this. For example, the first value is 1 and the second value is 0.
  • the current image area may include one image block, or the current image area may include multiple consecutive image blocks.
  • the code stream corresponding to the current image area refers to: the code stream related to the current image area, that is, the code stream contains information for processing the current image area. There is no restriction on the code stream corresponding to the current image area.
  • the first type of feature information corresponding to the current image area may include but is not limited to at least one of the following: prediction mode; data amount in the code stream buffer; quantization step size. Based on this, if the first type of feature information includes a prediction mode, when the prediction mode corresponding to the current image area is the specified prediction mode, it is determined that the prediction mode satisfies the specific condition; otherwise, it is determined that the prediction mode does not satisfy the specific condition. If the first type of characteristic information includes the amount of data in the code stream buffer, when the amount of data in the code stream buffer is within the preset data amount interval, it is determined that the amount of data in the code stream buffer meets specific conditions; otherwise, it is determined The amount of data in the stream buffer does not meet certain conditions.
  • the first type of feature information includes a quantization step size
  • the quantization step size corresponding to the current image area is within the preset step size interval, it is determined that the quantization step size satisfies the specific condition; otherwise, it is determined that the quantization step size does not meet the specific condition.
  • the prediction mode corresponding to the current image area is determined when the prediction mode meets specific conditions and the amount of data in the code stream buffer also meets specific conditions.
  • the first type of feature information satisfies the specific condition; otherwise, it is determined that the first type of feature information corresponding to the current image area does not meet the specific condition.
  • the first type of feature information includes the quantization step size and the amount of data in the code stream buffer, then When the step size meets specific conditions and the amount of data in the code stream buffer also meets specific conditions, it is determined that the first type of feature information corresponding to the current image area meets the specific conditions. Otherwise, the first type of feature information corresponding to the current image area is determined.
  • the information does not meet certain criteria. Or, if the first type of feature information includes a prediction mode and a quantization step size, then it is determined that the first type of feature information corresponding to the current image area meets the specific conditions only when the prediction mode meets specific conditions and the quantization step size also meets specific conditions. , otherwise, it is determined that the first type of feature information corresponding to the current image area does not meet specific conditions.
  • the first type of feature information includes prediction mode, the amount of data in the code stream buffer, and the quantization step size
  • the prediction mode meets specific conditions
  • the amount of data in the code stream buffer meets specific conditions
  • the quantization step size Only when the specific conditions are met, it is determined that the first type of feature information corresponding to the current image area satisfies the specific conditions; otherwise, it is determined that the first type of feature information corresponding to the current image area does not meet the specific conditions.
  • this first type of characteristic information is not limited in this embodiment.
  • the specified prediction mode may be one or more of the common intra prediction modes.
  • the common intra prediction mode includes DC mode; or the common intra prediction mode includes DC mode, horizontal prediction mode and vertical prediction mode; or the common intra prediction mode includes DC mode and angle prediction mode; or the common intra prediction mode Prediction modes include DC mode, angle prediction mode and Planar mode; alternatively, ordinary intra prediction modes include DC mode, angle prediction mode and bilinear mode; alternatively, ordinary intra prediction modes include DC mode, angle prediction mode, Planar mode and bilinear mode model.
  • an implicit method can be used to determine whether the reconstruction value of the current image area needs to be adjusted.
  • the feature information involved in the implicit method is called the second type of feature information.
  • the second type of feature information corresponding to the current image area For example, obtain the second type of feature information corresponding to the current image area. If the second type of feature information corresponding to the current image area satisfies a specific condition (such as a second specific condition), it is determined that the reconstruction value of the current image area needs to be adjusted. If the current If the second type of feature information corresponding to the image area does not meet specific conditions, it is determined that there is no need to adjust the reconstruction value of the current image area.
  • a specific condition such as a second specific condition
  • Step 302 If it is determined that the reconstruction value of the current image area needs to be adjusted, the adjustment parameters corresponding to the current image area are obtained, where the adjustment parameters are used to adjust the reconstruction value of the current image area.
  • Step 303 Encode the adjustment parameters corresponding to the current image area in the code stream corresponding to the current image area.
  • the adjustment parameters corresponding to the current image area include multiple adjustment values
  • all or part of the adjustment values ie, some of the multiple adjustment values may be encoded in the code stream corresponding to the current image area.
  • encoding all the adjustment values or part of the adjustment values in the code stream corresponding to the current image area may include but is not limited to: sorting the multiple adjustment values according to the encoding order of the multiple adjustment values, and sequentially traversing the multiple adjustment values based on the sorting results.
  • the adjustment value for the current traversed adjustment value, if after encoding the adjustment value in the code stream corresponding to the current image area, the current code rate is less than the preset code rate value, then the adjustment value will be encoded in the code stream corresponding to the current image area, And continue to traverse the next adjustment value of the adjustment value, that is, use the next adjustment value as the current traversal adjustment value; otherwise, it is prohibited to encode the adjustment value in the code stream corresponding to the current image area, and stop traversing the adjustment value the next adjustment value.
  • the current image area may correspond to multiple pixel groups, and the adjustment parameters corresponding to the current image area may include multiple adjustment values.
  • the multiple adjustment values may include adjustment values corresponding to K pixel groups, and the K pixel groups may be all pixel groups or part of the pixel groups in multiple pixel groups (that is, all pixel groups in the current image area).
  • M adjustment values corresponding to K pixel groups can be encoded in the code stream corresponding to the current image area.
  • M can be a positive integer, M can be less than or equal to K, and the M adjustment values can be based on K The adjustment value corresponding to the pixel group is determined.
  • adjustment value grouping indication information may also be encoded in the code stream corresponding to the current image area, and the adjustment value grouping indication information is used to indicate the matching relationship between the M adjustment values and the K pixel groups.
  • the adjustment value grouping indication information may be a fourth value.
  • the fourth value indicates that K pixel groups correspond to the same adjustment value; if K pixel groups correspond to K adjustment values, the adjustment value grouping indication information may be a fifth value, and the fifth value may indicate that K pixel groups correspond to K adjustment values.
  • the encoding end can also encode the pixel group indication information corresponding to the K pixel groups in the code stream corresponding to the current image area, indicating the current image area.
  • the corresponding code stream carries the adjustment value of the pixel group corresponding to the pixel group indication information.
  • the encoding end may not encode the pixel group indication information corresponding to the pixel group in the code stream corresponding to the current image area, indicating that the pixel group indication information carried in the code stream corresponding to the current image area It is the adjustment value of all pixel groups.
  • the pixel group indication information is used to distinguish the pixel group of the target category among the pixel groups of all categories, that is, to distinguish the pixel group from all the pixel groups. Out of K pixel groups.
  • the adjustment value corresponding to the pixel group may include the adjustment value of multiple channels or a single channel corresponding to the pixel group.
  • the multiple channels or A single channel may include at least one of the following channels: Y channel, U channel, V channel, Co channel, Cg channel, R channel, G channel, B channel, alpha channel, IR channel, D channel, W channel.
  • multiple channels include Y channel, U channel, V channel, or multiple channels include R channel, G channel, and B channel, or multiple channels include R channel, G channel, B channel, and alpha channel
  • the multiple channels may include R channel, G channel, B channel, and IR channel
  • the multiple channels may include R channel, G channel, B channel, and W channel
  • the multiple channels may include R channel, G channel, B channel.
  • channel, IR channel, W channel, or the multiple channels include R channel, G channel, B channel, and D channel
  • the multiple channels may include R channel, G channel, B channel, D channel, and W channel.
  • RGB color photosensitive channels there may also be IR channels (infrared or near-infrared photosensitive channels), D channels (dark light channels, mainly through infrared light or near-infrared light), and W channels (full-color photosensitive channels).
  • the sensors have different channels, for example, the sensor type can be RGB sensor, RGBIR sensor, RGBW sensor, RGBIRW sensor, RGBD sensor, RGBDW sensor, etc.
  • the current image area corresponds to multiple pixel groups, which may include but is not limited to the following methods: determine the multiple pixel groups corresponding to the current image area based on the pre-adjusted reconstruction value of each pixel point; or, based on the surrounding pixel points of the pixel point
  • the pre-adjusted reconstruction value determines the classification value of the pixel, and determines the multiple pixel groups corresponding to the current image area according to the classification value of each pixel point; or, determines the multiple pixel groups corresponding to the current image area according to the pixel position of each pixel point.
  • the number of divisions, filtering areas and division methods of the pixel groups can be determined according to the prediction mode of the current image area; based on the number of divisions, the filtering The area and the division method determine the multiple pixel groups corresponding to the current image area.
  • the prediction mode of the current image area is the horizontal prediction mode
  • it is determined that the number of divisions of the pixel group is the first division number
  • it is determined that the filtering area of the pixel group is the first filtering area
  • it is determined that the dividing method is the first size specification
  • the prediction mode of the current image area is not the horizontal prediction mode
  • it is determined that the number of divisions of the pixel group is the second division number
  • the filtering area of the pixel group is determined to be the second filtering area
  • the dividing method is determined to be the second size specification.
  • the current image area is a 16*2 image block (i.e. one image block)
  • the prediction mode of the current image area is the horizontal prediction mode
  • the current image area will be All pixels are divided into 4 pixel groups, and the size of each pixel group is 8*1; or, all pixels in the current image area are divided into 2 pixel groups, and the size of each pixel group is 16*1.
  • the prediction mode of the current image area is not the horizontal prediction mode, all pixels in the current image area are divided into 4 pixel groups, and the size of each pixel group is 4*2.
  • the current image area is a 16*2 image block
  • all pixels in the current image area can also be directly divided into 4 pixel groups, and the size of each pixel group is 4*2, regardless of Prediction mode for the current image area.
  • the value range of the adjustment value may be determined based on the quantization step size.
  • the above execution sequence is only an example given for convenience of description. In actual applications, it can also be changed. There is no restriction on the execution order between the steps. Moreover, in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this specification, and the method may include more or fewer steps than described in this specification. In addition, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may also be combined into a single step for description in other embodiments.
  • a shallow coding method is proposed, which can be applied to scenarios with high real-time requirements, small cache, and high parallelism requirements.
  • After obtaining the reconstruction value of the current image area it can also The reconstruction value of the current image area is adjusted to make the reconstructed pixels closer to the original pixels, which improves the encoding performance and decoding performance.
  • the quantization error is reduced, especially in flat areas, and the color block problem caused by the overall deviation can be reduced, which can reduce subjective loss. That is, the shallow coding method can achieve subjective losslessness and simple hardware implementation.
  • Embodiment 2 The embodiment of this application proposes a decoding method. See Figure 4, which is a schematic flow chart of the decoding method. The method can be applied to the decoding end (also called a video decoder). The method can include :
  • Step 401 Determine whether the reconstruction value of the current image area needs to be adjusted based on the feature information corresponding to the current image area.
  • an explicit method can be used to determine whether the reconstruction value of the current image area needs to be adjusted.
  • the feature information involved in the explicit method is called the first type of feature information.
  • the first type of feature information corresponding to the current image area can be obtained. If the first type of feature information corresponding to the current image area meets a specific condition (such as a first specific condition), the adjustment can be obtained from the code stream corresponding to the current image area. Control the flag bit corresponding to the switch, and determine whether the reconstruction value of the current image area needs to be adjusted based on the flag bit. Wherein, if the flag bit has a first value, it can be determined that the reconstruction value adjustment of the current image area needs to be performed; if the flag bit has a second value, it can be determined that the reconstruction value adjustment of the current image area does not need to be performed.
  • a specific condition such as a first specific condition
  • the first type of feature information corresponding to the current image area does not meet specific conditions, it can be directly determined that there is no need to adjust the reconstruction value of the current image area, and there is no need to obtain the adjustment control switch correspondence from the code stream corresponding to the current image area. mark bit.
  • the current image area may include one image block, or the current image area may include multiple consecutive image blocks.
  • the code stream corresponding to the current image area refers to: the code stream related to the current image area, that is, the code stream contains information for processing the current image area. There is no restriction on the code stream corresponding to the current image area.
  • the first type of feature information corresponding to the current image area may include but is not limited to at least one of the following: prediction mode; data amount in the code stream buffer; quantization step size. Based on this, if the first type of feature information includes a prediction mode, when the prediction mode corresponding to the current image area is the specified prediction mode, it is determined that the prediction mode satisfies the specific condition; otherwise, it is determined that the prediction mode does not satisfy the specific condition. If the first type of characteristic information includes the amount of data in the code stream buffer, when the amount of data in the code stream buffer is within the preset data amount interval, it is determined that the amount of data in the code stream buffer meets specific conditions; otherwise, it is determined The amount of data in the stream buffer does not meet certain conditions.
  • the first type of feature information includes a quantization step size
  • the quantization step size corresponding to the current image area is within the preset step size interval, it is determined that the quantization step size satisfies the specific condition; otherwise, it is determined that the quantization step size does not meet the specific condition.
  • the specified prediction mode may be one or more of the common intra prediction modes; wherein: the common intra prediction mode includes the DC mode; or the common intra prediction mode includes the DC mode, the horizontal prediction mode and the Vertical prediction mode; Or, the common intra prediction mode includes DC mode and angle prediction mode; Or, the common intra prediction mode includes DC mode, angle prediction mode and Planar mode; Or, the common intra prediction mode includes DC mode, angle prediction mode and bilinear mode; alternatively, common intra prediction modes include DC mode, angle prediction mode, Planar mode and bilinear mode.
  • an implicit method can be used to determine whether the reconstruction value of the current image area needs to be adjusted.
  • the feature information involved in the implicit method is called the second type of feature information.
  • the second type of feature information corresponding to the current image area is obtained. If the second type of feature information corresponding to the current image area meets a specific condition (such as a second specific condition), it is determined that the reconstruction value of the current image area needs to be adjusted, If the second type of feature information corresponding to the current image area does not meet specific conditions, it is determined that there is no need to adjust the reconstruction value of the current image area.
  • a specific condition such as a second specific condition
  • Step 402 If it is determined that the reconstruction value of the current image area needs to be adjusted, the adjustment parameters corresponding to the current image area are obtained from the code stream corresponding to the current image area, and the adjustment parameters are used to adjust the reconstruction value.
  • Step 403 Adjust the reconstruction value of the current image area based on the adjustment parameter.
  • the adjustment parameters corresponding to the current image area may include multiple adjustment values
  • the current image area may correspond to multiple pixel groups
  • the multiple adjustment values may include adjustment values corresponding to K pixel groups.
  • a pixel group may be all or part of multiple pixel groups.
  • adjusting the reconstruction value of the current image area based on the adjustment parameter may include but is not limited to: adjusting the reconstruction value of the pixel points in the K pixel group based on multiple adjustment values.
  • K Can be a positive integer greater than or equal to 1.
  • adjusting the reconstruction values of the pixels in the K pixel groups based on multiple adjustment values may include but is not limited to the following methods: for each pixel group in the K pixel groups, if the multiple adjustment values include the pixel The adjustment value corresponding to the pixel group is adjusted based on the adjustment value corresponding to the pixel group, and the reconstruction value of each pixel point in the pixel group is adjusted to obtain the adjusted reconstruction value of each pixel point in the pixel group.
  • the decoder can also obtain the pixel group indication information corresponding to the K pixel groups from the code stream corresponding to the current image area; based on the pixel group
  • the instruction information selects K pixel groups from all pixel groups and associates multiple adjustment values with the K pixel groups. In this way, the reconstruction values of the pixels in the K pixel groups can be adjusted based on the multiple adjustment values. , that is, only the reconstruction values of pixels within K pixel groups are adjusted.
  • the pixel group indication information is used to distinguish the pixel group of the target category among the pixel groups of all categories, that is, to distinguish the pixel group from all the pixel groups. Out of K pixel groups.
  • the adjustment value corresponding to the pixel group may include the adjustment values of multiple channels corresponding to the pixel group, and the multiple channels may include at least one of the following channels: Y channel, U channel, V channel , R channel, G channel, B channel, alpha channel, IR channel, D channel, W channel.
  • multiple channels include Y channel, U channel, and V channel, or multiple channels include R channel, G channel, and B channel, or multiple channels include R channel, G channel, B channel, and alpha channel
  • the multiple channels may include R channel, G channel, B channel, and IR channel
  • the multiple channels may include R channel, G channel, B channel, and W channel
  • the multiple channels may include R channel, G channel , B channel, IR channel, W channel
  • the multiple channels may include R channel, G channel, B channel, D channel
  • the multiple channels may include R channel, G channel, B channel, D channel, W channel.
  • the adjustment value grouping indication information can also be obtained from the code stream corresponding to the current image area.
  • the adjustment value grouping indication information is used to indicate the mapping relationship between the adjustment value and the K pixel groups; based on the adjustment value grouping indication information M adjustment values are parsed from the code stream corresponding to the current image area, M is a positive integer, and M is less than or equal to K; the adjustment values corresponding to the K pixel groups can be determined based on the M adjustment values. For example, if the adjustment value grouping indication information is the fourth value, then M is 1. In this case, the decoder can determine that K pixel groups correspond to one adjustment value; if the adjustment value grouping indication information is the fifth value , then M is K. In this case, the decoding end can determine that K pixel groups correspond to K adjustment values.
  • parsing the M adjustment values from the code stream corresponding to the current image area may include: for each channel, parsing the code stream corresponding to the channel from the code stream corresponding to the current image area.
  • One or more adjustment values may be included in the code stream corresponding to the current image area.
  • the current image area corresponds to multiple pixel groups, which may include but is not limited to: determining the multiple pixel groups corresponding to the current image area according to the pre-adjusted reconstruction value of each pixel point; or, based on the adjustment of surrounding pixel points of the pixel point
  • the pre-reconstruction value determines the classification value of the pixel, and multiple pixel groups corresponding to the current image area are determined according to the classification value of each pixel point; or, multiple pixel groups corresponding to the current image area are determined according to the pixel position of each pixel point; or , Multiple pixel groups corresponding to the current image area are determined according to the prediction mode of the current image area; or multiple pixel groups corresponding to the current image area are determined according to the scanning order of the current image area.
  • the above methods are only examples and are not limited thereto.
  • the number of divisions, filtering areas and division methods of the pixel group can be determined according to the prediction mode of the current image area; then, based on the number of divisions, The filter area and the dividing method determine multiple pixel groups corresponding to the current image area.
  • determining the division number, filtering area and division method of the pixel group according to the prediction mode of the current image area may include: if the prediction mode of the current image area is the horizontal prediction mode, determining the division number of the pixel group to be the first division number , determine that the filter area of the pixel group is the first filter area, determine the division method is the first size specification; if the prediction mode of the current image area is not the horizontal prediction mode, determine the division number of the pixel group is the second division number, determine the pixel group The filtering area is the second filtering area, and the determined dividing method is the second size specification.
  • the current image area is a 16*2 image block (i.e. one image block)
  • the prediction mode of the current image area is the horizontal prediction mode
  • the current image area will be All pixels are divided into 4 pixel groups, and the size of each pixel group is 8*1; or, all pixels in the current image area are divided into 2 pixel groups, and the size of each pixel group is 16*1.
  • the prediction mode of the current image area is not the horizontal prediction mode, all pixels in the current image area are divided into 4 pixel groups, and the size of each pixel group is 4*2.
  • the current image area is a 16*2 image block
  • all pixels in the current image area can also be directly divided into 4 pixel groups, and the size of each pixel group is 4*2, regardless of Prediction mode for the current image area.
  • the value range of the adjustment value may be determined based on the quantization step size.
  • a shallow coding method is proposed, which can be applied to scenarios with high real-time requirements, small cache, and high parallelism requirements.
  • After obtaining the reconstruction value of the current image area it can also The reconstruction value of the current image area is adjusted to make the reconstructed pixels closer to the original pixels, which improves the encoding performance and decoding performance.
  • the quantization error is reduced, especially in flat areas, and the color block problem caused by the overall deviation can be reduced, which can reduce subjective loss. That is, the shallow coding method can achieve subjective losslessness and simple hardware implementation.
  • Embodiment 3 For Embodiment 1 and Embodiment 2, it can be determined whether the reconstruction value needs to be adjusted for the current image area. For example, for the encoding end, after encoding the code stream of N encoding blocks (N ⁇ 1), the encoding end can record P encoding blocks (P ⁇ N) among them as the current image area, and can determine whether it is needed. Adjust the reconstruction value of the current image area. For the decoding end, after parsing the code stream of N decoding blocks (N ⁇ 1), the decoding end can record the P decoding blocks (corresponding to the P encoding blocks on the encoding end) as the current image area, and can determine Whether it is necessary to adjust the reconstruction value of the current image area.
  • the predicted value of the current image area needs to be adjusted. That is to say, the predicted value of the current image area can be adjusted based on the adjustment parameters corresponding to the current image area.
  • the predicted value adjustment process and the reconstruction value adjustment process Similar details will not be described again in this embodiment.
  • the residual value adjustment process is the same as the reconstruction. The value adjustment process is similar and will not be described again in this embodiment.
  • Explicit syntax method The encoding end encodes the mark bit corresponding to the adjustment control switch in the code stream, and the decoder parses the mark bit corresponding to the adjustment control switch from the code stream, and determines whether the reconstruction value adjustment of the current image area needs to be based on the mark bit. .
  • This process may include:
  • Step S11 The encoding end determines whether the first type of feature information corresponding to the current image area meets the first specific condition.
  • step S12 may be performed, and if yes, step S13 may be performed.
  • the first type of feature information corresponding to the current image area may include but is not limited to at least one of the following: prediction mode; data amount in the code stream buffer; quantization step size.
  • prediction mode the prediction mode
  • data amount in the code stream buffer the quantization step size
  • the first type of feature information may include prediction modes.
  • the prediction mode corresponding to the current image area is the specified prediction mode, it can be determined that the first type of feature information satisfies the first specific condition; otherwise, when the prediction mode corresponding to the current image area is not the specified prediction mode, it can be determined that the first type of feature information The first specific condition is not met.
  • the first type of characteristic information may include the amount of data in the code stream buffer. When the amount of data in the code stream buffer is within the preset data amount interval, it can be determined that the first type of characteristic information satisfies the first specific condition; otherwise, when the amount of data in the code stream buffer is not within the preset data amount interval, It can be determined that the first type of characteristic information does not satisfy the first specific condition.
  • the preset data volume interval [a1, a2] can be configured in advance, a1 is used to represent the minimum value of the data volume, and a2 is used to represent the maximum value of the data volume. Both a1 and a2 can be configured based on experience, and there is no restriction on this. .
  • the data amount in the code stream buffer is greater than or equal to a1, and the data amount in the code stream buffer is less than or equal to a2, then the data amount in the code stream buffer is within the preset data amount interval. If the data amount in the code stream buffer is less than a1, or if the data amount in the code stream buffer is greater than a2, the data amount in the code stream buffer is not within the preset data amount range.
  • the amount of data in the code stream buffer is within the preset data amount interval, that is, the amount of data in the code stream buffer is less than or equal to a2
  • filtering is performed on the current image area (shown in Figure 1
  • overflow will not be triggered after adding filter parameters, that is, it will not cause the code stream buffer to exceed the buffer limit.
  • the first type of feature information may include quantization step size.
  • the quantization step corresponding to the current image area is within the preset step interval, it can be determined that the first type of feature information satisfies the first specific condition; otherwise, when the quantization step corresponding to the current image area is not within the preset step interval, It can be determined that the first type of characteristic information does not satisfy the first specific condition.
  • the preset step interval [b1, b2] can be configured in advance, b1 is used to represent the minimum value of the step, and b2 is used to represent the maximum value of the step. Both b1 and b2 can be configured based on experience, and there is no restriction on this. . If the quantization step corresponding to the current image area is greater than or equal to b1, and the quantization step corresponding to the current image area is less than or equal to b2, then the quantization step corresponding to the current image area is located in the preset step interval. If the quantization step corresponding to the current image area is less than b1, or if the quantization step corresponding to the current image area is greater than b2, then the quantization step corresponding to the current image area is not within the preset step interval.
  • the preset step interval can ensure that it does not affect the The subjective quantization step size is not adjusted.
  • b1 when configuring the value of b1, b1 can be configured based on experience, and there is no restriction on this.
  • b1 can be determined based on the input bit width of the current image area. The greater the input bit width of the current image area, the greater the value of b1. For example, when the input bit width of the current image area is 8 bits, the value of b1 can be 16. When the input bit width of the current image area is 10 bits, the value of b1 can be 24. When the input bit width of the current image area is 10 bits, the value of b1 can be 24. When it is 12bit, the value of b1 can be 32.
  • the above is just an example of the relationship between the input bit width and the minimum step size b1, and there is no limit to the minimum step size b1.
  • the quantization step size is greater than or equal to b1, that is, it meets the minimum value requirement of the preset step interval: for 8bit, QP ⁇ 16; for 10bit, QP ⁇ 24; for 12bit, QP ⁇ 32.
  • b2 when configuring the value of b2, b2 can be configured based on experience, and there is no restriction on this.
  • b2 can be an infinite value; b2 can also be a fixed value, such as 48, 60, 76, etc.
  • the first type of feature information may include the prediction mode and the amount of data in the code stream buffer.
  • the prediction mode corresponding to the current image area is the specified prediction mode and the data amount in the code stream buffer is within the preset data amount interval. It can be determined that the first type of feature information satisfies the first specific condition; otherwise, when the prediction mode corresponding to the current image area is not the specified prediction mode, and/or the data amount in the code stream buffer is not within the preset data amount interval, it is determined The first type of characteristic information does not satisfy the first specific condition.
  • the first type of feature information may include prediction mode and quantization step size.
  • the prediction mode corresponding to the current image area is the specified prediction mode, and the quantization step corresponding to the current image area is within the preset step interval, it can be determined that the first type of feature information satisfies the first specific condition; otherwise, the corresponding quantization step of the current image area is The prediction mode is not the specified prediction mode, and/or, when the quantization step size corresponding to the current image area is not within the preset step size interval, it is determined that the first type of feature information does not meet the first specific condition.
  • the first type of feature information may include the quantization step size and the amount of data in the code stream buffer.
  • the quantization step corresponding to the current image area is within the preset step interval, and the data amount in the code stream buffer is within the preset data amount interval, it is determined that the first type of feature information satisfies the first specific condition; otherwise, in the current image
  • the quantization step corresponding to the region is not within the preset step interval, and/or the data amount in the code stream buffer is not within the preset data amount interval, it is determined that the first type of characteristic information does not meet the first specific condition.
  • the first type of feature information may include the prediction mode, the amount of data in the code stream buffer and the quantization step size.
  • the prediction mode corresponding to the current image area is the specified prediction mode
  • the data amount in the code stream buffer is within the preset data amount interval
  • the quantization step corresponding to the current image area is within the preset step interval
  • the first type is determined
  • the feature information satisfies the first specific condition; otherwise, the prediction mode corresponding to the current image area is not the specified prediction mode, and/or, the data amount in the code stream buffer is not within the preset data amount interval, and/or, the current image area
  • the corresponding quantization step size is not within the preset step size interval
  • it is determined that the first type of feature information does not meet the first specific condition, that is, as long as one of the features does not satisfy it, it is determined that the first type of feature information does not meet the first specific condition.
  • the specified prediction mode may be one or more of the common intra prediction modes.
  • the specified prediction mode may also be a point-by-point prediction mode.
  • the normal intra prediction mode and the point-by-point prediction mode are just examples and are not limited thereto.
  • the preset step interval can also be set based on the specified prediction mode, such as setting the minimum value of the preset step interval based on the specified prediction mode.
  • the ordinary intra prediction mode can correspond to the first minimum value of the preset step interval, that is, the value of b1 can be the first minimum value
  • the point-by-point prediction mode can correspond to the second minimum value of the preset step interval, That is, the value of b1 can be the second minimum value.
  • the first minimum value can be greater than the second minimum value, and the first minimum value can also be less than the second minimum value.
  • the minimum value of the preset step interval can be related to the specified prediction mode.
  • Normal intra prediction modes may include DC modes.
  • the normal intra prediction mode may include DC mode, horizontal prediction mode, and vertical prediction mode.
  • the normal intra prediction mode may include DC mode and angle prediction modes (such as horizontal prediction mode, vertical prediction mode and other angle prediction modes).
  • the normal intra prediction mode may include DC mode, angle prediction mode, and Planar mode.
  • the normal intra prediction mode may include DC mode, angle prediction mode, and bilinear mode.
  • the common intra prediction mode may include DC mode, angle prediction mode, Planar mode, and bilinear mode.
  • the above are just examples of common intra prediction modes, and are not limited thereto. Based on each of the above common intra prediction modes, other types of intra prediction modes can also be used as common intra prediction modes.
  • Step S12 If the first type of feature information does not meet the first specific condition, the encoding end determines that there is no need to adjust the reconstruction value of the current image area, and does not encode the mark bit corresponding to the adjustment control switch in the code stream corresponding to the current image area.
  • Step S13 If the first type of feature information meets the first specific condition, the encoding end determines whether the reconstruction value needs to be adjusted for the current image area, and encodes the mark corresponding to the adjustment control switch in the code stream corresponding to the current image area. Bit.
  • the encoding end may determine whether the reconstruction value of the current image area needs to be adjusted, and there is no limit to the determination method. For example, the encoding end calculates the cost value of starting the reconstruction value adjustment of the current image area, recorded as the first-generation value, and calculates the cost value of turning off the reconstruction value adjustment of the current image area, recorded as the second-generation value. On this basis, if the first-generation value is less than the second-generation value, the encoding end determines that the reconstruction value adjustment of the current image area needs to be performed; otherwise, the encoding end determines that the reconstruction value adjustment of the current image area does not need to be performed.
  • the encoding end may encode the flag bit corresponding to the adjustment control switch in the code stream corresponding to the current image area. For example, if it is determined that the reconstruction value of the current image area needs to be adjusted, the flag bit may be a first value, and the first value indicates that the reconstruction value of the current image area needs to be adjusted. If it is determined that there is no need to adjust the reconstruction value of the current image area, the flag bit may be a second value, and the second value indicates that there is no need to adjust the reconstruction value of the current image area. Both the first value and the second value can be configured based on experience, for example, the first value is 0 and the second value is 1, or the first value is 1 and the second value is 0.
  • Step S14 The decoder determines whether the first type of feature information corresponding to the current image area satisfies the first specific condition.
  • step S15 may be performed, and if yes, step S16 may be performed.
  • step S14 is similar to step S11 and will not be repeated here.
  • Step S15 If the first type of feature information does not meet the first specific condition, the decoder determines that there is no need to adjust the reconstruction value of the current image area, nor does it need to decode the mark corresponding to the adjustment control switch from the code stream corresponding to the current image area. Bit.
  • Step S16 If the first type of feature information meets the first specific condition, the decoding end obtains the flag bit corresponding to the adjustment control switch from the code stream corresponding to the current image area, and determines whether the current image area needs to be reconstructed based on the flag bit. value adjustment. Among them, if the flag bit is the first value, the decoder can determine that the reconstruction value of the current image area needs to be adjusted; if the flag bit is the second value, the decoder can determine that the current image area does not need to be reconstructed. value adjustment.
  • both the encoding end and the decoding end can determine whether the reconstruction value adjustment needs to be performed on the current image area, and the conclusion of the reconstruction value adjustment can be applied to the current image area. If the reconstruction value of the current image area needs to be adjusted, for the encoding side, the reconstruction values of N coding blocks need to be adjusted, and for the decoding side, the reconstruction values of N decoding blocks need to be adjusted. If there is no need to adjust the reconstruction values of the current image area, for the encoding side, there is no need to adjust the reconstruction values of the N coding blocks, and for the decoding side, there is no need to adjust the reconstruction values of the N decoding blocks.
  • Embodiment 4 For Embodiment 1 and Embodiment 2, it can be determined whether the reconstruction value needs to be adjusted for the current image area. For example, for the encoding end, after encoding the code stream of N encoding blocks (N ⁇ 1), the encoding end can record the N encoding blocks as the current image area, and can determine whether the current image area needs to be reconstructed. Adjustment. For the decoding end, after parsing the code stream of N decoding blocks (N ⁇ 1), the decoding end can record the N decoding blocks (corresponding to the N encoding blocks on the encoding end) as the current image area, and can determine whether it is needed. Adjust the reconstruction value of the current image area.
  • Implicit export method The encoding end can implicitly derive whether the reconstruction value of the current image area needs to be adjusted based on the second type of feature information corresponding to the current image area.
  • the decoder can also implicitly derive based on the second type of feature information corresponding to the current image area. Whether the export requires reconstruction value adjustment for the current image area.
  • the process may include:
  • Step S21 The encoding end determines whether the second type of feature information corresponding to the current image area meets the second specific condition.
  • step S22 may be performed, and if yes, step S23 may be performed.
  • the second type of feature information corresponding to the current image area may include but is not limited to at least one of code-controlled overflow and underflow indication information, quantization parameters, reconstructed pixel features, and block positions.
  • Code-controlled overflow and underflow indication information Can
  • the quantization parameter may include but not limited to the quantization step size.
  • the current code rate is used to represent the average code rate of all code control units before the code control unit where the current image area is located;
  • the block position is the block position of the image block in the current image area, such as any image block in the current image area
  • the block position is used to represent the position of the image block in the current frame.
  • the current code rate, quantization parameters, reconstructed pixel features and block positions are just a few examples of the second type of feature information.
  • the second type of feature information There is no limit to this second type of feature information. Whether the second type of feature information meets the second specific condition can be including but not limited to:
  • the second type of feature information corresponding to the current image area may include the current code rate corresponding to the current image area.
  • the current code rate is also the code control information, that is, the overflow and underflow indication information of the code control. If the current code rate is less than the first code rate rate value, it is determined that the second type of characteristic information satisfies the second specific condition; otherwise, it is determined that the second type of characteristic information does not satisfy the second specific condition.
  • the first code rate value may be a code rate value configured based on experience. There is no restriction on the first code rate value. When the current code rate is less than the first code rate value, it may indicate that the code control information indicates the resource pool. (For example, the code stream buffer used to store bit streams) is sufficient.
  • a target upper limit code rate can be configured in advance.
  • the current code rate is close to the target upper limit code rate, it means that the code control information indicates that the resource pool is normal.
  • the code control information indicates that the resource pool is normal.
  • the sum of the thresholds it means that the code control information indicates that the resource pool is insufficient.
  • the target upper limit can be The difference between the code rate and the preset threshold is used as the first code rate value.
  • the second type of feature information corresponding to the current image area may include the block position corresponding to the current image area. If the block position corresponding to the current image area is located at the specified position, it is determined that the second type of feature information satisfies the second specific condition, Otherwise, if the block position corresponding to the current image area is not located at the specified position, it is determined that the second type of feature information does not meet the second specific condition.
  • the specified position can be the last L image blocks (L can be a positive integer greater than or equal to 1) of the current code control unit (that is, the code control unit where the current image area is located), or the specified position can be the current code control unit.
  • L can be a positive integer greater than or equal to 1
  • the specified position can be the current code control unit.
  • the specified position may be the Slice boundary position within the current frame. If the block position belongs to the Slice boundary position within the current frame, it is determined that the block position is located at the specified position; otherwise, it is determined that the block position is not located at the specified position.
  • the specified position can be the last L image blocks of the current code control unit and the Slice boundary position inside the current frame. If the block position belongs to the last L image blocks of the current code control unit, or the block position belongs to the inside of the current frame. Slice boundary position, then it is determined that the block position is at the specified position. If the block position does not belong to the last L image blocks of the current code control unit, and the block position does not belong to the Slice boundary position within the current frame, it is determined that the block position is not located at the specified position.
  • the second type of feature information corresponding to the current image area may include the quantization step size corresponding to the current image area. If the quantization step size is greater than the step size threshold, it is determined that the second type of feature information satisfies the second specific condition; otherwise, If the quantization step size is not greater than the step size threshold, it is determined that the second type of feature information does not meet the second specific condition.
  • the second type of feature information corresponding to the current image area may include the current code rate corresponding to the current image area and the block position corresponding to the current image area. On this basis, if the current code rate is less than the first code rate value, and the If the block position is located at the specified position, it is determined that the second type of feature information satisfies the second specific condition; otherwise, it is determined that the second type of feature information does not satisfy the second specific condition.
  • the second type of feature information corresponding to the current image area may include the current code rate corresponding to the current image area and the block position corresponding to the current image area. If the current code rate is less than the first code rate value, or the block position is located at the specified location, it is determined that the second type of characteristic information satisfies the second specific condition; otherwise, it is determined that the second type of characteristic information does not satisfy the second specific condition.
  • the second type of feature information corresponding to the current image area may include the current code corresponding to the current image area. rate and the quantization step corresponding to the current image area. If the current code rate is less than the first code rate value and the quantization step is greater than the step threshold, it is determined that the second type of feature information satisfies the second specific condition; otherwise, it is determined that the second type of feature information satisfies the second specific condition. The second type of feature information does not satisfy the second specific condition.
  • the second type of feature information corresponding to the current image area may include the current code rate corresponding to the current image area and the quantization step size corresponding to the current image area. If the current code rate is less than the first code rate value, or the quantization step size is greater than the step size threshold, it is determined that the second type of feature information satisfies the second specific condition; otherwise, it is determined that the second type of feature information does not meet the second specific condition.
  • the second type of feature information corresponding to the current image area may include the block position corresponding to the current image area and the quantization step size corresponding to the current image area. On this basis, if the block position is located at the specified position and the quantization step size is greater than the step size threshold, it is determined that the second type of feature information satisfies the second specific condition; otherwise, it is determined that the second type of feature information does not meet the second specific condition.
  • the second type of feature information corresponding to the current image area may include the block position corresponding to the current image area and the quantization step corresponding to the current image area, if the block position is located at a specified position, or the quantization step is greater than the step threshold , then it is determined that the second type of characteristic information satisfies the second specific condition; otherwise, it is determined that the second type of characteristic information does not satisfy the second specific condition.
  • the rate is less than the first code rate value, and the block position is at the specified position, and the quantization step is greater than the step threshold, then it can be determined that the second type of feature information satisfies the second specific condition, otherwise, it can be determined that the second type of feature information satisfies the second specific condition. The information does not satisfy the second specific condition.
  • the second type of feature information corresponding to the current image area may include the current code rate corresponding to the current image area, the block position corresponding to the current image area, and the quantization step corresponding to the current image area.
  • the current code rate is less than the first code rate value, or the block position is at a specified position, or the quantization step is greater than the step threshold, then it can be determined that the second type of feature information satisfies the second specific condition, otherwise, it can be determined that the second type of feature information satisfies the second specific condition.
  • the class characteristic information does not satisfy the second specific condition.
  • the second type of feature information corresponding to the current image area may include reconstructed pixel features corresponding to the current image area. On this basis, if the reconstructed pixel features indicate that the complexity of the current image area is simple, it can be determined that the The second type of characteristic information satisfies the second specific condition. Otherwise, it can be determined that the second type of characteristic information does not satisfy the second specific condition.
  • the reconstructed pixel feature can be the complexity (such as gradient) of the current image area calculated from the reconstructed pixels.
  • the Sobel operator can be used to evaluate the complexity of the current pixel area, and we get The complexity of the current image area; you can also transform the reconstructed pixel values of the current image area, and obtain the complexity of the current image area based on the characteristics of the transformation domain, such as the frequency domain; you can also calculate the horizontal and vertical gradients of the current image area, based on The horizontal and vertical gradients get the complexity of the current image area.
  • the above are just a few examples, as long as the reconstructed pixel features can be obtained, and the reconstructed pixel features can represent the complexity of the current image area.
  • the reconstructed pixel feature when the reconstructed pixel feature indicates that the complexity of the current image area is simple, it means that the reconstruction value of the current image area can be adjusted to reduce image loss. Therefore, it can be determined that the second type of feature information satisfies the second specific conditions.
  • the reconstructed pixel feature can be a complexity value.
  • the complexity value is greater than a preset threshold
  • the reconstructed pixel feature can indicate that the complexity of the current image area is complex. Otherwise, the complexity of the current image area is Simple.
  • there is no limit to the complexity of the current image area For example, when the complexity value is less than a preset threshold, the reconstructed pixel features can represent the complexity of the current image area as simple. Otherwise, the complexity of the current image area is simple. , the complexity of the current image area is complex.
  • the second type of feature information corresponding to the current image area may include reconstructed information corresponding to the current image area. Pixel features.
  • the second type of feature information corresponding to the current image area also includes at least one of the current code rate, block position and quantization step size. For convenience of description, it includes the current code rate, block position and quantization step at the same time. Taking the step size as an example, the implementation in other cases is similar.
  • the pixel feature indicates that the complexity of the current image area is simple, it can be determined that the second type of feature information satisfies the second specific condition; otherwise, it can be determined that the second type of feature information does not meet the second specific condition.
  • the second type of feature information corresponding to the current image area includes the reconstructed pixel features corresponding to the current image area.
  • the second type of feature information corresponding to the current image area also includes the current code rate, block position and quantization step. At least one of the length. For convenience of description, take the current code rate, block position and quantization step size as an example. The implementation in other cases is similar.
  • the current code rate is less than the first code rate value, or , the block position is at the specified position, or the quantization step is greater than the step threshold, or the reconstructed pixel feature represents the complexity of the current image area as simple, then it can be determined that the second type of feature information satisfies the second specific condition , otherwise, it can be determined that the second type of feature information does not satisfy the second specific condition.
  • Step S22 The encoding end determines that there is no need to adjust the reconstruction value of the current image area.
  • Step S23 The encoding end determines that the reconstruction value of the current image area needs to be adjusted.
  • Step S24 The decoding end determines whether the second type of feature information corresponding to the current image area meets the second specific condition.
  • step S25 may be performed, and if yes, step S26 may be performed.
  • step S24 is similar to step S21, and will not be repeated here.
  • Step S25 The decoding end determines that there is no need to adjust the reconstruction value of the current image area.
  • Step S26 The decoder determines that the reconstruction value of the current image area needs to be adjusted.
  • Embodiment 5 For Embodiment 1 and Embodiment 2, it can be determined whether the reconstruction value adjustment of the current image area is required. For example, for the encoding end, after encoding the code stream of N encoding blocks (N ⁇ 1), the encoding end can record the N encoding blocks as the current image area, and can determine whether the current image area needs to be reconstructed. Adjustment. For the decoding end, after parsing the code stream of N decoding blocks (N ⁇ 1), the decoding end can record the N decoding blocks (corresponding to the N encoding blocks on the encoding end) as the current image area, and can determine whether it is needed. Adjust the reconstruction value of the current image area.
  • the combined implementation method is the implementation method of explicit syntax + implicit export. For example, after the encoding end obtains the mark bit of the adjustment control switch corresponding to the current image area (see Embodiment 3), if the mark bit of the adjustment control switch is consistent with the target image area (such as the previous image area of the current image area, or If the mark bits of the adjustment control switches corresponding to a specified image area, or a default image area, etc.) are the same, the encoding end may not encode the mark bits of the adjustment control switches in the code stream corresponding to the current image area.
  • the decoder When the decoder learns that the code stream corresponding to the current image area does not carry the mark bit of the adjustment control switch, it can use the mark bit of the adjustment control switch corresponding to the target image area as the mark bit of the adjustment control switch corresponding to the current image area, and then determine Whether to adjust the reconstruction value of the current image area.
  • the encoding end After the encoding end obtains the mark bit of the adjustment control switch corresponding to the current image area, if the mark bit of the adjustment control switch is different from the mark bit of the adjustment control switch corresponding to the target image area, the encoding end can set the mark bit of the adjustment control switch corresponding to the current image area.
  • the decoding end can analyze the flag bit of the adjustment control switch corresponding to the current image area from the code stream, and determine whether to adjust the reconstruction value of the current image area based on the flag bit.
  • Embodiment 6 Regarding Embodiment 1 to Embodiment 5, after determining whether to perform reconstruction value adjustment on the current image area, if it is determined to perform reconstruction value adjustment on the current image area, the adjustment parameters corresponding to the current image area can be obtained.
  • This adjustment parameter can be used to adjust the reconstruction value of the current image area, that is, to adjust the reconstruction value (or prediction value, or residual value, etc.) of N image blocks in the current image area.
  • the current image area The domain can include N coding blocks, and the adjustment parameters can be used to adjust the reconstruction values of the N coding blocks.
  • the current image area can include N decoding blocks, and the adjustment parameters can be used to adjust the N decoding blocks.
  • the reconstruction value is adjusted.
  • the adjustment parameters corresponding to the current image area can be determined based on the original value of the current image area and the reconstructed value of the current image area.
  • the adjustment parameter is used to adjust the reconstruction value of the current image area so that the adjusted reconstruction value is close to the original value of the current image area. This embodiment does not limit the acquisition process of this adjustment parameter.
  • the adjustment parameters corresponding to the current image area may include multiple adjustment values, and the current image area may correspond to multiple pixel groups, that is, all pixels in the current image area may be divided into multiple pixel groups.
  • multiple The adjustment values may include adjustment values corresponding to K pixel groups, and the K pixel groups may be all pixel groups or part of the pixel groups among multiple pixel groups.
  • all pixels in the current image area can be divided into 32 pixel groups, and K pixel groups can be selected from the 32 pixel groups, such as 4 pixel groups, 8 pixel groups, 16 pixel groups, 32 pixel groups, etc. Pixel groups, etc., there is no limit to the value of K.
  • the encoding end obtains the adjustment parameters corresponding to the K pixel groups, that is, the adjustment parameters can include the adjustment values corresponding to the K pixel groups, and the adjustment value corresponding to each pixel group is used to adjust each pixel point in the pixel group.
  • the reconstruction value is adjusted. For example, assuming that the K pixel groups are pixel group 1 and pixel group 2, the encoding end can obtain the adjustment value corresponding to pixel group 1 and the adjustment value corresponding to pixel group 2.
  • the adjustment value corresponding to pixel group 1 is used to adjust the pixel group.
  • the reconstruction value of each pixel in pixel group 1 is adjusted, and the adjustment value corresponding to pixel group 2 is used to adjust the reconstruction value of each pixel in pixel group 2.
  • the adjustment value corresponding to the pixel group may include the adjustment value of multiple channels or a single channel corresponding to the pixel group.
  • multiple channels may include Y channel, U channel, and V channel, or multiple channels may include R channel, G channel, and B channel, or multiple channels may include R channel, G channel, B channel, alpha channel, or the plurality of channels may include R channel, G channel, B channel, IR channel, or the plurality of channels may include R channel, G channel, B channel, W channel, or the plurality of channels may include the R channel , G channel, B channel, IR channel, W channel, or the multiple channels may include R channel, G channel, B channel, D channel, or the multiple channels may include R channel, G channel, B channel, D channel , W channel.
  • a single channel can be any of the above channels. Of course, these are just a few examples.
  • two or more of the above channels can also use the same adjustment value.
  • the U channel and V channel can use the same adjustment value, or the R channel and G channel can use the same adjustment value. value, there is no limit on this.
  • the adjustment values corresponding to pixel group 1 include Y channel adjustment value 1, U channel adjustment value 1 and V channel adjustment value 1.
  • Y channel adjustment value 1 is used to reconstruct the Y channel value of each pixel in pixel group 1.
  • U channel adjustment value 1 is used to adjust the U channel reconstruction value of each pixel in pixel group 1.
  • V channel adjustment value 1 is used to adjust the V channel reconstruction value of each pixel in pixel group 1.
  • the adjustment values corresponding to pixel group 2 include Y channel adjustment value 2, U channel adjustment value 2 and V channel adjustment value 2.
  • Y channel adjustment value 2 is used to adjust the Y channel reconstruction value of each pixel in pixel group 2.
  • U channel adjustment value 2 is used to adjust the U channel reconstruction value of each pixel in pixel group 2
  • V channel adjustment value 2 is used to adjust the V channel reconstruction value of each pixel in pixel group 2.
  • the adjustment values of each channel corresponding to the pixel group may be different, may be the same, or may be partially the same and partially different.
  • the encoding end can also encode the adjustment parameters corresponding to the current image area in the code stream corresponding to the current image area.
  • the adjustment parameters may include adjustment values corresponding to K pixel groups. Therefore, the adjustment values corresponding to K pixel groups may be encoded in the code stream corresponding to the current image area.
  • the adjustment parameters corresponding to the current image area can be obtained from the code stream corresponding to the current image area.
  • the adjustment parameters are used to adjust the reconstruction value of the current image area so that the adjusted reconstruction value is close to the current image.
  • the original value of the area After obtaining the adjustment parameters, the reconstruction value of the current image area can be adjusted based on the adjustment parameters.
  • the adjustment parameters corresponding to the current image area may include multiple adjustment values. All pixels in the current image area may be divided into multiple pixel groups. On this basis, the multiple adjustment values may include K pixel groups corresponding to Adjustment value, K pixel groups can be all pixel groups or part of pixel groups in multiple pixel groups.
  • the decoding end can obtain the adjustment parameters corresponding to the K pixel groups from the code stream, that is, the adjustment parameters can include the adjustment values corresponding to the K pixel groups.
  • the decoder can adjust the reconstruction value of each pixel in the pixel group based on the adjustment value corresponding to the pixel group.
  • the decoding end can obtain the adjustment value corresponding to pixel group 1 and the adjustment value corresponding to pixel group 2, and the decoding end adjusts the pixels based on the adjustment value corresponding to pixel group 1.
  • the reconstruction value of each pixel in group 1 is adjusted, and the decoder adjusts the reconstruction value of each pixel in pixel group 2 based on the adjustment value corresponding to pixel group 2.
  • the adjustment value corresponding to the pixel group may include the adjustment value of multiple channels or a single channel corresponding to the pixel group.
  • the multiple channels may include Y channel, U channel, V channel, or , the multiple channels may include R channel, G channel, B channel, or the multiple channels may include R channel, G channel, B channel, alpha channel, or the multiple channels may include R channel, G channel, B channel , IR channel, or the multiple channels may include R channel, G channel, B channel, W channel, or the multiple channels may include R channel, G channel, B channel, IR channel, W channel, or multiple channels It may include an R channel, a G channel, a B channel, and a D channel, or the plurality of channels may include an R channel, a G channel, a B channel, a D channel, and a W channel.
  • a single channel can be any of the above channels. Of course, the above are just a few examples and are not limiting.
  • the decoder adjusts the reconstruction value of each pixel in the pixel group to obtain the adjusted reconstruction value of each pixel in the pixel group. For example, if the multiple adjustment values obtained from the code stream include Y channel adjustment value 1, U channel adjustment value 1 and V channel adjustment value 1 corresponding to pixel group 1, then pixel group 1 can be adjusted based on Y channel adjustment value 1. The Y channel reconstruction value of each pixel in pixel group 1 is adjusted based on the U channel adjustment value 1. The U channel reconstruction value of each pixel in pixel group 1 is adjusted based on the V channel adjustment value 1.
  • Each pixel in pixel group 1 is adjusted based on the V channel adjustment value 1.
  • the V channel reconstruction value of the point is adjusted. For another example, if the multiple adjustment values obtained from the code stream only include the Y channel adjustment value 1 corresponding to pixel group 1, but do not include the U channel adjustment value 1 and V channel adjustment value 1 corresponding to pixel group 1, then the decoding end The Y channel reconstruction value of each pixel in pixel group 1 can be adjusted based on the Y channel adjustment value 1.
  • the encoding end may not encode the K pixel groups in the code stream corresponding to the current image area.
  • the decoding end does not need to parse the pixel group indication information corresponding to K pixel groups from the code stream corresponding to the current image area.
  • the decoding end can learn that the adjustment parameters carried in the code stream are Adjustment value for all pixel groups (such as 32 pixel groups).
  • the encoding end can encode the pixel group indication information corresponding to the K pixel groups in the code stream corresponding to the current image area, indicating that the pixel group is carried in the code stream. Adjustment values of the K pixel groups corresponding to the indication information.
  • the decoder can parse the pixel group indication information corresponding to the K pixel groups from the code stream corresponding to the current image area, and learn that the adjustment parameters carried in the code stream are the adjustment values of the K pixel groups corresponding to the pixel group indication information.
  • the pixel group indication information includes index values of K pixel groups.
  • the index value indicates which pixel group the pixel group is among all pixel groups.
  • the K pixel groups include pixel group 1, pixel group 2, and pixel group.
  • the pixel group indication information may include the index value of pixel group 1 (the index value is used to indicate which pixel group pixel group 1 is among all pixel groups), the index of pixel group 2 value, the index value of pixel group 3 and the index value of pixel group 4.
  • the pixel group indication information is used to distinguish the pixel group of the target category among the pixel groups of all categories, that is, to distinguish the K pixel groups from all the pixel groups.
  • Pixel group, pixel group indication information can realize the classification function.
  • the pixel group indication information may include K pixel groups
  • the index value of the middle pixel group, and the index value of the remaining pixel group can be derived implicitly.
  • the pixel group indication information may only include the index value of pixel group 1. Since the K pixel groups are continuous pixel groups, therefore , the index value of pixel group 2, the index value of pixel group 3, and the index value of pixel group 4 can be derived implicitly.
  • the display method can be used to indicate the index values of the K pixel groups, or the display method can be used to indicate the index values of some pixel groups among the K pixel groups, and the indexes of the remaining pixel groups can be derived implicitly. value, there is no restriction on this in this embodiment, as long as the decoding end can obtain the index values of K pixel groups.
  • the K pixel groups are part of all pixel groups, and the K pixel groups are K pixel groups at the default position, for example, the K pixel groups are fixed to the first 4 pixel groups, or K The pixel group is fixed to the 1st, 3rd, 5th, and 7th pixel groups, or the K pixel groups are fixed to the next 4 pixel groups. Then, the encoding end does not need to encode the K pixel groups corresponding to the code stream corresponding to the current image area. Pixel group indication information, the decoding end does not need to parse the pixel group indication information corresponding to K pixel groups from the code stream corresponding to the current image area.
  • the decoding end learns that the adjustment parameters carried in the code stream are in the default position Adjustment values of K pixel groups, for example, the adjustment parameter is the adjustment value of the first 4 pixel groups, or the adjustment parameter is the adjustment value of the 1st, 3rd, 5th, and 7th pixel groups, or the adjustment parameter is the next 4 pixel groups adjustment value.
  • the adjustment parameters corresponding to the current image area include adjustment values corresponding to K pixel groups.
  • the adjustment parameters may include multiple adjustment values.
  • all or part of the adjustment values may be encoded in the code stream corresponding to the current image area. For example, take the adjustment value corresponding to a pixel group including the adjustment value of a single channel corresponding to the pixel group.
  • the K pixel groups are 12 pixel groups, among which the adjustment values of 4 pixel groups are the Y channel adjustment values, The adjustment value of the 4 pixel groups is the U channel adjustment value, and the adjustment value of the 4 pixel group is the V channel adjustment value.
  • the adjustment parameters corresponding to the current image area can include 12 adjustment values.
  • the 12 adjustment values can be encoded in the code stream corresponding to the current image area, or some of the 12 adjustment values can be encoded in the code stream corresponding to the current image area.
  • the decoding end when obtaining the adjustment parameters from the code stream corresponding to the current image area, if the encoding end encodes all the adjustment values corresponding to the K pixel groups, the decoding end can obtain them from the code stream corresponding to the current image area. All adjustment values corresponding to K pixel groups. If the encoding end encodes the partial adjustment values corresponding to the K pixel groups, the decoding end can obtain the partial adjustment values corresponding to the K pixel groups from the code stream corresponding to the current image area.
  • the decoding end For example, if the decoding end obtains the Y channel adjustment value, but does not obtain the U channel adjustment value and V channel adjustment value, the decoding end only reconstructs the Y channel reconstruction value of each pixel in the corresponding pixel group based on the Y channel adjustment value. Make adjustments without adjusting the U channel reconstruction value and V channel reconstruction value of each pixel in the pixel group. In addition, if the decoding end does not obtain the adjustment value of a certain pixel group among the K pixel groups, the decoding end will no longer adjust the reconstruction value of each pixel point in the pixel group.
  • the encoding end encodes all or part of the adjustment values in the code stream corresponding to the current image area, which may include but is not limited to the following steps:
  • Step S31 Sort the plurality of adjustment values according to their encoding order.
  • the adjustment values of 4 pixel groups are Y channel adjustment values
  • the adjustment values of 4 pixel groups are U channel adjustment values
  • the adjustment values of 4 pixel groups are Taking the V channel adjustment value as an example, the current image area corresponds to 12 adjustment values, and the encoding order of the 12 adjustment values can be determined.
  • the coding order of each pixel group can be determined. For example, when dividing multiple pixel groups according to the reconstructed value of each pixel point, the coding order of each pixel group can be determined according to the value range of each pixel group, such as according to the value range from small to large. Sort in order of large value, or sort in order of value range from large to small. Taking the order of value ranges from small to large as an example, assume that the value range corresponding to pixel group 1 is the smallest, the value range corresponding to pixel group 2 is the second smallest, and so on, the value range corresponding to pixel group 11 is the second largest, and the value range corresponding to pixel group 1 is the second largest. The value range corresponding to group 12 is the largest, that is, the value ranges from pixel group 1 to pixel group 12 increase sequentially. Then, the encoding order of each pixel group may be from pixel group 1 to pixel group 12.
  • the gradient value range of each pixel group can be used (that is, the gradient value result corresponding to each pixel group, such as the above-mentioned absolute value below 10 and other value ranges) Determine each pixel group encoding order. For example, sort according to the gradient value range from small to large, or sort according to the gradient value range from large to small.
  • the gradient value range corresponding to pixel group 1 is the smallest
  • the gradient value range corresponding to pixel group 2 is the second smallest
  • the gradient value corresponding to pixel group 11 The value range is the second largest
  • the gradient value range corresponding to pixel group 12 is the largest. That is, the corresponding gradient values from pixel group 1 to pixel group 12 increase in sequence.
  • the encoding order of each pixel group can be from pixel group 1 Up to pixel group 12 are encoded sequentially.
  • the coding order of each pixel group can be determined according to the block order corresponding to each pixel group. Taking the order of sorting from front to back in block order as an example, assume that the sub-region corresponding to pixel group 1 is the first block of the current image area, and the sub-region corresponding to pixel group 2 is the second block of the current image area. In this way, the sub-region corresponding to pixel group 11 is the eleventh block of the current image area, and the sub-region corresponding to pixel group 12 is the 12th block of the current image area. Then, the encoding order of each pixel group is from pixel group 1 Up to pixel group 12 are encoded sequentially.
  • the above methods are just a few examples of determining the encoding order of each channel, and there is no restriction on this.
  • the encoding order of each channel can be planned arbitrarily.
  • the encoding order of the multiple adjustment values may be determined based on the encoding order of each pixel group and the encoding order of each channel.
  • the coding order of the pixel group can be mainly used, and the coding order of each channel can be used as a supplement to determine the coding order of multiple adjustment values.
  • K pixel groups are 4 pixel groups, and each pixel group corresponds to 3 The adjustment value of the channel.
  • the encoding order of each pixel group is pixel group 1, pixel group 2, pixel group 3 and pixel group 4.
  • the encoding order of each channel is Y channel, U channel, V channel. For example, there are 12 adjustment values.
  • the encoding sequence can be: Y channel adjustment value, U channel adjustment value and V channel adjustment value of pixel group 1, Y channel adjustment value, U channel adjustment value and V channel adjustment value of pixel group 2, Y channel of pixel group 3 Adjustment value, U channel adjustment value and V channel adjustment value, Y channel adjustment value, U channel adjustment value and V channel adjustment value of pixel group 4.
  • the coding order of multiple adjustment values can be determined based on the coding order of each channel and the coding order of the pixel group as a supplement.
  • the coding order of the above 12 adjustment values can be: Y channel adjustment of pixel group 1 value, Y channel adjustment value of pixel group 2, Y channel adjustment value of pixel group 3, Y channel adjustment value of pixel group 4, U channel adjustment value of pixel group 1, U channel adjustment value of pixel group 2, pixel group 3 U channel adjustment value, U channel adjustment value of pixel group 4, V channel adjustment value of pixel group 1, V channel adjustment value of pixel group 2, V channel adjustment value of pixel group 3, V channel adjustment value of pixel group 4 .
  • the above are just two examples of the encoding order of multiple adjustment values. This embodiment does not limit the encoding order of multiple adjustment values, and the encoding order of multiple adjustment values can be configured arbitrarily.
  • Step S32 Traverse multiple adjustment values in sequence based on the sorting results.
  • the adjustment value of pixel group 1 is traversed for the first time, and the adjustment value of pixel group 2 is traversed for the second time.
  • Adjustment value the adjustment value of pixel group 3 is traversed for the third time, and the adjustment value of pixel group 4 is traversed for the fourth time; for the adjustment value of multiple channels corresponding to the pixel group, pixel group 1 is traversed for the first time.
  • the Y channel adjustment value is traversed for the second time, the U channel adjustment value of pixel group 1 is traversed, the V channel adjustment value of pixel group 1 is traversed for the third time, and the Y channel adjustment value of pixel group 2 is traversed for the fourth time.
  • Channel adjustment value is a pixel group corresponding to a single channel.
  • the traversal can also be performed according to the order of each channel. Taking the order of each channel as Y channel, U channel, and V channel as an example, the adjustment value of the Y channel is traversed during the first traversal.
  • each pixel group and each pixel channel may also have other orderings. The above are just examples of the traversal order, and this application does not limit this.
  • Step S33 For the currently traversed adjustment value, if after encoding the adjustment value in the code stream corresponding to the current image area, the current code rate is less than the second code rate value, then encode the adjustment value in the code stream corresponding to the current image area. , and continue to traverse the next adjustment value of this adjustment value, using the next adjustment value as the current traversed adjustment value.
  • the second code rate value may be configured based on experience, and there is no restriction on this.
  • the current code rate is less than the second code rate value, it means that the code control information indicates that the resource pool is sufficient.
  • a target upper limit code rate can be configured in advance.
  • the current code rate is close to the target upper limit code rate, it means that the code control information indicates that the resource pool is normal; when the current code rate is greater than the target upper limit code rate and the preset upper limit code rate, the code control information indicates that the resource pool is normal.
  • the code control information indicates that the resource pool is insufficient; when the current code rate is less than the difference between the target upper limit code rate and the preset threshold, it means that the code control information indicates that the resource pool is sufficient.
  • the difference between the target upper limit code rate and the preset threshold can be used as the second code rate value.
  • the second code rate value may be the same as the above-mentioned first code rate value, or may be different.
  • Step S34 For the currently traversed adjustment value, if after encoding the adjustment value in the code stream corresponding to the current image area, the current code rate is not less than the second code rate value, encoding in the code stream corresponding to the current image area may be prohibited. the adjustment value, and stops traversing the next adjustment value of the adjustment value, that is, ending the traversal process of multiple adjustment values.
  • the multiple adjustment values can be traversed in sequence. For the currently traversed adjustment value, if after encoding the adjustment value in the code stream, the current code rate is less than the second code rate value, then the adjustment value is encoded in the code stream, and the next adjustment value of the adjustment value is continued to be traversed; If the current code rate is not less than the second code rate value, the adjustment value is not encoded in the code stream, and the traversal of the next adjustment value of the adjustment value is stopped.
  • Embodiment 8 During the process of transferring adjustment parameters, the status of the code control will also be updated synchronously. After the coding adjustment parameters, if the code control is still in the underflow state (less than 0, such as when the current code rate is less than the second code rate value , indicating that the code control is still in the underflow state), then continue to code and adjust parameters. In case one, the adjustment parameters are gradually transferred in the form of channels, such as Y channel, U channel, V channel, R channel, G channel, B channel, alpha channel (some channels can also be shared, such as UV channel sharing), etc., if the code control status If it is an underflow, the parameters will be adjusted according to the order of encoding (parsing on the decoding end).
  • channels such as Y channel, U channel, V channel, R channel, G channel, B channel, alpha channel (some channels can also be shared, such as UV channel sharing), etc.
  • the adjustment parameters are gradually transferred in the form of pixel groups (at least one pixel), that is, according to a certain scanning order and grouping, the adjustment parameters are transferred one by one. For example, according to the Y channel first, then the U channel and then the V channel, each channel is processed vertically. Four groups of directions (such as 4 pixel groups), and then transfer the adjustment parameters group by group to gradually update the code control status.
  • the adjustment parameters express the adjustment of a certain type or multiple types of reconstruction values in N coding blocks (ie, the current image area).
  • the certain type or multiple types of reconstruction values can be passed through syntax or exported. Determined by the method, for example: unified agreement on the codec end; derived based on encoded information (such as mode information, reconstruction value information, etc.).
  • Embodiment 9 Regarding Embodiment 1 to Embodiment 8, for the encoding end and the decoding end, the current image area can correspond to multiple pixel groups. For example, all pixel points in the current image area are divided into multiple pixel groups, that is, all pixel points are divided into multiple pixel groups. Pixel points are classified. In this embodiment, the following method can be used to divide all pixels in the current image area into multiple pixel groups:
  • Method 1 Divide all pixels in the current image area into multiple pixel groups according to the pre-adjustment reconstruction value of each pixel, that is, you can use the pre-adjustment reconstruction value of each pixel (the subsequent reconstruction values used for grouping refer to the adjustment (pre-reconstruction value) is classified to obtain multiple pixel groups.
  • the value range of the reconstructed value can be divided into A pixel groups on average, and the pixel group is determined according to the range of the reconstructed value.
  • the reconstructed value with a bit width of 8 bits (value range 0 to 255) is divided into 16 pixel groups.
  • the 16 pixel groups range from 0 to 15, 16 to 31, 32 to 47, 48 to 63, ..., 240 to 255.
  • the pixel is divided into the first pixel group. If the reconstructed value of the pixel is in the range 16 to 31, the pixel is divided into the second pixel group. If the reconstructed value of the pixel is in the range 32 to 47, the pixel is divided into the third pixel group. If the reconstructed value of the pixel is in the range 48 to 63, the pixel is divided into the fourth pixel group.
  • the reconstruction value of a pixel is in the range of 240 to 255, the pixel is divided into the 16th pixel group.
  • all pixels in the current image area are divided into multiple pixels according to the reconstruction value of each pixel.
  • it can also be divided channel by channel. For example, taking the Y channel, U channel, and V channel as an example, if the Y channel reconstruction value of a pixel is in the range 0 to 15, then the Y channel reconstruction value of the pixel is divided into the first pixel group. Based on this, The Y channel reconstruction value of the pixel can be adjusted based on the Y channel adjustment value corresponding to the first pixel group. If the U channel reconstruction value of a pixel is in the range of 16 to 31, the U channel reconstruction value of the pixel is divided into the second pixel group.
  • the U channel adjustment value corresponding to the second pixel group can be used to adjust the U channel reconstruction value.
  • the U channel reconstruction value of the pixel is adjusted. If the V channel reconstruction value of a pixel is in the range of 16 to 31, the V channel reconstruction value of the pixel is divided into the second pixel group. Based on this, the V channel adjustment value corresponding to the second pixel group can be The V channel reconstruction value of the pixel is adjusted.
  • Method 2 Determine the classification value of the pixel based on the pre-adjustment reconstruction value of the surrounding pixels (the subsequent reconstruction values used for grouping refer to the pre-adjustment reconstruction value), and classify the current image according to the classification value of each pixel. All pixels in the area are divided into multiple pixel groups. For example, multiple pixel groups can be obtained by classifying according to the gradient value of each pixel.
  • a pixel can be classified according to the reconstructed values of the surrounding pixels. For example, using gradient information, the reconstructed values of the upper adjacent pixels of the pixel can be compared with the reconstructed values of the adjacent pixels on the left side of the pixel. The reconstructed value is subtracted to obtain the gradient value of the pixel. Pixels whose absolute value of the gradient value result is within a certain range can be defined as the same category. For example, those with absolute values below 10 are classified as the first category, those with absolute values between 10 and 30 are classified as the second category, and those with absolute values greater than 30 are classified as the second category. Category III.
  • the pixel is divided into the first pixel group. If the absolute value of the gradient value of the pixel is below 10 to 30, then the pixel is divided into the second pixel group. If the absolute value of the gradient value of the pixel is above 30, the pixel is divided into the third pixel group.
  • Method 3 Divide all pixels in the current image area into multiple pixel groups according to the pixel position of each pixel, that is, you can classify according to the pixel position of each pixel to obtain multiple pixel groups. For example, classification can be based on pixel positions, such as dividing the 16*2 current image area into four 4*2 sub-regions, and each 4*2 sub-region is divided into one category. On this basis, for a certain pixel, if the pixel is in the first 4*2 sub-area, the pixel can be divided into the first pixel group. If the pixel is in the second If the pixel is in the third 4*2 sub-area, the pixel can be divided into the second pixel group. If the pixel is in the third 4*2 sub-area, the pixel can be divided into the third pixel group. If the pixel is in the fourth 4*2 sub-region, the pixel can be divided into the fourth pixel group.
  • Each pixel can be divided into a pixel group, that is, each pixel is a pixel group, and different pixels correspond to different pixel groups. It can be understood that a pixel group includes one pixel.
  • the current image area can correspond to multiple pixel groups. For example, all pixel points in the current image area are divided into multiple pixel groups, that is, All pixels are classified.
  • the following method can be used to determine multiple pixel groups corresponding to the current image area: multiple pixel groups corresponding to the current image area are determined according to the prediction mode of the current image area. That is to say, the division of pixel groups can be based on the current image area. related to the regional prediction model. For example, the division attribute of the pixel group can be determined according to the prediction mode of the current image area, and multiple pixel groups corresponding to the current image area can be determined based on the division attribute.
  • the division attribute may include at least one of division number, filtering area, and division method. If the division attributes include the number of divisions, filter areas and division methods, the number of divisions, filter areas and division methods of the pixel group are determined based on the prediction mode of the current image area, and the corresponding number of the current image area is determined based on the number of divisions, filter areas and division methods. of multiple pixel groups. If the division attribute includes the number of divisions and the division method, the number of divisions and the division method of the pixel group are determined according to the prediction mode of the current image area, and the multiple pixel groups corresponding to the current image area are determined based on the number of divisions and the division method. Regarding the combination of other division attributes, the implementation methods are similar and will not be described again in this embodiment.
  • the number of divisions is used to indicate how many pixel groups the current image area is divided into
  • the filter area is used to indicate which part of the current image area is divided into multiple pixel groups
  • the division method is used to indicate the size specifications of each pixel group.
  • the filter area may mean dividing the entire current image area into multiple pixel groups, or it may mean dividing a part of the current image area into multiple pixel groups. If the division attribute does not include the filter area, it means that the entire area of the current image area is divided into multiple pixel groups.
  • the prediction mode of the current image area can be distinguished into a horizontal prediction mode and a non-horizontal prediction mode. If the prediction mode of the current image area is a horizontal prediction mode, it can be determined that the number of divisions of the pixel group is the first division number, and it is determined The filter area of the pixel group is the first filter area, and the division method is determined to be the first size specification; if the prediction mode of the current image area is not the horizontal prediction mode, it can be determined that the division number of the pixel group is the second division number, and the division number of the pixel group is determined. The filtering area is the second filtering area, and the determination method of dividing is the second size specification.
  • the prediction mode of the current image area is the horizontal prediction mode, it can be determined that the number of divisions of the pixel group is the first division number, and the division method is the first size specification; if the prediction mode of the current image area is not the horizontal prediction mode, then It can be determined that the number of divisions of the pixel group is the second division number, and the division method is determined to be the second size specification.
  • the prediction mode of the current image area can be divided into a vertical prediction mode and a non-vertical prediction mode. If the prediction mode of the current image area is the vertical prediction mode, it can be determined that the number of divisions of the pixel group is the third division number, and the number of divisions of the pixel group can be determined.
  • the filter area of the group is the third filter area, and the division method is determined to be the third size specification; if the prediction mode of the current image area is not the vertical prediction mode, it can be determined that the number of divisions of the pixel group is the fourth division number, and the filtering of the pixel group is determined
  • the area is the fourth filtering area, and the determination method of dividing is the fourth size specification.
  • the prediction mode of the current image area is the vertical prediction mode
  • the ways of distinguishing the horizontal prediction mode and the non-horizontal prediction mode, and the ways of distinguishing the vertical prediction mode and the non-vertical prediction mode are just two examples and are not limited thereto.
  • the prediction mode of the current image area can be divided into a first prediction mode and a non-first prediction mode.
  • the first prediction mode corresponds to the first division attribute (number of divisions, filtering area and division method)
  • the non-first prediction mode Corresponds to the second division attribute (number of divisions, filtering area and division method).
  • the prediction mode of the current image area can be distinguished into a first prediction mode, a second prediction mode, and a non-first and non-second prediction mode.
  • the first prediction mode corresponds to the first division attribute (number of divisions, filter area and division method)
  • the second prediction mode corresponds to the second division attribute (number of divisions, filtering area, and division method)
  • the non-first and non-second prediction modes correspond to the third division attribute (number of divisions, filtering area, and division method).
  • the prediction mode of the current image area can be divided into a first prediction mode and a second prediction mode.
  • the first prediction mode corresponds to the first division attribute (number of divisions, filtering area and division method)
  • the second prediction mode corresponds to the first division attribute. Two types of division attributes (number of divisions, filter area and division method), and so on.
  • the prediction mode of the current image area is divided into a horizontal prediction mode and a non-horizontal prediction mode as an example. If the prediction mode of the current image area is the horizontal prediction mode, it is determined that the number of divisions of the pixel group is the first division number, the filtering area of the pixel group is determined to be the first filtering area, and the dividing method is determined to be the first size specification; if the current image area The prediction mode is not the horizontal prediction mode, then it is determined that the number of divisions of the pixel group is the second division number, it is determined that the filtering area of the pixel group is the second filtering area, and it is determined that the dividing method is the second size specification.
  • the number of first divisions can be configured according to experience, for example, it can be 2, 4, 6, 8, 16, etc., and there is no limit to this.
  • the first filtering area it may be the entire area of the current image area, or it may be a part of the current image area, and there is no limitation on this.
  • the first size specification it can be configured based on experience.
  • the first size specification can include width and height.
  • the width can be 2, 4, 6, 8, 12, 16, etc. There is no limit to this.
  • the height can be 1, 2, 16, etc. 4, 6, 8, 12, 16, etc., there is no limit to this.
  • the number of second divisions can be configured based on experience, for example, it can be 2, 4, 6, 8, 16, etc., without limitation.
  • the second filtering area it may be the entire area of the current image area, or it may be a partial area of the current image area, and there is no limitation on this.
  • the second size specification it can be configured based on experience.
  • the second size specification can include width and height.
  • the width can be 2, 4, 6, 8, 12, 16, etc. There is no limit on this.
  • the height can be 1, 2, 4, 6, 8, 12, 16, etc., there is no restriction on this.
  • the current image area is a 16*2 image block
  • all pixels in the current image area can be divided into 4 pixel groups, and each pixel group
  • the size is 8*1; in this case, the first division number is 4, the first filter area is the entire area of the current image area, and the first size specification is 8*1, as shown in Figure 5A, which is 16*2
  • the image block is divided into four 8*1 pixel groups.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 16*1; in this case, the first division number is 2, and the first filter area is the current image area. For all areas, the first size specification is 16*1. As shown in Figure 5B, the 16*2 image block is divided into two 16*1 pixel groups.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 4*2; in this case, the first division number is 4, and the first filter area is the current image area. For all areas, the first size specification is 4*2. As shown in Figure 5C, the 16*2 image block is divided into four 4*2 pixel groups.
  • all pixels in the current image area can be divided into 8 pixel groups, and the size of each pixel group is 2*2; in this case, the first division number is 8, and the first filter area is the current image area. For all areas, the first size specification is 2*2. As shown in Figure 5D, the 16*2 image block is divided into eight 2*2 pixel groups.
  • the current image area is a 16*2 image block
  • the prediction mode of the current image area is not the horizontal prediction mode
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 4*2.
  • the second division number is 4,
  • the second filter area is the entire area of the current image area, and the second size specification is 4*2.
  • the 16*2 image block is divided into 4 A 4*2 pixel group.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 8*1; in this case, the second division number is 4, and the second filter area is the current image area. For all areas, the second size specification is 8*1. As shown in Figure 5A, the 16*2 image block is divided into four 8*1 pixel groups.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 16*1; in this case, the second division number is 2, and the second filter area is the current image area. For all areas, the second size specification is 16*1. As shown in Figure 5B, the 16*2 image block is divided into two 16*1 pixel groups.
  • all pixels in the current image area can be divided into 8 pixel groups, and the size of each pixel group is 2*2; in this case, the second division number is 8, and the second filter area is the current image area. For all areas, the second size specification is 2*2. As shown in Figure 5D, the 16*2 image block is divided into eight 2*2 pixel groups.
  • the current image area is an 8*2 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and each pixel group The size is 4*2; in this case, the first division number is 2, the first filter area is the entire area of the current image area, and the first size specification is 4*2.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 8*1; in this case, the first division number is 2, and the first filter area is the current image area. In all areas, the first size specification is 8*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 8*2; in this case, the first division number is 1, and the first filter area is the current image area. In all areas, the first size specification is 8*2.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 2*2; in this case, the first division number is 4, and the first filter area is the current image area. In all areas, the first size specification is 2*2.
  • the above are just a few examples of division in horizontal prediction mode, and there is no limitation on this.
  • the current image area is an 8*2 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 4*2; in this case, the second division number is 2, the second filter area is the entire area of the current image area, and the second size specification is 4*2.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 8*1; in this case, the second division number is 2, and the second filter area is the current image area. For all areas, the second size specification is 8*1.
  • the second division number is 1, the second filter area is the entire area of the current image area, and the second size specification is 8*2.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 2*2; in this case, the second division number is 4, and the second filter area is the current image area. In all areas, the second size specification is 2*2.
  • the above are just a few examples of division in non-horizontal prediction mode, and are not limiting.
  • the current image area is a 16*1 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and each pixel group The size is 8*1; in this case, the first division number is 2, the first filter area is the entire area of the current image area, and the first size specification is 8*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 4*1; in this case, the first division number is 4, and the first filter area is the current image area. In all areas, the first size specification is 4*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 16*1; in this case, the first division number is 1, and the first filter area is the current image area. In all areas, the first size specification is 16*1.
  • all pixels in the current image area can be divided into 8 pixel groups, and the size of each pixel group is 2*1; in this case, the first division number is 8, and the first filter area is the current image area. In all areas, the first size specification is 2*1.
  • the above are just a few examples of division in horizontal prediction mode, and there is no limitation on this.
  • the current image area is a 16*1 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 8*1; in this case, the second division number is 2, the second filter area is the entire area of the current image area, and the second size specification is 8*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 4*1; in this case, the second division number is 4, and the second filter area is the current image area. In all areas, the second size specification is 4*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 16*1; in this case, the second division number is 1, and the second filter area is the current image area.
  • the second size specification is 16*1.
  • all pixels in the current image area can be divided into 8 pixel groups, and the size of each pixel group is 2*1; in this case, the second division number is 8, and the second filter area is the current image area. In all areas, the second size specification is 2*1.
  • the above are just a few examples of division in non-horizontal prediction mode, and are not limiting.
  • the current image area is an 8*1 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and each pixel group The size is 4*1; in this case, the first division number is 2, the first filter area is the entire area of the current image area, and the first size specification is 4*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 2*1; in this case, the first division number is 4, and the first filter area is the current image area. In all areas, the first size specification is 2*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 8*1; in this case, the first division number is 1, and the first filter area is the current image area. In all areas, the first size specification is 8*1.
  • the above are just a few examples of division in horizontal prediction mode, and there is no limitation on this.
  • the current image area is an 8*1 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 4*1; in this case, the second division number is 2, the second filter area is the entire area of the current image area, and the second size specification is 4*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 2*1; in this case, the second division number is 4, and the second filter area is the current image area. In all areas, the second size specification is 2*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 8*1; in this case, the second division number is 1, and the second filter area is the current image area. For all areas, the second size specification is 8*1.
  • the above are just a few examples of division in non-horizontal prediction mode, and are not limiting.
  • the current image area can correspond to multiple pixel groups. For example, all pixel points in the current image area are divided into multiple pixel groups, that is, All pixels are classified.
  • the following method may be used to determine multiple pixel groups corresponding to the current image area: using a default strategy to determine multiple pixel groups corresponding to the current image area.
  • a default strategy can be used to determine the division attributes of the pixel group, and multiple pixel groups corresponding to the current image area are determined based on the division attributes.
  • the division attribute may include at least one of division number, filter area and division method.
  • the division attribute includes division number, filter area and division method, determine the division number, filter area and division method of the pixel group. , and determine multiple pixel groups corresponding to the current image area based on the number of divisions, filtering areas and division methods. If the division attribute includes the division number and the division method, the division number and division method of the pixel group are determined, and multiple pixel groups corresponding to the current image area are determined based on the division number and the division method. Among them, the number of divisions is used to indicate how many pixel groups the current image area is divided into, the filter area is used to indicate which part of the current image area is divided into multiple pixel groups, and the division method is used to indicate the size specifications of each pixel group. .
  • the number of divisions, the filtering area and the dividing method can all be specified based on the default policy.
  • the specified number of divisions is the first division number
  • the filtering area is the first filtering area
  • the dividing method is the first size specification.
  • specify The division number is the second division number
  • the filter area is the second filter area
  • the division method is the second size specification.
  • the number of divisions can be configured according to experience, for example, it can be 2, 4, 6, 8, 16, etc., and there is no limit to this.
  • the filtering area can be the entire area of the current image area, or it can be a part of the current image area, and there is no limit to this.
  • the size specifications corresponding to the division method can be configured based on experience.
  • the size specifications can include width and height.
  • the width can be 2, 4, 6, 8, 12, 16, etc. There is no limit to this.
  • the height can be 1, 2, 4, 6, 8, 12, 16, etc., there is no limit to this.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 8*1.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 16*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 4*2.
  • all pixels in the current image area can be divided into 8 pixel groups, and the size of each pixel group is 2*2.
  • the above are just a few examples and are not limiting.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 4*2.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 8*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 8*2.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 2*2.
  • the above are just a few examples and are not limiting.
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 8*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 4*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 16*1.
  • all pixels in the current image area can be divided into 8 pixel groups, and the size of each pixel group is 2*1.
  • the above are just a few examples and are not limiting.
  • the current image area is an 8*1 image block
  • all pixels in the current image area can be divided into 2 pixel groups, and the size of each pixel group is 4*1.
  • all pixels in the current image area can be divided into 4 pixel groups, and the size of each pixel group is 2*1.
  • all pixels in the current image area can be divided into 1 pixel group, and the size of each pixel group is 8*1.
  • the above are just a few examples and are not limiting.
  • Embodiment 12 Regarding Embodiment 1 to Embodiment 8, for the encoding end and the decoding end, the current image area can correspond to multiple pixel groups. For example, all pixel points in the current image area are divided into multiple pixel groups, that is, All pixels are classified.
  • the following method can be used to determine multiple pixel groups corresponding to the current image area: multiple pixel groups corresponding to the current image area are determined according to the scanning order of the current image area. That is to say, the division of pixel groups can be the same as that of the current image area.
  • This method can be understood as: using the scanning order of the current image area, rearrange all pixels in the current image area into one dimension, and then divide the current image area into pixel groups.
  • the scanning order of the current image area can be understood at the encoding end as the order in which the residual coefficients are encoded into the code stream. Therefore, when determining the multiple pixel groups corresponding to the current image area based on the scanning order of the current image area, the order of the multiple pixel groups is consistent with the order in which the residual coefficients are encoded into the code stream. For each pixel in the pixel group When the reconstruction value is adjusted, the waiting time can be reduced, thereby improving the hardware processing performance of the encoding side. On the decoding end, it can be understood as the order of parsing the residual coefficients from the code stream.
  • the order of the multiple pixel groups is consistent with the residual
  • the parsing order of the coefficients is consistent.
  • the scanning order of the current image area may be a raster scanning order, such as a raster scanning order for sub-blocks of the current image area and a raster scanning order for the current image area.
  • a raster scanning order such as a raster scanning order for sub-blocks of the current image area and a raster scanning order for the current image area.
  • the 16*2 image block can be divided into 4 4*2 sub-blocks.
  • the 16*2 image block can also be divided into two 8*2 sub-blocks, or it can also be divided into sub-blocks of other sizes. There is no restriction on this.
  • the current image area can be divided into four 4*2 pixel groups.
  • the raster scanning sequence is to scan the pixels of the first sub-block first, then scan the pixels of the second sub-block, then scan the pixels of the third sub-block, and then scan the pixels of the fourth sub-block. Therefore, as shown in Figure 6B, each pixel point of the first sub-block can be divided into the first pixel group, each pixel point of the second sub-block can be divided into the second pixel group, and each pixel point of the third sub-block can be divided into The pixels are divided into the third pixel group, and each pixel of the fourth sub-block is divided into the fourth pixel group.
  • the current image area can be divided into two 8*2 pixel groups.
  • FIG. 6E it is a raster scanning sequence for the current image area (that is, the entire current image area).
  • the current image area can be divided into four pixel groups of 8*1, as shown in Figure 6F; the current image area can also be divided into four 8*1 pixel groups.
  • the image area is divided into two pixel groups of 16*1, as shown in Figure 6G.
  • the raster scanning sequence in Figure 6E is to first scan the 16 pixels in the first row, and then scan the 16 pixels in the second row. Therefore, the division method of Figure 6F or Figure 6G can be used.
  • the scanning order of the current image area can be interlaced scanning. Taking the current image area as an image block of 16*2 as an example, see Figure 6H, which is the scanning order for the current image area, that is, the first block is scanned first. The first pixel of row 1 is scanned, then the first pixel of row 2 is scanned, then the third pixel of row 1 is scanned, and so on.
  • the current image area can be divided into four 4*2 pixel groups, see Figure 6I, or the current image area can be divided into two 8*2 pixel groups, see Figure Shown in 6J.
  • the pixels in columns 1, 3, 5, and 7 can be combined into a pixel group
  • the pixels in columns 2, 4, 6, and 8 can be combined into a pixel group
  • the pixels in columns 15 form a pixel group
  • the pixels in columns 10, 12, 14, and 16 form a pixel group.
  • the pixels in columns 1, 3, 5, 7, 9, 11, 13, and 15 can be combined into a pixel group
  • the pixels in columns 2, 4, 6, 8, 10, 12, 14, and 16 can be combined into one pixel group.
  • the pixels form a pixel group.
  • Embodiment 13 Regarding Embodiment 1 to Embodiment 12, for the encoding end and the decoding end, the reconstruction value of the pixel point can be adjusted based on the adjustment value.
  • the value range of the adjustment value it can be [-7,7].
  • the value range of [-7,7] is just an example, and there is no limit to this.
  • the value range of the adjustment value can be [-4] ,4],[-5,5],[-6,6], [-8,8], the adjustment value range can also be [-4,6], [-6,5], [-6,8], [-8,4].
  • the adjustment value range The value range can be set arbitrarily.
  • the value range of the adjustment value can also be determined based on the quantization step size. That is to say, the value range of the adjustment value can be related to the quantization step size. For example, when the quantization step size is 8, the maximum quantization error is 4, then the range of the adjustment value can be [-4, 4]. In this case, the adjustment value less than -4 or greater than 4 is It won't happen. Obviously, as shown in Table 2, the binarization shown in Table 1 can be adjusted. Of course, in practical applications, different adjustment value ranges can be configured for different quantization step sizes, and there is no limit to this value range. For another example, when the quantization step size is 10, the range of the adjustment value can be [-5, 5], etc., and so on.
  • different quantization step sizes may correspond to different value ranges of the adjustment values, and the number of values within the value ranges of the adjustment values is the same, but there may be a value interval between two adjacent values.
  • the value range corresponding to the quantization step A is [-3, 3], and there are a total of 7 values, such as -3, -2, -1, 0, 1, 2, 3, while the quantization step B ( Quantization step size B can be larger than quantization step size A)
  • the corresponding value range is [-6, 6], but there are only 7 values, such as -6, -4, -2, 0, 2, 4, 6, quantization
  • the corresponding value range of step size C (quantization step size C can be greater than quantization step size B) is [-9, 9], but there are only 7 values, such as -9, -6, -3, 0, 3, 6 , 9, and so on.
  • Embodiment 14 Due to hardware limitations, in one possible implementation, the filtered reconstruction value of the current image area cannot be used as a reference for other image blocks in the same row, but can only be used for other images in the next row. Block reference. For other image blocks in the same row as the current image area, only the pre-filtered reconstruction value of the current image area can be referred to.
  • Embodiment 15 For Embodiment 1 to Embodiment 13, the code stream sent from the encoding end to the decoding end needs to carry the following content:
  • the adjustment parameter may include multiple adjustment values.
  • the adjustment parameter may include one adjustment value for the channel, or may include at least two adjustment values for the channel.
  • one channel is used as example.
  • the current image area may correspond to multiple pixel groups.
  • the code stream corresponding to the current image area only includes adjustment values corresponding to K pixel groups, and the K pixel groups are part or all of the multiple pixel groups. Pixel group.
  • M can be a positive integer, and M can be less than or equal to K. That is to say, M is greater than or equal to 1, and less than or equal to K. .
  • K pixel groups correspond to the same adjustment value, such as adjustment value A
  • the code stream corresponding to the current image area can only include 1 adjustment value, that is, adjustment value A. Therefore, M adjustment values are 1 Adjustment value.
  • the code stream corresponding to the current image area can include 2 adjustments. values, namely adjustment value A and adjustment value B. Therefore, M adjustment values are 2 adjustment values.
  • the code stream corresponding to the current image area may include four adjustment values, namely adjustment value A corresponding to pixel group 1, adjustment value A corresponding to pixel group 2, adjustment value B corresponding to pixel group 3, and adjustment value B corresponding to pixel group 4. Adjustment value B, therefore, M adjustment values are 4 adjustment values.
  • K pixel groups correspond to K adjustment values, such as pixel group 1 corresponds to adjustment value A, pixel group 2 corresponds to adjustment value B, pixel group 3 corresponds to adjustment value C, and pixel group 4 corresponds to adjustment value D, then the current image area corresponds to
  • the code stream can include 4 adjustment values, namely adjustment value A, adjustment value B, adjustment value C and adjustment value D. Therefore, M adjustment values are 4 adjustment values.
  • Pixel group indication information When the current image area corresponds to multiple pixel groups (such as 32 pixel groups), the pixel group indication information can be used to indicate K pixel groups in all pixel groups, indicating that the code stream carries the adjustments corresponding to these K pixel groups. value. Obviously, if K pixel groups are all pixel groups, then there is no need to carry pixel group indication information in the code stream, and the decoder can know that K pixel groups are all pixel groups (such as 32 pixel groups). If the K pixel groups are part of the total pixel groups, the decoder needs to know which pixel groups the K pixel groups are. In this case, the following method can be used:
  • Display mode When the encoding end sends the code stream corresponding to the current image area to the decoder, the code stream corresponding to the current image area carries the pixel group indication information, indicating that the code stream carries the adjustment of the pixel group corresponding to the pixel group indication information. value.
  • the decoder can parse the pixel group indication information corresponding to the K pixel groups from the code stream corresponding to the current image area, and learn that the adjustment parameters carried in the code stream are the adjustment values of the K pixel groups corresponding to the pixel group indication information.
  • the pixel group indication information includes index values of K pixel groups. These index values indicate which pixel group the pixel group is among all pixel groups.
  • the K pixel groups include pixel group 1, pixel group 2, and pixel group. Taking 3 and pixel group 4 as an example, the pixel group indication information may include the index value of pixel group 1, the index value of pixel group 2, the index value of pixel group 3, and the index value of pixel group 4.
  • the pixel group indication information may include index values of some pixel groups in the K pixel groups, and the index values of the remaining pixel groups may be implicitly derived.
  • the pixel group indication information may only include the index value of pixel group 1. Since the K pixel groups are continuous pixel groups, therefore , the index value of pixel group 2, the index value of pixel group 3, and the index value of pixel group 4 can be derived implicitly.
  • Implicit method If the K pixel groups are part of all pixel groups, and the K pixel groups are K pixel groups at the default position, for example, the K pixel groups are fixed to the first 4 pixel groups, or K The pixel group is fixed to the 1st, 3rd, 5th, and 7th pixel groups, or the K pixel groups are fixed to the next 4 pixel groups. Then, the encoding end does not need to encode the K pixel groups corresponding to the code stream corresponding to the current image area. For the pixel group indication information, the decoder does not need to parse the pixel group indication information corresponding to the K pixel groups from the code stream corresponding to the current image area.
  • the decoder can learn that the adjustment parameters carried in the code stream are the adjustment values of the K pixel groups at the default position.
  • the adjustment parameters are the adjustment values of the first 4 pixel groups, or the adjustment parameters are the 1st and 3rd pixel groups. , 5, 7 pixel group adjustment values, or adjust The parameter is the adjustment value of the next 4 pixel groups.
  • Adjust value grouping indication information When the code stream corresponding to the current image area carries M adjustment values corresponding to K pixel groups, the adjustment value grouping indication information is used to indicate the matching relationship between the M adjustment values and the K pixel groups.
  • the adjustment value grouping indication information may be a flag bit, that is, the adjustment value grouping indication information only has the fourth value and The fifth value.
  • the adjustment value grouping indication information may be a fourth value, and the fourth value represents the K pixels. Groups correspond to the same adjustment value.
  • the decoder parses the adjustment value group indication information from the code stream, if it learns that the adjustment value group indication information is the fourth value, it can only parse out one adjustment value (such as adjustment value A) from the code stream, and use this The adjustment value is used as the adjustment value corresponding to the K pixel group.
  • K pixel groups correspond to K adjustment values
  • K pixel groups correspond to adjustment value A, adjustment value B, adjustment value C and adjustment value D in sequence (or correspond to adjustment value A, adjustment value A, adjustment value B and adjustment value in sequence).
  • value B the adjustment value grouping indication information may be a fifth value, and the fifth value indicates that K pixel groups correspond to K adjustment values.
  • the decoder parses the adjustment value group indication information from the code stream, if it learns that the adjustment value group indication information is the fifth value, it needs to parse out K adjustment values from the code stream. For example, the adjustment value A, adjustment value A, and adjustment value A must be parsed out in sequence.
  • the first parsed adjustment value A corresponds to the first pixel group (for example, pixel group 1)
  • the second parsed adjustment value B corresponds to the second pixel group (for example, pixel group 2)
  • the second parsed adjustment value B corresponds to the second pixel group (for example, pixel group 2).
  • the three parsed adjustment values C correspond to the third pixel group (eg pixel group 3)
  • the fourth parsed adjustment value D corresponds to the fourth pixel group (eg pixel group 4).
  • same_offset_flag represents adjustment value grouping indication information. If the value of same_offset_flag is the fourth value (such as 1), the decoder needs to parse an adjustment value from the code stream. If the value of same_offset_flag is the fourth value, Five values (such as 0), the decoder needs to parse out K adjustment values from the code stream in sequence.
  • same_offset_flag is a flag bit that determines whether it is a unified compensation value. If same_offset_flag is the fourth value, it indicates a unified compensation value, that is, it is determined that K pixel groups correspond to the same adjustment value (this article The adjustment value can also be called the compensation value). At this time, only one adjustment value needs to be parsed. If same_offset_flag is the fifth value, it represents a non-uniform compensation value, that is, it is determined that K pixel groups correspond to K adjustment values. At this time, K adjustment values need to be parsed.
  • the adjustment value grouping indication information may have multiple values.
  • the adjustment value grouping indication information may be a fourth value, and the fourth value indicates that the K pixel groups correspond to the same adjustment value.
  • the decoding end obtains After knowing that the adjustment value grouping indication information is the fourth value, it can be learned that K pixel groups correspond to the same adjustment value.
  • the adjustment value grouping indication information may be a fifth value, which indicates that the first pixel group and the second pixel group correspond to one adjustment value, and the third pixel group and the fourth pixel group correspond to another adjustment value. Adjustment value.
  • the adjustment value group indication information is the fifth value, it determines that the first pixel group and the second pixel group correspond to one adjustment value, and the third pixel group and the fourth pixel group correspond to another an adjustment value.
  • the adjustment value group The indication information may be a third value.
  • the decoder learns that the adjustment value group indication information is the third value, it determines that the first pixel group and the fourth pixel group correspond to one adjustment value, and the second pixel group and the third pixel group correspond to another an adjustment value.
  • each value of the adjustment value grouping indication information corresponds to a mapping relationship, which can represent the matching relationship between M adjustment values and K pixel groups.
  • the correspondence between the value and the mapping relationship can be agreed on the encoding side and the decoding side, and there is no restriction on this.
  • the adjustment value grouping indication information is used to indicate the matching relationship between M adjustment values and K pixel groups.
  • the decoder parses the adjustment value grouping indication information from the code stream, it can parse M adjustment values from the code stream corresponding to the current image area based on the adjustment value grouping indication information, and determine K pixels based on the M adjustment values.
  • the adjustment value corresponding to the group is to determine the adjustment value corresponding to the K pixel group based on the matching relationship between the M adjustment values and the K pixel group.
  • each of the above embodiments can be implemented individually or in combination.
  • each embodiment in Embodiment 1 to Embodiment 15 can be implemented individually, and at least two of Embodiments 1 to 15 can be implemented individually.
  • the embodiments can be implemented in combination.
  • the content on the encoding side can also be applied to the decoding side, that is, the decoding side can be processed in the same way, and the content on the decoding side can also be applied to the encoding side, that is, the encoding side can be processed in the same way.
  • Embodiment 16 Based on the same application concept as the above method, an embodiment of the present application also proposes a decoding device, which is applied to the decoding end.
  • the decoding device includes: a memory configured to store video data; A decoder configured to implement the decoding method in the above-mentioned Embodiment 1 to Embodiment 15, that is, the processing flow of the decoding end.
  • a decoder is configured to:
  • the adjustment parameters corresponding to the current image area are obtained from the code stream corresponding to the current image area;
  • the reconstruction value of the current image area is adjusted based on the adjustment parameter.
  • the embodiment of the present application also proposes an encoding device, which is applied to the encoding end.
  • the encoding device includes: a memory configured to store video data; an encoder, which It is configured to implement the encoding method in the above-mentioned Embodiment 1 to Embodiment 15, that is, the processing flow of the encoding end.
  • an encoder is configured to:
  • the adjustment parameters corresponding to the current image area are obtained, and the adjustment parameters are used to adjust the reconstruction value of the current image area;
  • the adjustment parameters corresponding to the current image area are encoded in the code stream corresponding to the current image area.
  • the decoding end device (which may also be called a video decoder) provided by the embodiment of the present application, from a hardware level, its hardware architecture schematic diagram can be seen in FIG. 7A .
  • It includes: a processor 711 and a machine-readable storage medium 712.
  • the machine-readable storage medium 712 stores machine-executable instructions that can be executed by the processor 711; the processor 711 is used to execute the machine-executable instructions to implement the above implementation of the present application. Decoding methods for Examples 1 to 15.
  • the encoding end device (which may also be called a video encoder) provided by the embodiment of the present application, from a hardware level, its hardware architecture schematic diagram can be seen in Figure 7B. It includes: a processor 721 and a machine-readable storage medium 722.
  • the machine-readable storage medium 722 stores machine-executable instructions that can be executed by the processor 721; the processor 721 is used to execute machine-executable instructions to implement the above implementation of the present application. Coding methods for Examples 1 to 15.
  • embodiments of the present application also provide a machine-readable storage medium.
  • Several computer instructions are stored on the machine-readable storage medium.
  • the present invention can be realized. Apply the methods disclosed in the above examples, such as the decoding method or encoding method in the above embodiments.
  • embodiments of this application also provide a computer application program.
  • the computer application program When the computer application program is executed by a processor, it can implement the decoding method or encoding method disclosed in the above examples of this application.
  • the embodiment of the present application also proposes a decoding device.
  • the decoding device is applied to the decoding end.
  • the decoding device includes: a determination module for determining based on the characteristic information corresponding to the current image area. Whether it is necessary to adjust the reconstruction value of the current image area; the acquisition module is used to, if it is determined that the reconstruction value of the current image area needs to be adjusted, obtain the code stream corresponding to the current image area from the code stream corresponding to the current image area. Adjustment parameters; an adjustment module, configured to adjust the reconstruction value of the current image area based on the adjustment parameters.
  • the feature information includes the first type of feature information
  • the determination module is specifically used to determine whether the reconstruction value of the current image region needs to be adjusted based on the feature information corresponding to the current image region: if the current image region corresponds to The first type of feature information satisfies the first specific condition, then obtain the mark bit corresponding to the adjustment control switch from the code stream corresponding to the current image area, and determine whether the current image area needs to be reconstructed based on the mark bit. Adjustment; wherein, if the flag bit is the first value, it is determined that the reconstruction value of the current image area needs to be adjusted; if the flag bit is the second value, it is determined that the current image area does not need to be reconstructed. value adjustment.
  • the determination module determines whether the reconstruction value of the current image area needs to be adjusted based on the characteristic information corresponding to the current image area, it is specifically used: if the first type of characteristic information corresponding to the current image area does not satisfy the first specific condition, it is determined that there is no need to adjust the reconstruction value of the current image area.
  • the feature information includes the second type of feature information
  • the determination module is specifically used to determine whether the reconstruction value of the current image region needs to be adjusted based on the feature information corresponding to the current image region: if the current image region corresponds to If the second type of feature information satisfies the second specific condition, it is determined that the reconstruction value adjustment of the current image area needs to be performed; if the second type of feature information corresponding to the current image area does not meet the second specific condition, it is determined that it is not necessary Adjust the reconstruction value of the current image area.
  • the adjustment parameters corresponding to the current image area include multiple adjustment values
  • the current image area corresponds to multiple pixel groups
  • the multiple adjustment values include adjustment values corresponding to K pixel groups
  • the K pixel groups are all pixel groups or part of the pixel groups in the plurality of pixel groups
  • the adjustment module adjusts the reconstruction value of the current image area based on the adjustment parameter, it is specifically used to: for each of the K pixel groups A pixel group, if the plurality of adjustment values include an adjustment value corresponding to the pixel group, then the reconstruction value of the pixel point in the pixel group is adjusted based on the adjustment value corresponding to the pixel group.
  • the acquisition module is also used to obtain adjustment value grouping indication information from the code stream corresponding to the current image area; the adjustment value grouping indication information is used to indicate the adjustment value and the K pixel groups.
  • the adjustment values determine the adjustment values corresponding to the K pixel groups.
  • the determination module is also configured to determine multiple pixel groups corresponding to the current image area in a determining manner: determine multiple pixel groups corresponding to the current image area according to the pre-adjusted reconstruction value of each pixel point; or, based on The pre-adjusted reconstruction values of the surrounding pixels of the pixel determine the classification value of the pixel, and the multiple pixel groups corresponding to the current image area are determined according to the classification value of each pixel; or, the pixel position of each pixel is determined according to the pixel position of each pixel.
  • Pixel group Describe the current picture Multiple pixel groups corresponding to the image area; or, determine multiple pixel groups corresponding to the current image area according to the prediction mode of the current image area; or determine multiple pixel groups corresponding to the current image area according to the scanning order of the current image area. Pixel group.
  • the determination module determines multiple pixel groups corresponding to the current image area according to the prediction mode of the current image area, it is specifically used to: determine the number of divisions of the pixel group and the filter area according to the prediction mode of the current image area. and a dividing method; determining a plurality of pixel groups corresponding to the current image area based on the number of divisions, the filtering area and the dividing method.
  • the determination module determines the division number, filtering area and division method of the pixel group according to the prediction mode of the current image area, it is specifically used to: if the prediction mode of the current image area is a horizontal prediction mode, determine the division of the pixel group.
  • the number is the first division number, it is determined that the filter area of the pixel group is the first filter area, and the division method is determined to be the first size specification; if the prediction mode of the current image area is not a horizontal prediction mode, it is determined that the number of divisions of the pixel group is The second division number determines that the filter area of the pixel group is the second filter area, and determines the division method is the second size specification.
  • the embodiment of the present application also proposes a coding device.
  • the coding device is applied to the coding end.
  • the coding device includes: a determination module for determining based on the characteristic information corresponding to the current image area. Whether it is necessary to adjust the reconstruction value of the current image area; the acquisition module is used to obtain the adjustment parameters corresponding to the current image area if it is determined that the reconstruction value of the current image area needs to be adjusted, and the adjustment parameters are used to adjust the reconstruction value of the current image area.
  • the reconstruction value of the current image area is adjusted; an encoding module is used to encode the adjustment parameters corresponding to the current image area in the code stream corresponding to the current image area.
  • the feature information includes the first type of feature information
  • the determination module is specifically used to determine whether the reconstruction value of the current image region needs to be adjusted based on the feature information corresponding to the current image region: if the third image region corresponding to the current image region If a type of feature information meets the first specific condition, it is determined whether the reconstruction value of the current image area needs to be adjusted, and the mark bit corresponding to the adjustment control switch is encoded in the code stream corresponding to the current image area; wherein, The flag bit is used to indicate whether the reconstruction value adjustment of the current image area needs to be performed; if the first type of feature information corresponding to the current image area does not meet the first specific condition, it is determined that the reconstruction value adjustment of the current image area does not need to be performed. .
  • the current image area corresponds to multiple pixel groups
  • the adjustment parameters corresponding to the current image area include multiple adjustment values
  • the multiple adjustment values include adjustment values corresponding to K pixel groups
  • the K The pixel group is all pixel groups or part of the pixel groups in the plurality of pixel groups; when the encoding module encodes the adjustment parameters corresponding to the current image area in the code stream corresponding to the current image area, it is specifically used to: M adjustment values corresponding to the K pixel groups are encoded in the code stream corresponding to the current image area, M is a positive integer, and M is less than or equal to K; wherein the M adjustment values are based on the K The adjustment value corresponding to the pixel group is determined; the encoding module is also used to encode adjustment value grouping indication information in the code stream corresponding to the current image area, and the adjustment value grouping indication information is used to indicate the M adjustment values and the matching relationship between the K pixel groups.
  • the determination module is further configured to determine multiple pixel groups corresponding to the current image area in the following manner: determine multiple pixel groups corresponding to the current image area according to the pre-adjusted reconstruction value of each pixel point; or , determine the classification value of the pixel based on the pre-adjusted reconstruction values of the surrounding pixels, and determine multiple pixel groups corresponding to the current image area according to the classification value of each pixel; or, according to the pixel position of each pixel Determine multiple pixel groups corresponding to the current image area; or determine multiple pixel groups corresponding to the current image area according to the prediction mode of the current image area; or determine the current image area according to the scanning order of the current image area Corresponding multiple pixel groups.
  • the determination module determines multiple pixel groups corresponding to the current image area according to the prediction mode of the current image area, it is specifically used to: determine the number of divisions of the pixel group and the filter area according to the prediction mode of the current image area. and a dividing method; determining a plurality of pixel groups corresponding to the current image area based on the number of divisions, the filtering area and the dividing method.
  • the determination module determines the division number, filtering area and division method of the pixel group according to the prediction mode of the current image area, it is specifically used to: if the prediction mode of the current image area is a horizontal prediction mode, determine the division of the pixel group.
  • the number is the first division number, and the filter area that determines the pixel group is the first
  • the division method is the first size specification
  • the prediction mode of the current image area is not the horizontal prediction mode
  • it is determined that the number of divisions of the pixel group is the second division number
  • it is determined that the filter area of the pixel group is the second filter area , determine the division method is the second size specification.
  • embodiments of the present application may be provided as methods, systems, or computer program products.
  • the application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects.
  • Embodiments of the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) embodying computer-usable program code.

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Abstract

本申请提供一种解码、编码方法、装置及其设备，该解码方法包括：基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整；若确定需要对所述当前图像区域进行重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；基于所述调整参数对所述当前图像区域的重建值进行调整。通过本申请能够提高编码性能和解码性能。

Description

一种解码、编码方法、装置及其设备 技术领域
本申请涉及编解码技术领域，尤其是涉及一种解码、编码方法、装置及其设备。
背景技术
为了达到节约空间的目的，视频图像都是经过编码后才传输的，完整的视频编码可以包括预测、变换、量化、熵编码、滤波等过程。预测过程可以包括帧内预测和帧间预测，帧间预测是指利用视频时间域的相关性，使用邻近已编码图像的像素预测当前像素，以达到有效减少视频时域冗余的目的。帧内预测是指利用视频空间域的相关性，使用当前帧图像的已编码块的像素预测当前像素，以达到减少视频空域冗余的目的。
浅编码是一种图像编码方法，其特点为简单预测。浅编码适用于实时性要求高、缓存小、并行性要求高的场景。但是，在采用浅编码的编码过程中，对于较大的量化步长，往往造成较大的量化误差，特别是在平坦区域，整体的偏差会导致出现色块，从而导致主观有损。
发明内容
有鉴于此，本申请提供了一种解码、编码方法、装置及其设备，提高了编码性能。
本申请提供一种解码方法，应用于解码端，所述方法包括：基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；若确定需要对所述当前图像区域进行所述重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；基于所述调整参数对所述当前图像区域的重建值进行调整。
本申请提供一种编码方法，应用于编码端，所述方法包括：基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；若确定需要对所述当前图像区域进行所述重建值调整，则获取所述当前图像区域对应的调整参数，所述调整参数用于对所述当前图像区域的重建值进行调整；在所述当前图像区域对应的码流中编码所述当前图像区域对应的所述调整参数。
本申请提供一种解码装置，所述解码装置包括：存储器，其经配置以存储视频数据；解码器，其经配置以实现：基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；若确定需要对所述当前图像区域进行所述重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；基于所述调整参数对所述当前图像区域的重建值进行调整。
本申请提供一种编码装置，所述编码装置包括：存储器，其经配置以存储视频数据；编码器，其经配置以实现：基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；若确定需要对所述当前图像区域进行所述重建值调整，则获取所述当前图像区域对应的调整参数，所述调整参数用于对所述当前图像区域的重建值进行调整；在所述当前图像区域对应的码流中编码所述当前图像区域对应的所述调整参数。
本申请提供一种解码端设备，包括：处理器和机器可读存储介质，所述机器可读存储介质存储有能够被所述处理器执行的机器可执行指令；所述处理器用于执行所述机器可执行指令，以实现上述的解码方法。
本申请提供一种编码端设备，包括：处理器和机器可读存储介质，所述机器可读存储介质存储有能够被所述处理器执行的机器可执行指令；所述处理器用于执行所述机器可执行指令，以实现上述的编码方法。
本申请提供一种机器可读存储介质，其上存储有计算机指令，所述计算机指令被至少一个处理器执行时，实现上述的解码方法或编码方法。
由以上技术方案可见，本申请实施例中，提出一种浅编码方法，可以适用于实时性 要求高、缓存小、并行性要求高的场景，在得到当前图像区域的重建值之后，还可以对当前图像区域的重建值进行调整，从而能够使重建像素更接近原始像素，带来编码性能和解码性能的提高。对于较大的量化步长，减少量化误差，特别在平坦区域，减少整体偏差导致的色块问题，能够减轻主观有损，即浅编码方法能够实现主观无损、硬件实现简单。
附图说明
图1A至图1C是帧内预测模式的工作原理示意图；
图2A至图2D是浅编码的视频编码框架的示意图；
图3是本申请一种实施方式中的编码方法的流程图；
图4是本申请一种实施方式中的解码方法的流程图；
图5A至图5D是本申请一种实施方式中的图像块的划分示意图；
图6A至图6J是本申请一种实施方式中的图像块的划分示意图；
图7A是本申请一种实施方式中的解码端设备的硬件结构图；
图7B是本申请一种实施方式中的编码端设备的硬件结构图。
具体实施方式
在本申请实施例使用的术语仅仅是出于描述特定实施例的目的，而非用于限制本申请。本申请实施例和权利要求书中所使用的单数形式的“一种”、“所述”和“该”也旨在包括多数形式，除非上下文清楚地表示其它含义。还应当理解，本文中使用的术语“和/或”是指包含一个或多个相关联的列出项目的任何或所有可能的组合。应当理解，尽管在本申请实施例可能采用术语第一、第二、第三等来描述各种信息，但是，这些信息不应限于这些术语。这些术语仅用来将同一类型的信息彼此区分开。例如，在不脱离本申请实施例范围的情况下，第一信息也可以被称为第二信息，类似地，第二信息也可以被称为第一信息，取决于语境。此外，所使用的词语“如果”可以被解释成为“在……时”，或“当……时”，或“响应于确定”。
本申请实施例中提出一种解码、编码方法、装置及其设备，可以涉及如下概念：
帧内预测(intra prediction)、帧间预测(inter prediction)与IBC(Intra Block Copy，帧内块拷贝)预测：
帧内预测是指，基于视频空间域的相关性，使用当前图像的已编码块的像素预测当前块的像素，以达到减少视频空域冗余(spatial redundancy)的目的。帧内预测规定了多种预测模式，每种预测模式对应一种纹理方向(DC(Direct Current，直流)模式除外)，例如，若图像纹理呈现水平状排布，则水平预测模式可以更好的预测图像信息。
帧间预测是指，基于视频时间域的相关性，由于视频序列包含较强的时域相关性，使用邻近已编码图像的像素预测当前图像的像素，可以达到有效减少视频时域冗余(temporal redundancy)的目的。视频编码标准帧间预测部分都采用了基于块的运动补偿技术，主要原理是为当前图像的每一个像素块在之前已编码图像中寻找一个最佳匹配块，该过程称为运动估计(Motion Estimation，ME)。
帧内块拷贝是指，允许同帧参考，当前块的参考数据来自同一帧。帧内块拷贝技术中，可以使用当前块的块矢量获取当前块的预测值，示例性的，基于屏幕内容中同一帧内存在大量重复出现的纹理这一特性，在采用块矢量获取当前块的预测值时，能够提升屏幕内容序列的压缩效率。
预测像素(Prediction Pixel)是指从已编解码的像素中导出的像素值，通过原始像素与预测像素之差获得残差，进而进行残差变换量化以及系数编码。帧间预测像素指的是当前块从参考帧导出的像素值，由于像素位置离散，需要通过插值运算来获取最终的预测像素。预测像素与原始像素越接近，两者相减得到的残差能量越小，编码压缩性能越高。
帧内预测模式：在帧内编码中，使用帧内预测模式进行运动补偿，即采用帧内预测 模式获取当前块的预测值，帧内预测模式是使用到当前帧的重建值和预测值等进行预测的模式。例如，帧内预测模式可以包括但不限于DC模式、bilinear模式、角度预测模式(如水平角度预测模式、垂直角度预测模式等，对此角度预测模式不做限制，可以是任意角度，如33种角度模式或者65种角度模式等)、IBC模式、ISC(Intra String Copy，帧内串复制)模式、Planar模式、逐点预测模式等。
DC模式和角度预测模式可以参见图1A所示，DC模式适用于大面积平坦区域，将当前块的周围像素的平均值作为当前块的预测值，角度预测模式是将某角度指向的当前块的周围像素的值作为当前块的预测值。在图1A中，a)是DC模式的示意图，将“D”上侧的16个参考像素的均值作为“D”的预测值。b)是角度预测模式1的示意图，表示将该角度指向的参考像素的值作为当前块的预测值。c)是角度预测模式2的示意图，d)是角度预测模式3的示意图，e)是角度预测模式4的示意图，f)是角度预测模式5的示意图，g)是角度预测模式6的示意图。
bilinear模式即双线性插值模式，参见图1B所示，bilinear模式的预测过程如下：首先产生右下角C位置的预测值(右上角参考像素A和左下角参考像素B的加权平均)，然后产生右边界AC位置的预测值(右上角参考像素A和右下角C位置预测值的加权平均)，然后产生下边界BC位置的预测值(左下角参考像素B和右下角C位置预测值的加权平均)，剩余其它内部像素点的预测值(例如X位置的预测值)通过水平线性预测产生的预测值和垂直线性预测产生的预测值的加权平均产生。水平线性预测产生的预测值为左边对应位置参考像素L和右边界AC位置的预测值的加权平均；垂直线性预测产生的预测值为上边对应位置参考像素T和下边界BC位置的预测值的加权平均。
Planar模式(或Plane模式)适用于像素值缓慢变化的区域，使用水平方向和垂直方向的两个线性滤波器，将两个方向上像素的平均值作为当前块像素的预测值。Planar模式是渐变模式，Planar模式是一种利用了不同位置的参考像素以及不同的权重参数得到预测值的帧内预测模式。
ISC模式，是将当前块内像素以一定的扫描顺序(一般为水平光栅扫描顺序或垂直光栅扫描顺序)排列成若干一维像素组，每个像素组进行类似运动估计的方式得到像素组的预测值。
逐点预测模式，参见图1C所示，为16*2的像素块的4种逐点预测模式的示意图。示例性的，16*2的像素块的逐点预测模式可以包括4种，每种逐点预测模式都是以16*2整块作为基本单元进行预测。在图1C中，≡用于表示采用左右两侧像素的重建值求平均得到当前像素的预测值；|||用于表示采用上下两侧像素的重建值求平均得到当前像素的预测值；>用于表示直接采用左侧像素的重建值作为当前像素的预测值；∨用于表示直接采用上侧像素的重建值作为当前像素的预测值。从图1C可以看出，对于逐点预测模式1，Group2的预测需要依赖于Group1的重建；对于逐点预测模式2，Group1的预测需要依赖于Group2的重建。
率失真优化(Rate-Distortion Optimization，RDO)原则：评价编码效率的有两大指标：码率和PSNR(Peak Signal to Noise Ratio，峰值信噪比)，比特流越小，则压缩率越大，PSNR越大，则重建图像质量越好，在模式选择时，判别公式实质上也就是对二者的综合评价。例如，模式对应的代价：J(mode)＝D+λ*R，其中，D表示Distortion(失真)，通常可以使用SSE(Sum of the Squared Errors，误差平方和)指标来进行衡量，SSE是指重建图像块与源图像的差值的均方和，为了实现代价考虑，也可以使用SAD指标，SAD是指重建图像块与源图像的差值绝对值之和；λ是拉格朗日乘子，R就是该模式下图像块编码所需的实际比特数，包括编码模式信息、运动信息、残差等所需的比特总和。在模式选择时，若使用率失真原则去对编码模式做比较决策，通常可以保证编码性能最佳。
码控：控制码率平稳性，一般是通过对量化步长的调整来达到码率平稳的目的。
浅编码：浅编码是一种图像编码方法，其特点为简单预测，浅编码适用于实时性要求高、缓存小、并行性要求高的应用场景。浅编码的压缩效率较低，可以采用帧内预测，且压缩倍率较低(例如，一般是10倍以下)。在浅编码的实现过程中，一般要求主观无损，硬件实现简单。
浅编码的视频编码框架：参见图2A所示，为编码端的视频编码框架的示意图，可以使用该视频编码框架实现本申请实施例的编码端处理流程，即实现浅编码。解码端的视频解码框架的示意图与图2A类似，在此不再重复赘述，可以使用视频解码框架实现本申请实施例的解码端处理流程。
示例性的，参见图2A所示，视频编码框架可以包括块划分、预测、变换、量化、码控、熵编码器、反量化、反变换、重建等模块。在编码端，通过这些模块之间的配合，可以实现编码端处理流程。此外，视频解码框架可以包括块划分、预测、变换、量化、码控、熵解码器、反量化、反变换、重建等模块，在该情况下，属于编码端的码控模块也可以作用于解码端，用以节省量化参数的编码代价以及控制预测模式等；或者，视频解码框架可以包括块划分、预测、变换、量化、熵解码器、反量化、反变换、重建等模块，在该情况下，不存在码控模块。在解码端，通过这些模块之间的配合，可以实现解码端处理流程。
示例性的，在浅压缩场景下，码控技术应用于一个码控单元，码控单元就是码控的作用范围，表示对码控单元对应的范围进行码控操作。例如，码控单元可以是若干个图像块，或码控单元可以是若干个像素行，或码控单元可以是整个Slice，或码控单元可以是Slice内部的若干像素块，或码控单元可以是Slice内部的若干像素行等。当然，上述只是码控单元的几个示例，对此码控单元不做限制。在此基础上，可以对每个码控单元内的像素块进行预测、变换、量化等操作，预测部分的模式选择由码控参与，像素块完成重建后，可以进行重建值调整操作。
下面对编码端和解码端的结构进行简单介绍。参见图2B所示，示出用于实现本申请实施例的编码端的示意性框图。在图2B中，编码端可包括预测处理单元、残差计算单元、变换处理单元、量化单元、编码处理单元、反量化单元(也可以称为逆量化单元)、反变换处理单元(也可以称为逆变换处理单元)、重构单元(或者称为重建单元)以及滤波器单元。在一个例子中，编码端还可以包括缓冲器、经解码图像缓冲器，其中，缓冲器用于缓存重构单元输出的重构图像块，经解码图像缓冲器用于缓存滤波器单元输出的滤波后的图像块。
编码端(也称为编码器)的输入可以为图像(可以称为待编码图像)的图像块，图像块也可以称为当前块或待编码块，编码端中还可以包括分割单元(图中未示出)，该分割单元用于将待编码图像分割成多个图像块。编码端可以对该多个图像块逐块编码从而完成对待编码图像的编码，例如，对每个图像块执行编码过程。预测处理单元用于接收或获取图像块(当前待编码图像的当前待编码图像块，也可以称为当前块，该图像块可以理解为图像块的真实值)和已重构图像数据，基于已重构图像数据中的相关数据对当前块进行预测，得到当前块的预测块。在一个例子中，预测处理单元可以包含帧间预测单元、帧内预测单元和模式选择单元，模式选择单元用于选择帧内预测模式或者帧间预测模式，若选择帧内预测模式，则由帧内预测单元执行预测过程，若选择帧间预测模式，则可以由帧间预测单元执行预测过程。
残差计算单元用于计算图像块的真实值和该图像块的预测块之间的残差，得到残差块，例如，残差计算单元可以通过逐像素将图像块的像素值减去预测块的像素值。
变换处理单元用于对残差块进行例如离散余弦变换(discrete cosine transform，DCT)或离散正弦变换(discrete sine transform，DST)的变换，以在变换域中获取变换系数，变换系数也可以称为变换残差系数，该变换残差系数可以在变换域中表示残差块。
量化单元用于通过应用标量量化或向量量化来量化变换系数，以获取经量化变换系 数，经量化变换系数也可以称为经量化残差系数。量化过程可以减少与部分或全部变换系数有关的位深度。例如，可在量化期间将n位变换系数向下舍入到m位变换系数，其中n大于m。可通过调整量化参数(quantization parameter，QP)修改量化程度。例如，对于标量量化，可以应用不同的标度来实现较细或较粗的量化。较小量化步长对应较细量化，而较大量化步长对应较粗量化。可以通过量化参数指示合适的量化步长。
编码处理单元用于对上述经量化残差系数和一部分编码参数进行编码，以经编码比特流的形式输出经编码图像数据(即当前待编码图像块的编码结果)和经编码的编码参数，然后将经编码比特流传输到解码器，或将其存储起来，后续传输至解码器或用于检索。编码处理单元还可用于对当前图像块的其它语法元素进行编码，例如将预测模式编码至码流等。编码算法包括但不限于可变长度编码(variable length coding，VLC)算法、上下文自适应VLC(context adaptive VLC，CAVLC)算法、算术编码算法、上下文自适应二进制算术编码(context adaptive binary arithmetic coding，CABAC)算法、基于语法的上下文自适应二进制算术编码(syntax-based context-adaptive binary arithmetic coding，SBAC)算法、概率区间分割熵(probability interval partitioning entropy，PIPE)算法。
反量化单元用于对上述经量化残差系数进行反量化，以获取经反量化系数，该反量化是上述量化单元的反向应用，例如，基于或使用与量化单元相同的量化步长，应用量化单元应用的量化方案对应的逆量化方案。经反量化系数也可以称为经反量化残差系数。
反变换处理单元用于对上述经反量化系数进行反变换，应该理解，该反变换是上述变换处理单元的反向应用。例如，反变换可以包括逆离散余弦变换(inverse discrete cosine transform，IDCT)或逆离散正弦变换(inverse discrete sine transform，IDST)，以在像素域(或者称为样本域)中获取逆变换块。逆变换块也可以称为逆变换经反量化块或逆变换残差块。
重构单元用于将逆变换块(即逆变换残差块)添加至预测块，以在样本域中获取经重构块，重构单元可以为求和器，例如，将残差块的样本值(即像素值)与预测块的样本值相加。该重构单元输出的重构块可以后续用于预测其他图像块，例如，在帧内预测模式下使用。
滤波器单元(或简称“滤波器”)用于对经重构块进行滤波以获取经滤波块，从而顺利进行像素转变或提高图像质量。滤波器单元可以为环路滤波器单元，旨在表示一个或多个环路滤波器，例如，滤波器单元可以为去块滤波器、样本自适应偏移(sample-adaptive offset，SAO)滤波器或其它滤波器，例如双边滤波器、自适应环路滤波器(adaptive loop filter，ALF)，或锐化或平滑滤波器，或协同滤波器。在一个例子中，该滤波单元输出的经滤波块可以后续用于预测其他图像块，例如，在帧间预测模式下使用，对此不做限制。
参见图2C所示，示出用于实现本申请实施例的解码端(也可以称为解码器)的示意性框图。解码器用于接收例如由编码器编码的经编码图像数据(即经编码比特流，例如，包括图像块的经编码比特流及相关联的语法元素)，以获取经解码图像。解码器包括解码单元、反量化单元、反变换处理单元、预测处理单元、重构单元、滤波器单元。在一些实施例中，解码器可执行大体上与图2B的编码器描述的编码过程互逆的解码过程。在一个例子中，解码器还可以包括缓冲器、经解码图像缓冲器，其中，缓冲器用于缓存重构单元输出的重构图像块，经解码图像缓冲器用于缓存滤波器单元输出的滤波后的图像块。
解码单元用于对经编码图像数据执行解码，以获取经量化变换系数和/或经解码的编码参数(例如，编码参数可以包括帧间预测参数、帧内预测参数、滤波器参数和/或其它语法元素中的任意一个或多个)。解码单元还用于将上述经解码的编码参数转发至预测处理单元，以供预测处理单元根据编码参数执行预测过程。反量化单元的功能可与编码器的反量化单元的功能相同，用于反量化(即，逆量化)由解码单元解码的经量化变换 系数。
反变换处理单元的功能与编码器的反变换处理单元的功能可以相同，用于对上述经量化变换系数进行逆变换(例如，逆DCT、逆整数变换或概念上类似的逆变换过程)，从而得到逆变换块(也可以称为逆变换残差块)，该逆变换块即为当前图像块在像素域中的残差块。
预测处理单元，用于接收或获取经编码图像数据(例如当前图像块的经编码比特流)和已重构图像数据，预测处理单元还可以从例如解码单元接收或获取预测相关参数和/或关于所选择的预测模式的信息(即经解码的编码参数)，并且基于已重构图像数据中的相关数据和经解码的编码参数对当前图像块进行预测，得到当前图像块的预测块。
在一个例子中，预测处理单元可以包含帧间预测单元、帧内预测单元和模式选择单元，模式选择单元用于选择帧内预测模式或者帧间预测模式，若选择帧内预测模式，则由帧内预测单元执行预测过程，若选择帧间预测模式，则由帧间预测单元执行预测过程。
重构单元(例如求和器)的功能与编码器的重构单元的功能可以相同，重构单元用于将逆变换块(即逆变换残差块)添加到预测块，以在样本域中获取经重构块，例如将逆变换残差块的样本值与预测块的样本值相加。
滤波器单元用于对经重构块进行滤波以获取经滤波块，该经滤波块即为经解码图像块。
应当理解的是，在本申请实施例的编码器和解码器中，针对某个环节的处理结果也可以经过进一步处理后，输出到下一个环节，例如，在插值滤波、运动矢量推导或滤波等环节之后，对相应环节的处理结果进一步进行Clip或移位shift等操作。
在编码器以及解码器的基础上，本申请实施例提供一种可能的编/解码实现方式，如图2D所示，图2D为本申请实施例提供的一种编码和/或解码的流程示意图，该编码和解码实现方式包括过程①至过程⑤，过程①至过程⑤可以由上述的解码器和/或编码器执行。过程①：将一帧图像分成一个或多个互相不重叠的并行编码单元。该一个或多个并行编码单元之间无依赖关系，可以完全并行地独立编码和解码，如图2D所示出的并行编码单元1和并行编码单元2。
过程②：对于每个并行编码单元，可再将其分成一个或多个互相不重叠的独立编码单元，各个独立编码单元间可相互不依赖，但可以共用一些并行编码单元头信息。例如，独立编码单元的宽为w_lcu，高为h_lcu。若并行编码单元划分成一个独立编码单元，则独立编码单元的尺寸与并行编码单元完全相同；否则，则独立编码单元的宽应大于高(除非是边缘区域)。
通常的，独立编码单元可为固定的w_lcu×h_lcu，w_lcu和h_lcu均为2的N次方(N≥0)，如独立编码单元的尺寸为：128×4，64×4，32×4，16×4，8×4，32×2，16×2或8×2等。
作为一种可能的示例，独立编码单元可以为固定的128×4。若并行编码单元的尺寸为256×8，则可以将并行编码单元等分为4个独立编码单元；若并行编码单元的尺寸为288×10，则并行编码单元可以划分为：第一、二行为2个128×4+1个32×4的独立编码单元；第三行为2个128×2+1个32×2的独立编码单元。值得注意的是，独立编码单元既可以包括亮度Y、色度Cb、色度Cr三个分量，或红(red，R)、绿(green，G)、蓝(blue，B)三个分量，或亮度Y、色度Co、色度Cg三个分量也可以仅包含其中的某一个分量。若独立编码单元包含三个分量，则这三个分量的尺寸可以完全一样，也可不一样，具体与图像的输入格式相关。
过程③：对于每个独立编码单元，可再将其分成一个或多个互相不重叠的编码单元，独立编码单元内的各个编码单元可相互依赖，如多个编码单元可以进行相互参考预编/解码。
若编码单元与独立编码单元尺寸相同(即独立编码单元仅分成一个编码单元)，则 其尺寸可为过程②所述的所有尺寸。若独立编码单元分成多个互相不重叠的编码单元，则其可行划分例子包括：水平等分(编码单元的高与独立编码单元相同，但宽不同，可为其1/2，1/4，1/8，1/16等)，垂直等分(编码单元的宽与独立编码单元相同，但高不同，可为其1/2，1/4，1/8，1/16等)，水平和垂直等分(四叉树划分)等，优选为水平等分。
编码单元的宽为w_cu，高为h_cu，其宽应大于高(除非是边缘区域)。通常的，编码单元可为固定的w_cu×h_cu，w_cu和h_cu均为2个N次方(N大于等于0)，如16×4，8×4，16×2，8×2，8×1，4×1等。作为一种可能的示例，编码单元可为固定的16×4。若独立编码单元的尺寸为64×4，则可将独立编码单元等分为4个编码单元；若独立编码单元的尺寸为72×4，则编码单元划分为：4个16×4+1个8×4。值得注意的是，编码单元既可以包括亮度Y、色度Cb、色度Cr三个分量(或红R、绿G、蓝B三分量，或，亮度Y、色度Co、色度Cg)，也可以仅包含其中的某一个分量。若包含三个分量，几个分量的尺寸可以完全一样，也可以不一样，具体与图像输入格式相关。
值得注意的是，过程③可以是编解码方法中一个可选的步骤，编/解码器可以对过程②获得的独立编码单元的残差系数(或残差值)进行编/解码。
过程④：对于编码单元，可以将其再将其分成一个或多个互相不重叠的预测组(Prediction Group，PG)，PG也简称为Group，各PG按照选定预测模式进行编解码，得到PG的预测值，组成整个编码单元的预测值，可以基于编码单元的预测值和原始值，获得编码单元的残差值。
过程⑤：基于编码单元的残差值，对编码单元进行分组，获得一个或多个互相不重叠的残差小块(residual block，RB)，各个RB的残差系数按照选定模式进行编解码，形成残差系数流。具体的，可分为对残差系数进行变换和不进行变换两类。
其中，过程⑤中残差系数编解码方法的选定模式可以包括但不限于下述任一种：半定长编码方式、指数哥伦布(Golomb)编码方法、Golomb-Rice编码方法、截断一元码编码方法、游程编码方法、直接编码原始残差值等。例如，编码器可直接对RB内的系数进行编码。又例如，编码器也可以对残差块进行变换，如DCT、DST、Hadamard变换等，再对变换后的系数进行编码。作为一种可能的示例，当RB较小时，编码器可以直接对RB内的各个系数进行统一量化，再进行二值化编码。若RB较大，可以进一步划分为多个系数组(coefficient group，CG)，再对各个CG进行统一量化，再进行二值化编码。在本申请的一些实施例中，系数组(CG)和量化组(QG)可以相同，当然，系数组和量化组也可以不同。
下面以半定长编码方式对残差系数编码的部分进行示例性说明。首先，将一个RB块内残差绝对值的最大值定义为修整最大值(modified maximum，mm)。其次，确定该RB块内残差系数的编码比特数(同一RB块内残差系数的编码比特数一致)。例如，若当前RB块的关键限值(critical limit，CL)为2，当前残差系数为1，则编码残差系数1需要2个比特，表示为01。若当前RB块的CL为7，则表示编码8-bit的残差系数和1-bit的符号位。CL的确定是去找满足当前子块所有残差都在[-2^(T-1),2^(T-1)]范围之内的最小T值。若同时存在-2^(T-1)和2^(T-1)两个边界值，则T增加1，即需要T+1个比特编码当前RB块的所有残差；若仅存在-2^(T-1)和2^(T-1)两个边界值中的一个，则编码一个Trailing位来确定该边界值是-2^(T-1)还是2^(T-1)；若所有残差均不存在-2^(T-1)和2^(T-1)中的任何一个，则无需编码该Trailing位。对于某些特殊的情况，编码器可以直接编码图像的原始值，而不是残差值。
示例性的，浅编码是一种图像编码方法，其特点为简单预测，浅编码适用于实时性要求高、缓存小、并行性要求高的场景。但是，浅编码的编码过程中，对于较大的量化步长，往往造成较大的量化误差，特别在平坦区域，整体的偏差会导致出现色块，从而导致主观有损。
本申请中的主观有损是指人眼能察觉到重建图像和源图像的不同，可以是在合适的观测距离下以特定的频率(例如，8Hz)交替播放重建图像和源图像，以进行确定。
针对上述问题，本申请实施例中提出一种浅编码的滤波方法，可以适用于实时性要求高、缓存小、并行性要求高的场景，在得到当前图像区域的重建值之后，可以对当前图像区域的重建值进行调整，从而能够使重建像素更接近原始像素，带来编码性能和解码性能的提高。对于较大的量化步长，减少量化误差，特别在平坦区域，减少整体偏差导致的色块问题，能够减轻主观有损，提高主观性能，浅编码的编码过程中，能够实现主观无损、硬件实现简单。
以下结合几个具体实施例，对本申请实施例中的解码方法和编码方法进行详细说明。
实施例1：本申请实施例中提出一种编码方法，参见图3所示，为该编码方法的流程示意图，该方法可以应用于编码端(也可以称为视频编码器)，该方法可以包括：
步骤301、基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整。
在一种可能的实施方式中，可以采用显式方法确定是否需要对当前图像区域进行重建值调整，为了区分方便，将显式方法涉及的特征信息称为第一类特征信息。
例如，可以获取当前图像区域对应的第一类特征信息，若当前图像区域对应的第一类特征信息满足特定条件(如第一特定条件)，则确定是否需要对当前图像区域进行重建值调整，并基于确定结果在当前图像区域对应的码流中编码调整控制开关对应的标记位，该标记位用于指示是否需要对当前图像区域进行重建值调整。若当前图像区域对应的第一类特征信息不满足特定条件，则确定不需要对当前图像区域进行重建值调整，也不在当前图像区域对应的码流中编码调整控制开关对应的标记位。
其中，在第一类特征信息满足特定条件时，若确定需要对当前图像区域进行重建值调整，则在当前图像区域对应的码流中编码调整控制开关对应的标记位，且该标记位为第一取值，通过第一取值表示需要对当前图像区域进行重建值调整。若确定不需要对当前图像区域进行重建值调整，则在当前图像区域对应的码流中编码调整控制开关对应的标记位，且该标记位为第二取值，通过第二取值表示不需要对当前图像区域进行重建值调整。其中，第一取值和第二取值可以根据经验配置，对此不做限制，比如说，第一取值为1，第二取值为0。
针对“确定是否需要对当前图像区域进行重建值调整”的过程，若启动当前图像区域的重建值调整的代价值，小于关闭当前图像区域的重建值调整的代价值，则确定需要对当前图像区域进行重建值调整；否则，确定不需要对当前图像区域进行重建值调整。
示例性的，当前图像区域可以包括一个图像块，或者，当前图像区域可以包括连续的多个图像块。当前图像区域对应的码流是指：与当前图像区域有关的码流，即该码流中存在用于对当前图像区域进行处理的信息，对此当前图像区域对应的码流不做限制。
示例性的，当前图像区域对应的第一类特征信息可以包括但不限于以下至少一种：预测模式；码流缓冲区内的数据量；量化步长。基于此，若第一类特征信息包括预测模式，则在当前图像区域对应的预测模式是指定预测模式时，确定该预测模式满足特定条件；否则，确定该预测模式不满足特定条件。若第一类特征信息包括码流缓冲区内的数据量，则在码流缓冲区内的数据量位于预设数据量区间时，确定码流缓冲区内的数据量满足特定条件；否则，确定码流缓冲区内的数据量不满足特定条件。若第一类特征信息包括量化步长，则在当前图像区域对应的量化步长位于预设步长区间时，确定该量化步长满足特定条件；否则，确定该量化步长不满足特定条件。
若第一类特征信息包括预测模式和码流缓冲区内的数据量，那么，在预测模式满足特定条件，且码流缓冲区内的数据量也满足特定条件时，才确定当前图像区域对应的第一类特征信息满足特定条件，否则，确定当前图像区域对应的第一类特征信息不满足特定条件。或者，若第一类特征信息包括量化步长和码流缓冲区内的数据量，那么，在量 化步长满足特定条件，且码流缓冲区内的数据量也满足特定条件时，才确定当前图像区域对应的第一类特征信息满足特定条件，否则，确定当前图像区域对应的第一类特征信息不满足特定条件。或者，若第一类特征信息包括预测模式和量化步长，那么，在预测模式满足特定条件，且量化步长也满足特定条件时，才确定当前图像区域对应的第一类特征信息满足特定条件，否则，确定当前图像区域对应的第一类特征信息不满足特定条件。或者，若第一类特征信息包括预测模式、码流缓冲区内的数据量和量化步长，那么，在预测模式满足特定条件，码流缓冲区内的数据量满足特定条件，且量化步长也满足特定条件时，才确定当前图像区域对应的第一类特征信息满足特定条件，否则，确定当前图像区域对应的第一类特征信息不满足特定条件。
当然，上述只是第一类特征信息的几个示例，本实施例中对此第一类特征信息不做限制。
在上述实施例中，指定预测模式可以是普通帧内预测模式中的一种或多种。其中：普通帧内预测模式包括DC模式；或者，普通帧内预测模式包括DC模式、水平预测模式和垂直预测模式；或者，普通帧内预测模式包括DC模式和角度预测模式；或者，普通帧内预测模式包括DC模式、角度预测模式和Planar模式；或者，普通帧内预测模式包括DC模式、角度预测模式和bilinear模式；或者，普通帧内预测模式包括DC模式、角度预测模式、Planar模式和bilinear模式。
在另一种可能的实施方式中，可以采用隐式方法确定是否需要对当前图像区域进行重建值调整，为了区分方便，将隐式方法涉及的特征信息称为第二类特征信息。
例如，获取当前图像区域对应的第二类特征信息，若当前图像区域对应的第二类特征信息满足特定条件(如第二特定条件)，则确定需要对当前图像区域进行重建值调整，若当前图像区域对应的第二类特征信息不满足特定条件，则确定不需要对当前图像区域进行重建值调整。
关于隐式方法的具体实现方式，可以参见后续实施例，在此不再赘述。
步骤302、若确定需要对当前图像区域进行重建值调整，则获取当前图像区域对应的调整参数，其中，该调整参数用于对当前图像区域的重建值进行调整。
步骤303、在当前图像区域对应的码流中编码当前图像区域对应的调整参数。
示例性的，若当前图像区域对应的调整参数包括多个调整值，则可以在当前图像区域对应的码流中编码全部调整值或者部分调整值(即多个调整值中的部分调整值)。
其中，在当前图像区域对应的码流中编码全部调整值或者部分调整值可以包括但不限于：按照多个调整值的编码顺序对多个调整值进行排序，并基于排序结果依次遍历多个调整值；针对当前遍历的调整值，若在当前图像区域对应的码流中编码该调整值之后，当前码率小于预设码率值，则在当前图像区域对应的码流中编码该调整值，且继续遍历该调整值的下一个调整值，也即，将下一个调整值作为当前遍历的调整值；否则，禁止在当前图像区域对应的码流中编码该调整值，且停止遍历该调整值的下一个调整值。
示例性的，当前图像区域可以对应多个像素组，当前图像区域对应的调整参数可以包括多个调整值。且多个调整值可以包括K个像素组对应的调整值，K个像素组可以是多个像素组(即当前图像区域的所有像素组)中的全部像素组或部分像素组。
在此基础上，可以在当前图像区域对应的码流中编码K个像素组对应的M个调整值，M可以为正整数，M可以小于或者等于K，且M个调整值可以是基于K个像素组对应的调整值确定的。以及，还可以在当前图像区域对应的码流中编码调整值分组指示信息，该调整值分组指示信息用于指示M个调整值与K个像素组之间的匹配关系。
比如说，若K个像素组对应同一个调整值，则调整值分组指示信息可以为第四取值，通过第四取值表示K个像素组对应同一个调整值；若K个像素组对应K个调整值，则调整值分组指示信息可以为第五取值，通过第五取值可以表示K个像素组对应K个调整值。
示例性的，若K个像素组是多个像素组中的部分像素组，则编码端还可以在当前图像区域对应的码流中编码K个像素组对应的像素组指示信息，表示当前图像区域对应的码流中携带的是该像素组指示信息对应的像素组的调整值。若K个像素组是多个像素组中的全部像素组，则编码端可以不在当前图像区域对应的码流中编码像素组对应的像素组指示信息，表示当前图像区域对应的码流中携带的是所有像素组的调整值，此时，不需要在码流中编码像素组对应的像素组指示信息。其中，若K个像素组是多个像素组中的部分像素组，则该像素组指示信息用于区分所有类别的像素组中的目标类别的像素组，也就是说，从所有像素组中区分出K个像素组。
示例性的，在当前图像区域对应多个通道时，针对每个像素组来说，该像素组对应的调整值可以包括该像素组对应的多个通道或单个通道的调整值，多个通道或单个通道可以包括如下通道中的至少一种：Y通道、U通道、V通道、Co通道、Cg通道、R通道、G通道、B通道、alpha通道、IR通道、D通道、W通道。比如说，多个通道包括Y通道、U通道、V通道，或者，多个通道包括R通道、G通道、B通道，或者，多个通道包括、R通道、G通道、B通道、alpha通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道，或者，多个通道包括R通道、G通道、B通道、W通道，或者，多个通道包括R通道、G通道、B通道、IR通道、W通道，或者，多个通道包括R通道、G通道、B通道、D通道，或者，多个通道可以包括R通道、G通道、B通道、D通道、W通道。其中，除了RGB彩色感光通道，也可能有IR通道(红外或近红外感光通道)，D通道(暗光通道，主要通过红外光或近红外光)，W通道(全色感光通道)，针对不同的传感器有不同的通道，比如说，传感器类型可以是RGB传感器，RGBIR传感器，RGBW传感器，RGBIRW传感器，RGBD传感器，RGBDW传感器等。
示例性的，当前图像区域对应多个像素组，可以包括但不限于如下方式：按照各像素点的调整前重建值确定当前图像区域对应的多个像素组；或者，基于像素点的周围像素点的调整前重建值确定该像素点的分类值，按照各像素点的分类值确定当前图像区域对应的多个像素组；或者，按照各像素点的像素位置确定当前图像区域对应的多个像素组；或者，根据当前图像区域的预测模式确定当前图像区域对应的多个像素组；或者，根据当前图像区域的扫描顺序确定当前图像区域对应的多个像素组。当然，上述方式只是示例，对此不做限制。
其中，在根据当前图像区域的预测模式确定当前图像区域对应的多个像素组时，可以根据当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式；基于该划分数量、该滤波区域和该划分方式确定当前图像区域对应的多个像素组。
示例性的，若当前图像区域的预测模式是水平预测模式，则确定像素组的划分数量是第一划分数量，确定像素组的滤波区域是第一滤波区域，确定划分方式是第一尺寸规格；若当前图像区域的预测模式不是水平预测模式，则确定像素组的划分数量是第二划分数量，确定像素组的滤波区域是第二滤波区域，确定划分方式是第二尺寸规格。
比如说，若当前图像区域是16*2的图像块(即一个图像块)，在根据预测模式划分多个像素组时，若当前图像区域的预测模式是水平预测模式，则将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是8*1；或者，将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是16*1。若当前图像区域的预测模式不是水平预测模式，则将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2。
示例性的，若当前图像区域是16*2的图像块，那么，也可以直接将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2，而不考虑当前图像区域的预测模式。
在上述实施例中，调整值的取值范围可以基于量化步长确定。
示例性的，上述执行顺序只是为了方便描述给出的示例，在实际应用中，还可以改 变步骤之间的执行顺序，对此执行顺序不做限制。而且，在其它实施例中，并不一定按照本说明书示出和描述的顺序来执行相应方法的步骤，其方法所包括的步骤可以比本说明书所描述的更多或更少。此外，本说明书中所描述的单个步骤，在其它实施例中可能被分解为多个步骤进行描述；本说明书中所描述的多个步骤，在其它实施例也可能被合并为单个步骤进行描述。
由以上技术方案可见，本申请实施例中，提出一种浅编码方法，可以适用于实时性要求高、缓存小、并行性要求高的场景，在得到当前图像区域的重建值之后，还可以对当前图像区域的重建值进行调整，从而能够使重建像素更接近原始像素，带来编码性能和解码性能的提高。对于较大的量化步长，减少量化误差，特别在平坦区域，减少整体偏差导致的色块问题，能够减轻主观有损，即浅编码方法能够实现主观无损、硬件实现简单。
实施例2：本申请实施例中提出一种解码方法，参见图4所示，为该解码方法的流程示意图，该方法可以应用于解码端(也可以称为视频解码器)，该方法可以包括：
步骤401、基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整。
在一种可能的实施方式中，可以采用显式方法确定是否需要对当前图像区域进行重建值调整，为了区分方便，将显式方法涉及的特征信息称为第一类特征信息。
例如，可以获取当前图像区域对应的第一类特征信息，若当前图像区域对应的第一类特征信息满足特定条件(如第一特定条件)，则可以从当前图像区域对应的码流中获取调整控制开关对应的标记位，并基于该标记位确定是否需要对当前图像区域进行重建值调整。其中，若该标记位为第一取值，则可以确定需要对当前图像区域进行重建值调整；若该标记位为第二取值，则可以确定不需要对当前图像区域进行重建值调整。或者，若当前图像区域对应的第一类特征信息不满足特定条件，则可以直接确定不需要对当前图像区域进行重建值调整，也不需要从当前图像区域对应的码流中获取调整控制开关对应的标记位。
示例性的，当前图像区域可以包括一个图像块，或者，当前图像区域可以包括连续的多个图像块。当前图像区域对应的码流是指：与当前图像区域有关的码流，即该码流中存在用于对当前图像区域进行处理的信息，对此当前图像区域对应的码流不做限制。
示例性的，当前图像区域对应的第一类特征信息可以包括但不限于以下至少一种：预测模式；码流缓冲区内的数据量；量化步长。基于此，若第一类特征信息包括预测模式，则在当前图像区域对应的预测模式是指定预测模式时，确定该预测模式满足特定条件；否则，确定该预测模式不满足特定条件。若第一类特征信息包括码流缓冲区内的数据量，则在码流缓冲区内的数据量位于预设数据量区间时，确定码流缓冲区内的数据量满足特定条件；否则，确定码流缓冲区内的数据量不满足特定条件。若第一类特征信息包括量化步长，则在当前图像区域对应的量化步长位于预设步长区间时，确定该量化步长满足特定条件；否则，确定该量化步长不满足特定条件。
在上述实施例中，指定预测模式可以是普通帧内预测模式中的一种或多种；其中：普通帧内预测模式包括DC模式；或者，普通帧内预测模式包括DC模式、水平预测模式和垂直预测模式；或者，普通帧内预测模式包括DC模式和角度预测模式；或者，普通帧内预测模式包括DC模式、角度预测模式和Planar模式；或者，普通帧内预测模式包括DC模式、角度预测模式和bilinear模式；或者，普通帧内预测模式包括DC模式、角度预测模式、Planar模式和bilinear模式。
在另一种可能的实施方式中，可以采用隐式方法确定是否需要对当前图像区域进行重建值调整，为了区分方便，将隐式方法涉及的特征信息称为第二类特征信息。
例如，获取当前图像区域对应的第二类特征信息，若当前图像区域对应的第二类特征信息满足特定条件(如第二特定条件)，则确定需要对当前图像区域进行重建值调整， 若当前图像区域对应的第二类特征信息不满足特定条件，则确定不需要对当前图像区域进行重建值调整。
关于隐式方法的具体实现方式，可以参见后续实施例，在此不再赘述。
步骤402、若确定需要对当前图像区域进行重建值调整，则从当前图像区域对应的码流中获取当前图像区域对应的调整参数，该调整参数用于对重建值进行调整。
步骤403、基于该调整参数对当前图像区域的重建值进行调整。
在一种可能的实施方式中，当前图像区域对应的调整参数可以包括多个调整值，当前图像区域可以对应多个像素组，多个调整值可以包括K个像素组对应的调整值，K个像素组可以是多个像素组中的全部像素组或部分像素组。在此基础上，基于该调整参数对当前图像区域的重建值进行调整，可以包括但不限于：基于多个调整值对K个像素组内的像素点的重建值进行调整，示例性的，K可以为大于或等于1的正整数。其中，基于多个调整值对K个像素组内的像素点的重建值进行调整，可以包括但不限于如下方式：针对K个像素组中的每个像素组，若多个调整值包括该像素组对应的调整值，则基于该像素组对应的调整值对该像素组内每个像素点的重建值进行调整，得到该像素组内每个像素点的调整后的重建值。
示例性的，若K个像素组是多个像素组中的部分像素组，则解码端还可以从当前图像区域对应的码流中获取K个像素组对应的像素组指示信息；基于该像素组指示信息从所有像素组中选取K个像素组，并将多个调整值与K个像素组进行关联，这样，就可以基于多个调整值对K个像素组内的像素点的重建值进行调整，即只对K个像素组内的像素点的重建值进行调整。
其中，若K个像素组是多个像素组中的部分像素组，则该像素组指示信息用于区分所有类别的像素组中的目标类别的像素组，也就是说，从所有像素组中区分出K个像素组。
其中，针对每个像素组，该像素组对应的调整值可以包括该像素组对应的多个通道的调整值，多个通道可以包括如下通道中的至少一种：Y通道、U通道、V通道、R通道、G通道、B通道、alpha通道、IR通道、D通道、W通道。比如说，多个通道包括Y通道、U通道、V通道，或者，多个通道包括R通道、G通道、B通道，或者，多个通道包括、R通道、G通道、B通道、alpha通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道，或者，多个通道可以包括R通道、G通道、B通道、W通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道、W通道，或者，多个通道可以包括R通道、G通道、B通道、D通道，或者，多个通道可以包括R通道、G通道、B通道、D通道、W通道。
示例性的，还可以从当前图像区域对应的码流中获取调整值分组指示信息，该调整值分组指示信息用于指示调整值与K个像素组之间的映射关系；基于调整值分组指示信息从当前图像区域对应的码流中解析M个调整值，M为正整数，且M小于或者等于K；可以基于M个调整值确定K个像素组对应的调整值。比如说，若调整值分组指示信息为第四取值，则M为1，在该情况下，解码端可以确定K个像素组与一个调整值对应；若调整值分组指示信息为第五取值，则M为K，在该情况下，解码端可以确定K个像素组与K个调整值对应。
示例性的，在当前图像区域对应多个通道时，从当前图像区域对应的码流中解析M个调整值可以包括：针对每个通道，从当前图像区域对应的码流中解析该通道对应的一个或多个调整值。
示例性的，当前图像区域对应多个像素组，可以包括但不限于：按照各像素点的调整前重建值确定当前图像区域对应的多个像素组；或者，基于像素点的周围像素点的调整前重建值确定该像素点的分类值，按照各像素点的分类值确定当前图像区域对应的多个像素组；或者，按照各像素点的像素位置确定当前图像区域对应的多个像素组；或者， 根据当前图像区域的预测模式确定当前图像区域对应的多个像素组；或者，根据当前图像区域的扫描顺序确定当前图像区域对应的多个像素组。当然，上述方式只是示例，对此不做限制。
其中，在根据当前图像区域的预测模式确定当前图像区域对应的多个像素组时，可以根据当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式；然后，基于该划分数量、该滤波区域和该划分方式确定当前图像区域对应的多个像素组。
示例性的，根据当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式可以包括：若当前图像区域的预测模式是水平预测模式，则确定像素组的划分数量是第一划分数量，确定像素组的滤波区域是第一滤波区域，确定划分方式是第一尺寸规格；若当前图像区域的预测模式不是水平预测模式，则确定像素组的划分数量是第二划分数量，确定像素组的滤波区域是第二滤波区域，确定划分方式是第二尺寸规格。
比如说，若当前图像区域是16*2的图像块(即一个图像块)，在根据预测模式划分多个像素组时，若当前图像区域的预测模式是水平预测模式，则将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是8*1；或者，将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是16*1。若当前图像区域的预测模式不是水平预测模式，则将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2。
示例性的，若当前图像区域是16*2的图像块，那么，也可以直接将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2，而不考虑当前图像区域的预测模式。
在上述实施例中，调整值的取值范围可以基于量化步长确定。
由以上技术方案可见，本申请实施例中，提出一种浅编码方法，可以适用于实时性要求高、缓存小、并行性要求高的场景，在得到当前图像区域的重建值之后，还可以对当前图像区域的重建值进行调整，从而能够使重建像素更接近原始像素，带来编码性能和解码性能的提高。对于较大的量化步长，减少量化误差，特别在平坦区域，减少整体偏差导致的色块问题，能够减轻主观有损，即浅编码方法能够实现主观无损、硬件实现简单。
实施例3：针对实施例1和实施例2，可以确定是否需要对当前图像区域进行重建值调整。比如说，针对编码端来说，编码端在编码N个编码块(N≥1)的码流后，可以将其中的P个编码块(P≤N)记为当前图像区域，可以确定是否需要对当前图像区域进行重建值调整。针对解码端来说，解码端在解析N个解码块(N≥1)的码流后，可以将其中的P个解码块(与编码端的P个编码块对应)记为当前图像区域，可以确定是否需要对当前图像区域进行重建值调整。
示例性的，还可以确定是否需要对当前图像区域进行预测值调整，也就是说，可以基于当前图像区域对应的调整参数对当前图像区域的预测值进行调整，预测值调整过程与重建值调整过程类似，本实施例中不再赘述。示例性的，还可以确定是否需要对当前图像区域进行残差值调整，也就是说，可以基于当前图像区域对应的调整参数对当前图像区域的残差值进行调整，残差值调整过程与重建值调整过程类似，本实施例中不再赘述。
示例性的，为了确定是否需要对当前图像区域进行重建值调整，可以采用如下方式：
显式语法方式：编码端在码流中编码调整控制开关对应的标记位，解码端从码流中解析调整控制开关对应的标记位，基于该标记位确定是否需要对当前图像区域进行重建值调整。
以下结合具体应用场景，对显式语法方式的实现过程进行说明，该过程可以包括：
步骤S11、编码端确定当前图像区域对应的第一类特征信息是否满足第一特定条件。
如果否，则可以执行步骤S12，如果是，则可以执行步骤S13。
示例性的，当前图像区域对应的第一类特征信息可以包括但不限于以下至少一种：预测模式；码流缓冲区内的数据量；量化步长。当然，上述只是第一类特征信息的几个示例，对此不做限制，后续以预测模式、码流缓冲区内的数据量、量化步长为例进行说明。
情况1：第一类特征信息可包括预测模式。在当前图像区域对应的预测模式是指定预测模式时，可以确定第一类特征信息满足第一特定条件；否则，在当前图像区域对应的预测模式不是指定预测模式时，可以确定第一类特征信息不满足第一特定条件。
情况2：第一类特征信息可包括码流缓冲区内的数据量。在码流缓冲区内的数据量位于预设数据量区间时，可以确定第一类特征信息满足第一特定条件；否则，在码流缓冲区内的数据量不位于预设数据量区间时，可以确定第一类特征信息不满足第一特定条件。
示例性的，可以预先配置预设数据量区间[a1，a2]，a1用于表示数据量最小值，a2用于表示数据量最大值，a1和a2均可以根据经验配置，对此不做限制。
若码流缓冲区内的数据量大于或者等于a1，且码流缓冲区内的数据量小于或者等于a2，则码流缓冲区内的数据量位于预设数据量区间。若码流缓冲区内的数据量小于a1，或者，若码流缓冲区内的数据量大于a2，则码流缓冲区内的数据量不位于预设数据量区间。
示例性的，若码流缓冲区内的数据量位于预设数据量区间，即码流缓冲区内的数据量小于或者等于a2，那么，在对当前图像区域进行滤波处理(图1所示的编码过程就是滤波过程)时，在加入滤波参数后不会触发上溢，即不会导致码流缓冲区超出buffer限制。
情况3：第一类特征信息可包括量化步长。在当前图像区域对应的量化步长位于预设步长区间时，可以确定第一类特征信息满足第一特定条件；否则，在当前图像区域对应的量化步长不位于预设步长区间时，可以确定第一类特征信息不满足第一特定条件。
示例性的，可以预先配置预设步长区间[b1，b2]，b1用于表示步长最小值，b2用于表示步长最大值，b1和b2均可以根据经验配置，对此不做限制。若当前图像区域对应的量化步长大于或者等于b1，且当前图像区域对应的量化步长小于或者等于b2，则当前图像区域对应的量化步长位于预设步长区间。若当前图像区域对应的量化步长小于b1，或者，若当前图像区域对应的量化步长大于b2，则当前图像区域对应的量化步长不位于预设步长区间。
示例性的，对于情况3，在量化步长满足一定条件(即位于预设步长区间)时，才确定第一类特征信息满足第一特定条件，而预设步长区间能够使得对于不影响主观的量化步长不进行调整。
示例性的，在配置b1的取值时，b1可以根据经验配置，对此不做限制。例如，b1可以根据当前图像区域的输入位宽确定，当前图像区域的输入位宽越大，b1的取值越大。例如，在当前图像区域的输入位宽是8bit时，b1的取值可以是16，在当前图像区域的输入位宽是10bit时，b1的取值可以是24，在当前图像区域的输入位宽是12bit时，b1的取值可以是32。当然，上述只是输入位宽与步长最小值b1之间关系的示例，对此步长最小值b1不做限制。
综上所述，针对不同的当前图像区域的输入位宽，在量化参数(QP)满足如下关系时，量化步长大于或者等于b1，即满足预设步长区间的最小值要求：针对8bit，QP≥16；针对10bit，QP≥24；针对12bit，QP≥32。
示例性的，在配置b2的取值时，b2可以根据经验配置，对此不做限制。例如，b2可以是无穷大的取值；b2也可以是某个固定值，例如48、60、76等。
情况4：第一类特征信息可包括预测模式和码流缓冲区内的数据量。在当前图像区域对应的预测模式是指定预测模式，且码流缓冲区内的数据量位于预设数据量区间时， 可以确定第一类特征信息满足第一特定条件；否则，在当前图像区域对应的预测模式不是指定预测模式，和/或，码流缓冲区内的数据量不位于预设数据量区间时，确定第一类特征信息不满足第一特定条件。
情况5：第一类特征信息可包括预测模式和量化步长。在当前图像区域对应的预测模式是指定预测模式，且当前图像区域对应的量化步长位于预设步长区间时，可以确定第一类特征信息满足第一特定条件；否则，在当前图像区域对应的预测模式不是指定预测模式，和/或，当前图像区域对应的量化步长不位于预设步长区间时，确定第一类特征信息不满足第一特定条件。
情况6：第一类特征信息可包括量化步长和码流缓冲区内的数据量。在当前图像区域对应的量化步长位于预设步长区间，且码流缓冲区内的数据量位于预设数据量区间时，确定第一类特征信息满足第一特定条件；否则，在当前图像区域对应的量化步长不位于预设步长区间，和/或，码流缓冲区内的数据量不位于预设数据量区间时，确定第一类特征信息不满足第一特定条件。
情况7：第一类特征信息可包括预测模式、码流缓冲区内的数据量和量化步长。在当前图像区域对应的预测模式是指定预测模式，且码流缓冲区内的数据量位于预设数据量区间，且当前图像区域对应的量化步长位于预设步长区间时，确定第一类特征信息满足第一特定条件；否则，在当前图像区域对应的预测模式不是指定预测模式，和/或，码流缓冲区内的数据量不位于预设数据量区间，和/或，当前图像区域对应的量化步长不位于预设步长区间时，则确定第一类特征信息不满足第一特定条件，即只要有一个不满足，就确定第一类特征信息不满足第一特定条件。
当然，上述几种情况只是“确定当前图像区域对应的第一类特征信息是否满足第一特定条件”的几个示例，本实施例中对此“第一类特征信息是否满足第一特定条件”的确定过程不做限制。
针对上述情况1、情况4、情况5和情况7，在一种可能的实施方式中，指定预测模式可以是普通帧内预测模式中的一种或多种。在另一种可能的实施方式中，指定预测模式还可以是逐点预测模式。当然，普通帧内预测模式和逐点预测模式只是示例，对此不做限制。
针对情况5和情况7，对于预设步长区间，还可以基于指定预测模式来设置预设步长区间，如基于指定预测模式来设置预设步长区间的最小值。比如说，普通帧内预测模式可以对应预设步长区间的第一最小值，即b1的取值可以是第一最小值；逐点预测模式可以对应预设步长区间的第二最小值，即b1的取值可以是第二最小值。其中，第一最小值可以大于第二最小值，第一最小值也可以小于第二最小值，对此不做限制，预设步长区间的最小值与指定预测模式有关即可。
普通帧内预测模式可以包括DC模式。或者，普通帧内预测模式可以包括DC模式、水平预测模式和垂直预测模式。或者，普通帧内预测模式可以包括DC模式和角度预测模式(如水平预测模式、垂直预测模式和其它角度预测模式)。或者，普通帧内预测模式可以包括DC模式、角度预测模式和Planar模式。或者，普通帧内预测模式可以包括DC模式、角度预测模式和bilinear模式。或者，普通帧内预测模式可以包括DC模式、角度预测模式、Planar模式和bilinear模式。当然，上述只是普通帧内预测模式的示例，对此不做限制。在上述每种普通帧内预测模式的基础上，还可以将其它类型的帧内预测模式作为普通帧内预测模式。
步骤S12、若第一类特征信息不满足第一特定条件，则编码端确定不需要对当前图像区域进行重建值调整，也不在当前图像区域对应的码流中编码调整控制开关对应的标记位。
步骤S13、若第一类特征信息满足第一特定条件，则编码端确定是否需要对当前图像区域进行重建值调整，并在当前图像区域对应的码流中编码调整控制开关对应的标记 位。
示例性的，若第一类特征信息满足第一特定条件，则编码端可以确定是否需要对当前图像区域进行重建值调整，对此确定方式不做限制。比如说，编码端计算启动当前图像区域的重建值调整的代价值，记为第一代价值，并计算关闭当前图像区域的重建值调整的代价值，记为第二代价值。在此基础上，若第一代价值小于第二代价值，则编码端确定需要对当前图像区域进行重建值调整；否则，编码端确定不需要对当前图像区域进行重建值调整。
示例性的，编码端在确定是否需要对当前图像区域进行重建值调整之后，可以在当前图像区域对应的码流中编码调整控制开关对应的标记位。比如说，若确定需要对当前图像区域进行重建值调整，则该标记位可以为第一取值，通过第一取值表示需要对当前图像区域进行重建值调整。若确定不需要对当前图像区域进行重建值调整，则该标记位可以为第二取值，通过第二取值表示不需要对当前图像区域进行重建值调整。第一取值和第二取值均可以根据经验配置，如第一取值为0，第二取值为1，或者，第一取值为1，第二取值为0。
步骤S14、解码端确定当前图像区域对应的第一类特征信息是否满足第一特定条件。
如果否，则可以执行步骤S15，如果是，则可以执行步骤S16。
示例性的，步骤S14的实现过程与步骤S11类似，在此不再重复赘述。
步骤S15、若第一类特征信息不满足第一特定条件，则解码端确定不需要对当前图像区域进行重建值调整，也不需要从当前图像区域对应的码流中解码调整控制开关对应的标记位。
步骤S16、若第一类特征信息满足第一特定条件，则解码端从当前图像区域对应的码流中获取调整控制开关对应的标记位，并基于该标记位确定是否需要对当前图像区域进行重建值调整。其中，若该标记位为第一取值，则解码端可以确定需要对当前图像区域进行重建值调整；若该标记位为第二取值，则解码端可以确定不需要对当前图像区域进行重建值调整。
综上所述，编码端和解码端均可以确定是否需要对当前图像区域进行重建值调整，且这个重建值调整的结论可以应用到当前图像区域。若需要对当前图像区域进行重建值调整，对于编码端，需要对N个编码块的重建值进行调整，对于解码端，需要对N个解码块的重建值进行调整。若不需要对当前图像区域进行重建值调整，对于编码端，不需要对N个编码块的重建值进行调整，对于解码端，不需要对N个解码块的重建值进行调整。
实施例4：针对实施例1和实施例2，可以确定是否需要对当前图像区域进行重建值调整。比如说，针对编码端来说，编码端在编码N个编码块(N≥1)的码流后，可以将N个编码块记为当前图像区域，可以确定是否需要对当前图像区域进行重建值调整。针对解码端来说，解码端在解析N个解码块(N≥1)的码流后，可以将N个解码块(与编码端的N个编码块对应)记为当前图像区域，可以确定是否需要对当前图像区域进行重建值调整。
示例性的，为了确定是否需要对当前图像区域进行重建值调整，可以采用如下方式：
隐式导出方式：编码端可以根据当前图像区域对应的第二类特征信息隐式导出是否需要对当前图像区域进行重建值调整，解码端也可以根据当前图像区域对应的第二类特征信息隐式导出是否需要对当前图像区域进行重建值调整。
以下结合具体应用场景，对隐式导出方式的实现过程进行说明，该过程可以包括：
步骤S21、编码端确定当前图像区域对应的第二类特征信息是否满足第二特定条件。
如果否，则可以执行步骤S22，如果是，则可以执行步骤S23。
示例性的，当前图像区域对应的第二类特征信息可以包括但不限于码控的上下溢指示信息、量化参数、已重建像素特征、块位置中的至少一种，码控的上下溢指示信息可 以包括但不限于当前码率，量化参数可以包括但不限于量化步长。其中，当前码率用于表示当前图像区域所在码控单元之前的所有码控单元的平均码率；块位置是当前图像区域内的图像块的块位置，如当前图像区域内的任一图像块的块位置，块位置用于表示该图像块在当前帧中的位置。当然，当前码率、量化参数、已重建像素特征和块位置只是第二类特征信息的几个示例，对此第二类特征信息不做限制，第二类特征信息是否满足第二特定条件可以包括但不限于：
情况I、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码率，当前码率也就是码控信息，即码控的上下溢指示信息，若当前码率小于第一码率值，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
示例性的，第一码率值可以是根据经验配置的码率值，对此第一码率值不做限制，在当前码率小于第一码率值时，可以表示码控信息指示资源池(例如，用来存放比特流的码流缓冲区)充足。
在一种可能的实施方式中，可以预先配置一个目标上限码率，在当前码率接近于目标上限码率时，表示码控信息指示资源池正常，在当前码率大于目标上限码率与预设阈值之和时，表示码控信息指示资源池不足，在当前码率小于目标上限码率与预设阈值之差时，表示码控信息指示资源池充足，在此基础上，可以将目标上限码率与预设阈值之差作为第一码率值。
情况II、当前图像区域对应的第二类特征信息可包括当前图像区域对应的块位置，若当前图像区域对应的该块位置位于指定位置，则确定该第二类特征信息满足第二特定条件，否则，若当前图像区域对应的该块位置不位于指定位置，确定该第二类特征信息不满足第二特定条件。
比如说，指定位置可以是当前码控单元(即当前图像区域所在的码控单元)的最后L个图像块(L可以为大于或等于1的正整数)，或者指定位置可以是当前码控单元的最下一行图像块等。在此基础上，若该块位置属于当前码控单元的最后L个图像块或最下一行图像块，则确定该块位置位于指定位置，否则，确定该块位置不位于指定位置。
又例如，指定位置可以是当前帧内部Slice边界位置，若该块位置属于当前帧内部Slice边界位置，则确定该块位置位于指定位置，否则，确定该块位置不位于指定位置。
又例如，指定位置可以是当前码控单元的最后L个图像块和当前帧内部Slice边界位置，若该块位置属于当前码控单元的最后L个图像块，或，该块位置属于当前帧内部Slice边界位置，则确定该块位置位于指定位置。若该块位置不属于当前码控单元的最后L个图像块，且该块位置不属于当前帧内部Slice边界位置，则确定该块位置不位于指定位置。
当然，上述只是指定位置的几个示例，本实施例中对此指定位置不做限制。
情况III、当前图像区域对应的第二类特征信息可包括当前图像区域对应的量化步长，若该量化步长大于步长阈值，则确定该第二类特征信息满足第二特定条件，否则，若该量化步长不大于步长阈值，确定该第二类特征信息不满足第二特定条件。
情况IV、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码率和当前图像区域对应的块位置，在此基础上，若当前码率小于第一码率值、且该块位置位于指定位置，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
情况V、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码率和当前图像区域对应的块位置，若当前码率小于第一码率值，或者，该块位置位于指定位置，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
情况VI、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码 率和当前图像区域对应的量化步长，若当前码率小于第一码率值、且该量化步长大于步长阈值，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
情况VII、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码率和当前图像区域对应的量化步长，若当前码率小于第一码率值，或者，该量化步长大于步长阈值，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
情况VIII、当前图像区域对应的第二类特征信息可包括当前图像区域对应的块位置和当前图像区域对应的量化步长，在此基础上，若该块位置位于指定位置、且该量化步长大于步长阈值，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
情况IX、当前图像区域对应的第二类特征信息可包括当前图像区域对应的块位置和当前图像区域对应的量化步长，若该块位置位于指定位置，或者，该量化步长大于步长阈值，则确定该第二类特征信息满足第二特定条件，否则，确定该第二类特征信息不满足第二特定条件。
情况X、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码率、当前图像区域对应的块位置和当前图像区域对应的量化步长，在此基础上，若该当前码率小于第一码率值、且该块位置位于指定位置、且该量化步长大于步长阈值，则可以确定该第二类特征信息满足第二特定条件，否则，可以确定该第二类特征信息不满足第二特定条件。
情况XI、当前图像区域对应的第二类特征信息可包括当前图像区域对应的当前码率、当前图像区域对应的块位置和当前图像区域对应的量化步长，在此基础上，若该当前码率小于第一码率值，或者，该块位置位于指定位置，或者，该量化步长大于步长阈值，则可以确定该第二类特征信息满足第二特定条件，否则，可以确定该第二类特征信息不满足第二特定条件。
情况XII、当前图像区域对应的第二类特征信息可包括当前图像区域对应的已重建像素特征，在此基础上，若该已重建像素特征表示当前图像区域的复杂程度为简单，则可以确定该第二类特征信息满足第二特定条件，否则，可以确定该第二类特征信息不满足第二特定条件。
示例性的，已重建像素特征可以是，从重建像素中计算得到的当前图像区域的复杂程度(例如梯度)，如可以采用索贝尔(Sobel)算子对当前像素区域的复杂度进行评估，得到当前图像区域的复杂程度；也可以对当前图像区域的重建像素值进行变换，根据变换域，如频域，的特征得到当前图像区域的复杂程度；还可以计算当前图像区域的水平垂直梯度，基于水平垂直梯度得到当前图像区域的复杂程度。当然，上述只是几个示例，只要能够得到已重建像素特征即可，且已重建像素特征可以表示当前图像区域的复杂程度。
已重建像素特征的原理和块位置的原理类似，对于复杂区域往往能承受更多的损失而不被察觉，但对于简单区域，比如平坦区域，此时很小的损失就会被人眼察觉到。
基于上述原理，在已重建像素特征表示当前图像区域的复杂程度为简单时，则表示可以对当前图像区域的重建值进行调整，以减少图像损失，因此，可以确定第二类特征信息满足第二特定条件。示例性的，已重建像素特征可以是复杂程度值，当该复杂程度值大于预设阈值时，则已重建像素特征可表示当前图像区域的复杂程度为复杂，否则，当前图像区域的复杂程度为简单。本申请实施例中对表示当前图像区域的复杂程度不进行限制，例如，还可以是当该复杂程度值小于预设阈值时，则已重建像素特征可表示当前图像区域的复杂程度为简单，否则，当前图像区域的复杂程度为复杂。
情况XIII、当前图像区域对应的第二类特征信息可包括当前图像区域对应的已重建 像素特征，在此基础上，当前图像区域对应的第二类特征信息还包括当前码率、块位置和量化步长中的至少一个，为了方便描述，以同时包括当前码率、块位置和量化步长为例，其它情况下的实现方式类似，基于此，若该当前码率小于第一码率值，且该块位置位于指定位置，且该量化步长大于步长阈值，且该已重建像素特征表示当前图像区域的复杂程度为简单，则可以确定该第二类特征信息满足第二特定条件，否则，可以确定该第二类特征信息不满足第二特定条件。
情况XIV、当前图像区域对应的第二类特征信息包括当前图像区域对应的已重建像素特征，在此基础上，当前图像区域对应的第二类特征信息还包括当前码率、块位置和量化步长中的至少一个，为了方便描述，以同时包括当前码率、块位置和量化步长为例，其它情况下的实现方式类似，基于此，若该当前码率小于第一码率值，或，该块位置位于指定位置，或，该量化步长大于步长阈值，或，该已重建像素特征表示当前图像区域的复杂程度为简单，则可以确定该第二类特征信息满足第二特定条件，否则，可以确定该第二类特征信息不满足第二特定条件。
当然，上述几种情况只是“确定当前图像区域对应的第二类特征信息是否满足第二特定条件”的几个示例，本实施例中对此“第二类特征信息是否满足第二特定条件”的确定过程不做限制。
步骤S22、编码端确定不需要对当前图像区域进行重建值调整。
步骤S23、编码端确定需要对当前图像区域进行重建值调整。
步骤S24、解码端确定当前图像区域对应的第二类特征信息是否满足第二特定条件。
如果否，则可以执行步骤S25，如果是，则可以执行步骤S26。
示例性的，步骤S24的实现过程与步骤S21类似，在此不再重复赘述。
步骤S25、解码端确定不需要对当前图像区域进行重建值调整。
步骤S26、解码端确定需要对当前图像区域进行重建值调整。
实施例5：针对实施例1和实施例2，可以确定是否需要对当前图像区域进行重建值调整。比如说，针对编码端来说，编码端在编码N个编码块(N≥1)的码流后，可以将N个编码块记为当前图像区域，可以确定是否需要对当前图像区域进行重建值调整。针对解码端来说，解码端在解析N个解码块(N≥1)的码流后，可以将N个解码块(与编码端的N个编码块对应)记为当前图像区域，可以确定是否需要对当前图像区域进行重建值调整。
示例性的，为了确定是否需要对当前图像区域进行重建值调整，可以采用如下方式：
组合实现方式，即显式语法+隐式导出的实现方式。例如，编码端在获取到当前图像区域对应的调整控制开关的标记位(参见实施例3)之后，若该调整控制开关的标记位与目标图像区域(如当前图像区域的前一个图像区域，或指定的某个图像区域，或默认的图像区域等)对应的调整控制开关的标记位相同，则编码端可不在当前图像区域对应的码流中编码调整控制开关的标记位。解码端获知当前图像区域对应的码流中未携带调整控制开关的标记位时，就可以将目标图像区域对应的调整控制开关的标记位作为当前图像区域对应的调整控制开关的标记位，继而确定是否对当前图像区域进行重建值调整。或者，编码端在获取到当前图像区域对应的调整控制开关的标记位之后，若该调整控制开关的标记位与目标图像区域对应的调整控制开关的标记位不同，则编码端可以在当前图像区域对应的码流中编码调整控制开关的标记位。解码端可以从码流中解析当前图像区域对应的调整控制开关的标记位，并基于该标记位确定是否对当前图像区域进行重建值调整。
实施例6：针对实施例1-实施例5，在确定是否对当前图像区域进行重建值调整之后，若确定对当前图像区域进行重建值调整，则可以获取当前图像区域对应的调整参数。该调整参数可用于对当前图像区域的重建值进行调整，即用于调整当前图像区域内的N个图像块的重建值(或预测值，或残差值等)。比如说，针对编码端来说，当前图像区 域可以包括N个编码块，该调整参数可用于对N个编码块的重建值进行调整，针对解码端来说，当前图像区域可以包括N个解码块，该调整参数可用于对N个解码块的重建值进行调整。
针对编码端来说，可以基于当前图像区域的原始值和当前图像区域的重建值确定当前图像区域对应的调整参数。该调整参数用于对当前图像区域的重建值进行调整，以使调整后的重建值接近当前图像区域的原始值，本实施例对此调整参数的获取过程不做限制。
示例性的，当前图像区域对应的调整参数可以包括多个调整值，当前图像区域可以对应多个像素组，即当前图像区域的所有像素点可以被划分至多个像素组，在此基础上，多个调整值可以包括K个像素组对应的调整值，K个像素组可以是多个像素组中的全部像素组或者部分像素组。比如说，可以将当前图像区域的所有像素点划分至32个像素组，可以从32个像素组中选取K个像素组，如4个像素组、8个像素组、16个像素组、32个像素组等，对K的取值不做限制。基于此，编码端获取这K个像素组对应的调整参数，即调整参数可以包括K个像素组对应的调整值，每个像素组对应的调整值用于对该像素组内每个像素点的重建值进行调整。比如说，假设K个像素组为像素组1和像素组2，则编码端可以获取像素组1对应的调整值和像素组2对应的调整值，像素组1对应的调整值用于对像素组1内每个像素点的重建值进行调整，像素组2对应的调整值用于对像素组2内每个像素点的重建值进行调整。
针对每个像素组来说，该像素组对应的调整值可以包括该像素组对应的多个通道或单个通道的调整值。比如说，多个通道可以包括Y通道、U通道、V通道，或者，多个通道可以包括R通道、G通道、B通道，或者，多个通道可以包括、R通道、G通道、B通道、alpha通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道，或者，多个通道可以包括R通道、G通道、B通道、W通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道、W通道，或者，多个通道可以包括R通道、G通道、B通道、D通道，或者，多个通道可以包括R通道、G通道、B通道、D通道、W通道。单个通道可以是上述通道中的任一。当然，上述只是几个示例。
在实际应用中，上述通道中的两个或两个以上还可以使用同一个调整值，比如说，U通道和V通道可以使用同一个调整值，或者，R通道和G通道可以使用同一个调整值，对此不做限制。
比如说，像素组1对应的调整值包括Y通道调整值1、U通道调整值1和V通道调整值1，Y通道调整值1用于对像素组1内每个像素点的Y通道重建值进行调整、U通道调整值1用于对像素组1内每个像素点的U通道重建值进行调整、V通道调整值1用于对像素组1内每个像素点的V通道重建值进行调整。像素组2对应的调整值包括Y通道调整值2、U通道调整值2和V通道调整值2，Y通道调整值2用于对像素组2内每个像素点的Y通道重建值进行调整、U通道调整值2用于对像素组2内每个像素点的U通道重建值进行调整、V通道调整值2用于对像素组2内每个像素点的V通道重建值进行调整。在一个像素组对应多个通道的情况下，该像素组对应的各通道的调整值可以均不同，也可以均相同，还可以部分相同部分不同。
示例性的，编码端在得到当前图像区域对应的调整参数之后，还可以在当前图像区域对应的码流中编码当前图像区域对应的调整参数。比如说，该调整参数可以包括K个像素组对应的调整值，因此，可以在当前图像区域对应的码流中编码K个像素组对应的调整值。
针对解码端来说，可以从当前图像区域对应的码流中获取当前图像区域对应的调整参数，该调整参数用于对当前图像区域的重建值进行调整，以使调整后的重建值接近当前图像区域的原始值。在得到调整参数之后，就可以基于该调整参数对当前图像区域的重建值进行调整。
示例性的，当前图像区域对应的调整参数可以包括多个调整值，可以将当前图像区域的所有像素点划分至多个像素组，在此基础上，多个调整值可以包括K个像素组对应的调整值，K个像素组可以是多个像素组中的全部像素组或者部分像素组。解码端可以从码流中获取K个像素组对应的调整参数，即调整参数可以包括K个像素组对应的调整值。解码端可以基于像素组对应的调整值，对该像素组内每个像素点的重建值进行调整。比如说，假设K个像素组为像素组1和像素组2，则解码端可以获取像素组1对应的调整值和像素组2对应的调整值，解码端基于像素组1对应的调整值对像素组1内每个像素点的重建值进行调整，以及，解码端基于像素组2对应的调整值对像素组2内每个像素点的重建值进行调整。
针对每个像素组来说，该像素组对应的调整值可以包括该像素组对应的多个通道或单个通道的调整值，比如说，多个通道可以包括Y通道、U通道、V通道，或者，多个通道可以包括R通道、G通道、B通道，或者，多个通道可以包括、R通道、G通道、B通道、alpha通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道，或者，多个通道可以包括R通道、G通道、B通道、W通道，或者，多个通道可以包括R通道、G通道、B通道、IR通道、W通道，或者，多个通道可以包括R通道、G通道、B通道、D通道，或者，多个通道可以包括R通道、G通道、B通道、D通道、W通道。单个通道可以是上述通道中的任一。当然，上述只是几个示例，对此不做限制。
示例性的，以像素组对应的调整值包括该像素组对应的多个通道的调整值为例，针对K个像素组中的每个像素组，若从码流中获取的多个调整值包括该像素组对应的调整值，则解码端基于该像素组对应的调整值对该像素组内每个像素点的重建值进行调整，得到该像素组内每个像素点的调整后的重建值。比如说，若从码流中获取的多个调整值包括像素组1对应的Y通道调整值1、U通道调整值1和V通道调整值1，则可以基于Y通道调整值1对像素组1内每个像素点的Y通道重建值进行调整，基于U通道调整值1对像素组1内每个像素点的U通道重建值进行调整，基于V通道调整值1对像素组1内每个像素点的V通道重建值进行调整。又例如，若从码流中获取的多个调整值只包括像素组1对应的Y通道调整值1，而未包括像素组1对应的U通道调整值1和V通道调整值1，则解码端可以基于Y通道调整值1对像素组1内每个像素点的Y通道重建值进行调整。
在一种可能的实施方式中，若K个像素组是多个像素组(如32个像素组)中的全部像素组，则编码端可以不在当前图像区域对应的码流中编码K个像素组对应的像素组指示信息，解码端也不需要从当前图像区域对应的码流中解析K个像素组对应的像素组指示信息，在此基础上，解码端可以获知码流中携带的调整参数是所有像素组(如32个像素组)的调整值。
若K个像素组是所有像素组中的部分像素组，则编码端可以在当前图像区域对应的码流中编码K个像素组对应的像素组指示信息，表示码流中携带的是该像素组指示信息对应的K个像素组的调整值。解码端可以从当前图像区域对应的码流中解析K个像素组对应的像素组指示信息，获知码流中携带的调整参数是该像素组指示信息对应的K个像素组的调整值。
比如说，该像素组指示信息包括K个像素组的索引值，该索引值表示像素组是所有像素组中的第几个像素组，以K个像素组包括像素组1、像素组2、像素组3和像素组4为例，则像素组指示信息可以包括像素组1的索引值(该索引值用于表示像素组1是所有像素组中的第几个像素组)、像素组2的索引值、像素组3的索引值和像素组4的索引值。显然，若K个像素组是多个像素组中的部分像素组，则该像素组指示信息用于区分所有类别的像素组中的目标类别的像素组，即从所有像素组中区分出K个像素组，像素组指示信息能够实现分类功能。
又例如，假设K个像素组是连续像素组，该像素组指示信息可以包括K个像素组 中部分像素组的索引值，剩余像素组的索引值可以隐式推导出。以K个像素组包括像素组1、像素组2、像素组3和像素组4为例，则像素组指示信息可以只包括像素组1的索引值，由于K个像素组是连续像素组，因此，可以隐式推导出像素组2的索引值、像素组3的索引值和像素组4的索引值。
综上所述，可以采用显示方式指示K个像素组的索引值，或者，也可以采用显示方式指示K个像素组中部分像素组的索引值，并通过隐式方式推导出剩余像素组的索引值，本实施例中对此不做限制，只要解码端能够获知K个像素组的索引值即可。
示例性的，若K个像素组是所有像素组中的部分像素组，且K个像素组是处于默认位置的K个像素组，如K个像素组固定为前面4个像素组，或K个像素组固定为第1、3、5、7个像素组，或K个像素组固定为后面4个像素组，那么，编码端可以不在当前图像区域对应的码流中编码K个像素组对应的像素组指示信息，解码端也不需要从当前图像区域对应的码流中解析K个像素组对应的像素组指示信息，在此基础上，解码端获知码流中携带的调整参数是默认位置的K个像素组的调整值，例如，调整参数是前面4个像素组的调整值，或调整参数是第1、3、5、7个像素组的调整值，或调整参数是后面4个像素组的调整值。
实施例7：针对编码端来说，当前图像区域对应的调整参数包括K个像素组对应的调整值。调整参数可以包括多个调整值，在当前图像区域对应的码流中编码K个像素组对应的调整值时，可以在当前图像区域对应的码流中编码全部调整值或者部分调整值。比如说，以像素组对应的调整值包括该像素组对应的单个通道的调整值为例，假设K个像素组是12个像素组，其中，4个像素组的调整值为Y通道调整值、4个像素组的调整值为U通道调整值、4个像素组的调整值为V通道调整值，则当前图像区域对应的调整参数可以包括12个调整值。可以在当前图像区域对应的码流中编码12个调整值，也可以在当前图像区域对应的码流中编码12个调整值中的部分调整值。
针对解码端来说，在从当前图像区域对应的码流中获取调整参数时，若编码端编码了K个像素组对应的全部调整值，则解码端可以从当前图像区域对应的码流中获取K个像素组对应的全部调整值。若编码端编码了K个像素组对应的部分调整值，则解码端可以从当前图像区域对应的码流中获取K个像素组对应的部分调整值。比如说，若解码端得到Y通道调整值，但是未得到U通道调整值和V通道调整值，则解码端只基于该Y通道调整值对对应的像素组内每个像素点的Y通道重建值进行调整，而不对该像素组内每个像素点的U通道重建值和V通道重建值进行调整。此外，若解码端未得到K个像素组中的某个像素组的调整值，则解码端不再对该像素组内每个像素点的重建值进行调整。
在一种可能的实施方式中，基于K个像素组对应的多个调整值，编码端在当前图像区域对应的码流中编码全部调整值或者部分调整值，可以包括但不限于如下步骤：
步骤S31、按照多个调整值的编码顺序对多个调整值进行排序。
以12个像素组(如像素组1至像素组12)，其中，4个像素组的调整值为Y通道调整值、4个像素组的调整值为U通道调整值、4个像素组的调整值为V通道调整值为例，则当前图像区域对应12个调整值，可以确定12个调整值的编码顺序。
首先，可以确定各像素组的编码顺序，例如，在按照各像素点的重建值划分多个像素组时，可以按照各像素组的值域确定各像素组的编码顺序，如按照值域从小到大的顺序排序，或按照值域从大到小的顺序排序。以按照值域从小到大的顺序排序为例，假设像素组1对应的值域最小，像素组2对应的值域第二小，以此类推，像素组11对应的值域第二大，像素组12对应的值域最大，也即像素组1至像素组12的值域依次增大，那么，各像素组的编码顺序可以是从像素组1至像素组12依次编码。
又例如，在按照各像素点的梯度值划分多个像素组时，可以按照各像素组的梯度值值域(即各像素组对应的梯度值结果，如上述绝对值在10以下等值域)确定各像素组 的编码顺序。如按照梯度值值域从小到大的顺序排序，或按照梯度值值域从大到小的顺序排序。以按照梯度值值域从小到大的顺序排序为例，假设像素组1对应的梯度值值域最小，像素组2对应的梯度值值域第二小，以此类推，像素组11对应的梯度值值域第二大，像素组12对应的梯度值值域最大，也即像素组1至像素组12的对应的梯度值依次增大，那么，各像素组的编码顺序可以是从像素组1至像素组12依次编码。
又例如，在按照各像素点的像素位置划分多个像素组时，可以按照各像素组对应的块顺序确定各像素组的编码顺序。以按照块顺序从前到后的顺序排序为例，假设像素组1对应的子区域是当前图像区域的第一个块，像素组2对应的子区域是当前图像区域的第二个块，以此类推，像素组11对应的子区域是当前图像区域的第十一个块，像素组12对应的子区域是当前图像区域的第12个块，那么，各像素组的编码顺序是从像素组1至像素组12依次编码。
当然，上述方式只是确定各像素组的编码顺序的几个示例，对此不做限制。
还可以确定各通道的编码顺序，如确定Y通道、U通道和V通道之间的编码顺序，如编码顺序依次是：Y通道、U通道、V通道；或者，Y通道、V通道、U通道；或者，U通道、Y通道、V通道；或者，U通道、V通道、Y通道。当然，上述方式只是确定各通道的编码顺序的几个示例，对此不做限制，可以任意规划各通道的编码顺序。
在像素组对应的调整值包括该像素组对应的多个通道的调整值的情况下，可以基于各像素组的编码顺序和各通道的编码顺序，确定多个调整值的编码顺序。比如说，可以以像素组的编码顺序为主，以各通道的编码顺序为辅，确定多个调整值的编码顺序，以K个像素组是4个像素组，其中每个像素组对应3个通道的调整值，各像素组的编码顺序是像素组1、像素组2、像素组3和像素组4，各通道的编码顺序是Y通道、U通道、V通道为例，则12个调整值的编码顺序可以是：像素组1的Y通道调整值、U通道调整值和V通道调整值，像素组2的Y通道调整值、U通道调整值和V通道调整值，像素组3的Y通道调整值、U通道调整值和V通道调整值，像素组4的Y通道调整值、U通道调整值和V通道调整值。又例如，可以以各通道的编码顺序为主，以像素组的编码顺序为辅，确定多个调整值的编码顺序，则上述12个调整值的编码顺序可以是：像素组1的Y通道调整值、像素组2的Y通道调整值、像素组3的Y通道调整值、像素组4的Y通道调整值、像素组1的U通道调整值、像素组2的U通道调整值、像素组3的U通道调整值、像素组4的U通道调整值、像素组1的V通道调整值、像素组2的V通道调整值、像素组3的V通道调整值、像素组4的V通道调整值。当然，上述只是多个调整值的编码顺序的两个示例，本实施例对此多个调整值的编码顺序不做限制，可以任意配置多个调整值的编码顺序。
步骤S32、基于排序结果依次遍历多个调整值。
比如说，以K个像素组是4个像素组为例，针对像素组对应单通道的调整值，第一次遍历时，遍历像素组1的调整值，第二次遍历时遍历像素组2的调整值，第三次遍历时遍历像素组3的调整值，第四次遍历时遍历像素组4的调整值；针对像素组对应多个通道的调整值，第一次遍历时，遍历像素组1的Y通道调整值，第二次遍历时，遍历像素组1的U通道调整值，第三次遍历时，遍历像素组1的V通道调整值，第四次遍历时，遍历像素组2的Y通道调整值，第五次遍历时，遍历像素组2的U通道调整值，以此类推。上述针对像素组对应单通道的调整值时，还可以按照各通道的排序进行遍历，以各通道的排序为Y通道、U通道、V通道为例，第一次遍历时遍历Y通道的调整值，第二次遍历时遍历U通道的调整值，第三次遍历时遍历V通道的调整值。各像素组和各像素通道还可以具有其他排序，以上只是对遍历顺序的示例，本申请对此不做限制。
步骤S33、针对当前遍历的调整值，若在当前图像区域对应的码流中编码该调整值之后，当前码率小于第二码率值，则在当前图像区域对应的码流中编码该调整值，且继续遍历该调整值的下一个调整值，将下一个调整值作为当前遍历的调整值。
示例性的，第二码率值可以是根据经验配置的，对此不做限制，在当前码率小于第二码率值时，表示码控信息指示资源池充足。在一种可能的实施方式中，可以预先配置一个目标上限码率，在当前码率接近于目标上限码率时，表示码控信息指示资源池正常；在当前码率大于目标上限码率与预设阈值之和时，表示码控信息指示资源池不足；在当前码率小于目标上限码率与预设阈值之差时，表示码控信息指示资源池充足。在此基础上，可以将目标上限码率与预设阈值之差作为第二码率值。第二码率值与上述第一码率值可以相同，也可以不同。
步骤S34、针对当前遍历的调整值，若在当前图像区域对应的码流中编码该调整值之后，当前码率不小于第二码率值，则可以禁止在当前图像区域对应的码流中编码该调整值，且停止遍历该调整值的下一个调整值，即结束多个调整值的遍历过程。
综上所述，本实施例中，编码端在当前图像区域对应的码流中编码K个像素组对应的多个调整值时，可以依次遍历多个调整值。针对当前遍历的调整值，若在码流中编码该调整值之后，当前码率小于第二码率值，则在码流中编码该调整值，且继续遍历该调整值的下一个调整值；若当前码率不小于第二码率值，则不在码流中编码该调整值，且停止遍历该调整值的下一个调整值。以此类推，一直到已遍历K个像素组对应的全部调整值，或者当前码率不小于第二码率值时，停止遍历调整值。至此，可以在当前图像区域对应的码流中编码K个像素组对应的全部调整值或者部分调整值，对此过程不做赘述。
实施例8：在传递调整参数的过程中，码控的状态也会同步更新，在编码调整参数过后，若码控仍然为下溢状态(小于0，如当前码率小于第二码率值时，表示码控仍然为下溢状态)，则继续编码调整参数。情况一，以通道形式逐步传递调整参数，如Y通道，U通道，V通道，R通道，G通道，B通道，alpha通道(也可以部分通道共享，例如UV通道共享)等，若码控状态为下溢，则按照顺序编码(解码端为解析)调整参数，传递过后若码控仍然下溢，则继续编码(解码端为解析)下一个调整参数。以此类推，直至码控不下溢或者调整参数全部被传递。情况二，以像素组(至少一个像素)的形式逐步传递调整参数，即按照一定的扫描顺序与分组，逐个传递调整参数，例如，按照先Y通道再U通道再V通道，每个通道进行垂直方向的四分组(如4个像素组)，然后逐个组传递调整参数，逐步更新码控状态。示例性的，调整参数表达了，对N个编码块(即当前图像区域)中的某一类或多类重建值进行调整，某一类或多类重建值可以通过语法传递，也可通过导出的方式确定，例如：编解码端统一约定；根据已编码信息导出(如模式信息，重建值信息等)。
实施例9：针对实施例1至实施例8，对于编码端和解码端来说，当前图像区域可以对应多个像素组，如将当前图像区域的所有像素点划分至多个像素组，即对所有像素点进行分类。本实施例中，可以采用如下方式将当前图像区域的所有像素点划分至多个像素组：
方式1：按照各像素点的调整前重建值将当前图像区域的所有像素点划分至多个像素组，即可以根据各像素点的调整前重建值(后续用于分组的重建值，均是指调整前重建值)进行分类，得到多个像素组。比如说，可以将重建值的值域平均分为A个像素组，根据重建值所在范围确定像素组，如将位宽为8bit的重建值(值域0至255)分为16个像素组，16个像素组的范围分别为0至15，16至31，32至47，48至63，...，240至255。若像素点的重建值处于范围0至15，则将该像素点划分至第1个像素组，若像素点的重建值处于范围16至31，则将该像素点划分至第2个像素组，若像素点的重建值处于范围32至47，则将该像素点划分至第3个像素组，若像素点的重建值处于范围48至63，则将该像素点划分至第4个像素组，以此类推，若像素点的重建值处于范围240至255，则将该像素点划分至第16个像素组。
示例性的，在按照各像素点的重建值将当前图像区域的所有像素点划分至多个像素 组时，还可以逐通道进行划分。比如说，以Y通道、U通道、V通道为例，若像素点的Y通道重建值处于范围0至15，则将该像素点的Y通道重建值划分至第1个像素组，基于此，可以基于第1个像素组对应的Y通道调整值对该像素点的Y通道重建值进行调整。若像素点的U通道重建值处于范围16至31，则将该像素点的U通道重建值划分至第2个像素组，基于此，可以基于第2个像素组对应的U通道调整值对该像素点的U通道重建值进行调整。若像素点的V通道重建值处于范围16至31，则将该像素点的V通道重建值划分至第2个像素组，基于此，可以基于第2个像素组对应的V通道调整值对该像素点的V通道重建值进行调整。
方式2：基于像素点的周围像素点的调整前重建值(后续用于分组的重建值，均是指调整前重建值)确定该像素点的分类值，按照各像素点的分类值将当前图像区域的所有像素点划分至多个像素组，如可以根据各像素点的梯度值进行分类，得到多个像素组。
比如说，可以根据像素点的周围像素点的重建值对该像素点进行分类，如利用梯度信息，可以将像素点的上侧相邻像素点的重建值与像素点的左侧相邻像素点的重建值相减，得到该像素点的梯度值。可以将梯度值结果的绝对值位于某一范围的像素点定义为同一类，如绝对值在10以下的为第一类，绝对值在10至30的为第二类，绝对值大于30的为第三类。在此基础上，针对某个像素点来说，若该像素点的梯度值的绝对值处于10以下，则将该像素点划分至第1个像素组，若像素点的梯度值的绝对值处于10至30，则将该像素点划分至第2个像素组，若像素点的梯度值的绝对值处于30以上，则将该像素点划分至第3个像素组。
方式3：按照各像素点的像素位置将当前图像区域的所有像素点划分至多个像素组，即可以根据各像素点的像素位置进行分类，得到多个像素组。比如说，可以根据像素位置进行分类，如将16*2的当前图像区域等分为四个4*2的子区域，每个4*2的子区域划分为一类。在此基础上，针对某个像素点来说，若该像素点处于第一个4*2的子区域，则可以将该像素点划分至第1个像素组，若该像素点处于第二个4*2的子区域，则可以将该像素点划分至第2个像素组，若该像素点处于第三个4*2的子区域，则可以将该像素点划分至第3个像素组，若该像素点处于第四个4*2的子区域，则可以将该像素点划分至第4个像素组。
方式4：可以将每个像素点划分成一个像素组，即每个像素点就是一个像素组，不同像素点对应不同像素组，可以理解为，像素组就包括一个像素点。
当然，上述方式只是划分方式的几个示例，对此划分方式不做限制。
实施例10：针对实施例1至实施例8，对于编码端和解码端来说，当前图像区域可以对应多个像素组，例如，将当前图像区域的所有像素点划分至多个像素组，即对所有像素点进行分类。本实施例中，可以采用如下方式确定当前图像区域对应的多个像素组：根据当前图像区域的预测模式确定当前图像区域对应的多个像素组，也就是说，像素组的划分可以与当前图像区域的预测模式有关。比如说，可以根据当前图像区域的预测模式确定像素组的划分属性，并基于该划分属性确定当前图像区域对应的多个像素组。
示例性的，该划分属性可以包括划分数量、滤波区域和划分方式中的至少一种。若该划分属性包括划分数量、滤波区域和划分方式，则根据当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式，并基于划分数量、滤波区域和划分方式确定当前图像区域对应的多个像素组。若该划分属性包括划分数量和划分方式，则根据当前图像区域的预测模式确定像素组的划分数量和划分方式，并基于划分数量和划分方式确定当前图像区域对应的多个像素组。关于其它划分属性的组合，其实现方式类似，本实施例中不再赘述。
其中，划分数量用于表示将当前图像区域划分为多少个像素组，滤波区域用于表示将当前图像区域的哪部分区域划分为多个像素组，划分方式用于表示每个像素组的尺寸规格。
其中，若划分属性包括滤波区域，则滤波区域可以表示将当前图像区域的全部区域划分为多个像素组，也可以表示将当前图像区域的部分区域划分为多个像素组。若划分属性不包括滤波区域，则表示将当前图像区域的全部区域划分为多个像素组。
示例性的，可以将当前图像区域的预测模式区分为水平预测模式和非水平预测模式，若当前图像区域的预测模式是水平预测模式，则可以确定像素组的划分数量是第一划分数量，确定像素组的滤波区域是第一滤波区域，确定划分方式是第一尺寸规格；若当前图像区域的预测模式不是水平预测模式，则可以确定像素组的划分数量是第二划分数量，确定像素组的滤波区域是第二滤波区域，确定划分方式是第二尺寸规格。或者，若当前图像区域的预测模式是水平预测模式，则可以确定像素组的划分数量是第一划分数量，确定划分方式是第一尺寸规格；若当前图像区域的预测模式不是水平预测模式，则可以确定像素组的划分数量是第二划分数量，确定划分方式是第二尺寸规格。又例如，可以将当前图像区域的预测模式区分为垂直预测模式和非垂直预测模式，若当前图像区域的预测模式是垂直预测模式，则可以确定像素组的划分数量是第三划分数量，确定像素组的滤波区域是第三滤波区域，确定划分方式是第三尺寸规格；若当前图像区域的预测模式不是垂直预测模式，则可以确定像素组的划分数量是第四划分数量，确定像素组的滤波区域是第四滤波区域，确定划分方式是第四尺寸规格。或者，若当前图像区域的预测模式是垂直预测模式，则可以确定像素组的划分数量是第三划分数量，确定划分方式是第三尺寸规格；若当前图像区域的预测模式不是垂直预测模式，则可以确定像素组的划分数量是第四划分数量，确定划分方式是第四尺寸规格。当然，水平预测模式和非水平预测模式的区分方式，以及，垂直预测模式和非垂直预测模式的区分方式，只是两个示例，对此不做限制。
比如说，可以将当前图像区域的预测模式区分为第一预测模式和非第一预测模式，第一预测模式对应第一种划分属性(划分数量、滤波区域和划分方式)，非第一预测模式对应第二种划分属性(划分数量、滤波区域和划分方式)。又例如，可以将当前图像区域的预测模式区分为第一预测模式、第二预测模式、非第一非第二预测模式，第一预测模式对应第一种划分属性(划分数量、滤波区域和划分方式)，第二预测模式对应第二种划分属性(划分数量、滤波区域和划分方式)，非第一非第二预测模式对应第三种划分属性(划分数量、滤波区域和划分方式)。又例如，可以将当前图像区域的预测模式区分为第一预测模式和第二预测模式，第一预测模式对应第一种划分属性(划分数量、滤波区域和划分方式)，第二预测模式对应第二种划分属性(划分数量、滤波区域和划分方式)，以此类推。
当然，在实际应用中，也可以划分为更多的预测模式，对此不做限制。
为了方便描述，本实施例中，以将当前图像区域的预测模式区分为水平预测模式和非水平预测模式为例。若当前图像区域的预测模式是水平预测模式，则确定像素组的划分数量是第一划分数量，确定像素组的滤波区域是第一滤波区域，确定划分方式是第一尺寸规格；若当前图像区域的预测模式不是水平预测模式，则确定像素组的划分数量是第二划分数量，确定像素组的滤波区域是第二滤波区域，确定划分方式是第二尺寸规格。
其中，关于第一划分数量，可以根据经验配置，如可以是2个、4个、6个、8个、16个等，对此不做限制。关于第一滤波区域，可以是当前图像区域的全部区域，也可以是当前图像区域的部分区域，对此不做限制。关于第一尺寸规格，可以根据经验配置，第一尺寸规格可以包括宽度和高度，宽度可以是2、4、6、8、12、16等，对此不做限制，高度可以是1、2、4、6、8、12、16等，对此不做限制。此外，关于第二划分数量，可以根据经验配置，如可以是2个、4个、6个、8个、16个等，对此不做限制。关于第二滤波区域，可以是当前图像区域的全部区域，也可以是当前图像区域的部分区域，对此不做限制。关于第二尺寸规格，可以根据经验配置，第二尺寸规格可以包括宽度和高度，宽度可以是2、4、6、8、12、16等，对此不做限制，高度可以是1、2、4、6、8、 12、16等，对此不做限制。
比如说，若当前图像区域是16*2的图像块，则在当前图像区域的预测模式是水平预测模式时，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是8*1；在该情况下，第一划分数量是4，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是8*1，参见图5A所示，是将16*2的图像块划分为4个8*1的像素组。
或者，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是16*1；在该情况下，第一划分数量是2，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是16*1，参见图5B所示，是将16*2的图像块划分为2个16*1的像素组。
或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2；在该情况下，第一划分数量是4，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是4*2，参见图5C所示，是将16*2的图像块划分为4个4*2的像素组。
或者，可以将当前图像区域的所有像素点划分至8个像素组，每个像素组的尺寸是2*2；在该情况下，第一划分数量是8，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是2*2，参见图5D所示，是将16*2的图像块划分为8个2*2的像素组。
当然，上述只是水平预测模式下划分的几个示例，对此不做限制。
此外，若当前图像区域是16*2的图像块，在当前图像区域的预测模式不是水平预测模式时，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2。在该情况下，第二划分数量是4，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是4*2，参见图5C所示，是将16*2的图像块划分为4个4*2的像素组。
或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是8*1；在该情况下，第二划分数量是4，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是8*1，参见图5A所示，是将16*2的图像块划分为4个8*1的像素组。
或者，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是16*1；在该情况下，第二划分数量是2，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是16*1，参见图5B所示，是将16*2的图像块划分为2个16*1的像素组。
或者，可以将当前图像区域的所有像素点划分至8个像素组，每个像素组的尺寸是2*2；在该情况下，第二划分数量是8，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是2*2，参见图5D所示，是将16*2的图像块划分为8个2*2的像素组。
当然，上述只是非水平预测模式下划分的几个示例，对此不做限制。
又例如，若当前图像区域是8*2的图像块，则在当前图像区域的预测模式是水平预测模式时，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是4*2；在该情况下，第一划分数量是2，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是4*2。或者，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是8*1；在该情况下，第一划分数量是2，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是8*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是8*2；在该情况下，第一划分数量是1，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是8*2。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是2*2；在该情况下，第一划分数量是4，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是2*2。当然，上述只是水平预测模式下划分的几个示例，对此不做限制。
此外，若当前图像区域是8*2的图像块，则在当前图像区域的预测模式不是水平预测模式时，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是4*2；在该情况下，第二划分数量是2，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是4*2。或者，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是8*1；在该情况下，第二划分数量是2，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是8*1。或者，可以将当前图像区域的所有像素点划分至1个 像素组，每个像素组的尺寸是8*2；在该情况下，第二划分数量是1，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是8*2。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是2*2；在该情况下，第二划分数量是4，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是2*2。当然，上述只是非水平预测模式下划分的几个示例，对此不做限制。
又例如，若当前图像区域是16*1的图像块，则在当前图像区域的预测模式是水平预测模式时，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是8*1；在该情况下，第一划分数量是2，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是8*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*1；在该情况下，第一划分数量是4，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是4*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是16*1；在该情况下，第一划分数量是1，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是16*1。或者，可以将当前图像区域的所有像素点划分至8个像素组，每个像素组的尺寸是2*1；在该情况下，第一划分数量是8，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是2*1。当然，上述只是水平预测模式下划分的几个示例，对此不做限制。
此外，若当前图像区域是16*1的图像块，则在当前图像区域的预测模式不是水平预测模式时，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是8*1；在该情况下，第二划分数量是2，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是8*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*1；在该情况下，第二划分数量是4，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是4*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是16*1；在该情况下，第二划分数量是1，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是16*1。或者，可以将当前图像区域的所有像素点划分至8个像素组，每个像素组的尺寸是2*1；在该情况下，第二划分数量是8，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是2*1。当然，上述只是非水平预测模式下划分的几个示例，对此不做限制。
又例如，若当前图像区域是8*1的图像块，则在当前图像区域的预测模式是水平预测模式时，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是4*1；在该情况下，第一划分数量是2，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是4*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是2*1；在该情况下，第一划分数量是4，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是2*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是8*1；在该情况下，第一划分数量是1，第一滤波区域是当前图像区域的全部区域，第一尺寸规格是8*1。当然，上述只是水平预测模式下划分的几个示例，对此不做限制。
此外，若当前图像区域是8*1的图像块，则在当前图像区域的预测模式不是水平预测模式时，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是4*1；在该情况下，第二划分数量是2，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是4*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是2*1；在该情况下，第二划分数量是4，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是2*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是8*1；在该情况下，第二划分数量是1，第二滤波区域是当前图像区域的全部区域，第二尺寸规格是8*1。当然，上述只是非水平预测模式下划分的几个示例，对此不做限制。
在实际应用中，在当前图像区的尺寸是其它尺寸时，如16*4的图像块、8*4的图 像块、16*8的图像块等，其划分方式与上述方式类似，本实施例中不再重复赘述。
实施例11：针对实施例1至实施例8，对于编码端和解码端来说，当前图像区域可以对应多个像素组，例如，将当前图像区域的所有像素点划分至多个像素组，即对所有像素点进行分类。本实施例中，可以采用如下方式确定当前图像区域对应的多个像素组：采用默认策略确定当前图像区域对应的多个像素组。比如说，可以采用默认策略确定像素组的划分属性，并基于该划分属性确定当前图像区域对应的多个像素组。示例性的，该划分属性可以包括划分数量、滤波区域和划分方式中的至少一种，若该划分属性包括划分数量、滤波区域和划分方式，则确定像素组的划分数量、滤波区域和划分方式，并基于划分数量、滤波区域和划分方式确定当前图像区域对应的多个像素组。若该划分属性包括划分数量和划分方式，则确定像素组的划分数量和划分方式，并基于划分数量和划分方式确定当前图像区域对应的多个像素组。其中，划分数量用于表示将当前图像区域划分为多少个像素组，滤波区域用于表示将当前图像区域的哪部分区域划分为多个像素组，划分方式用于表示每个像素组的尺寸规格。
在上述方式中，划分数量、滤波区域和划分方式均可以基于默认策略指定，如指定划分数量是第一划分数量，滤波区域是第一滤波区域，划分方式是第一尺寸规格，又例如，指定划分数量是第二划分数量，滤波区域是第二滤波区域，划分方式是第二尺寸规格。
其中，划分数量可以根据经验配置，如可以是2个、4个、6个、8个、16个等，对此不做限制。滤波区域可以是当前图像区域的全部区域，也可以是当前图像区域的部分区域，对此不做限制。划分方式对应的尺寸规格可以根据经验配置，尺寸规格可以包括宽度和高度，宽度可以是2、4、6、8、12、16等，对此不做限制，高度可以是1、2、4、6、8、12、16等，对此不做限制。
比如说，若当前图像区域是16*2的图像块，则可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是8*1。或者，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是16*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*2。或者，可以将当前图像区域的所有像素点划分至8个像素组，每个像素组的尺寸是2*2。当然，上述只是几个示例，对此不做限制。
又例如，若当前图像区域是8*2的图像块，则可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是4*2。或者，可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是8*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是8*2。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是2*2。当然，上述只是几个示例，对此不做限制。
又例如，若当前图像区域是16*1的图像块，则可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是8*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是4*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是16*1。或者，可以将当前图像区域的所有像素点划分至8个像素组，每个像素组的尺寸是2*1。当然，上述只是几个示例，对此不做限制。
又例如，若当前图像区域是8*1的图像块，则可以将当前图像区域的所有像素点划分至2个像素组，每个像素组的尺寸是4*1。或者，可以将当前图像区域的所有像素点划分至4个像素组，每个像素组的尺寸是2*1。或者，可以将当前图像区域的所有像素点划分至1个像素组，每个像素组的尺寸是8*1。当然，上述只是几个示例，对此不做限制。
在实际应用中，在当前图像区的尺寸是其它尺寸时，如16*4的图像块、8*4的图 像块、16*8的图像块等，其划分方式与上述方式类似，本实施例中不再重复赘述。
实施例12：针对实施例1至实施例8，对于编码端和解码端来说，当前图像区域可以对应多个像素组，例如，将当前图像区域的所有像素点划分至多个像素组，即对所有像素点进行分类。本实施例中，可以采用如下方式确定当前图像区域对应的多个像素组：根据当前图像区域的扫描顺序确定当前图像区域对应的多个像素组，也就是说，像素组的划分可以与当前图像区域的扫描顺序有关。该方式可以理解为：利用当前图像区域的扫描顺序，将当前图像区域的所有像素点重新排列成一维，然后再将当前图像区域切分成像素组。
其中，针对当前图像区域的扫描顺序，在编码端，可以理解成残差系数编入码流的顺序。因此，在根据当前图像区域的扫描顺序确定当前图像区域对应的多个像素组时，多个像素组的顺序就与残差系数编入码流的顺序一致，在对像素组内每个像素点的重建值进行调整时，就可以减少等待时间，从而能够提高编码端的硬件处理性能。在解码端，可以理解成从码流中解析残差系数的顺序，因此，在根据当前图像区域的扫描顺序确定当前图像区域对应的多个像素组时，多个像素组的顺序就与残差系数的解析顺序一致，在对像素组内每个像素点的重建值进行调整时，就可以减少等待时间，从而能够提高解码端的硬件处理性能。
示例性的，当前图像区域的扫描顺序可以是光栅扫描顺序，如针对当前图像区域的子块的光栅扫描顺序和针对当前图像区域的光栅扫描顺序。以当前图像区域是16*2的图像块为例，参见图6A所示，是针对当前图像区域的子块的光栅扫描顺序，在实际应用中，可以将16*2的图像块划分为4个4*2的子块，当然，也可以将16*2的图像块划分为2个8*2的子块，也可以划分为其它尺寸的子块，对此不做限制。针对4个4*2的子块，参照图6A所示的光栅扫描顺序，可以将当前图像区域划分为4个4*2的像素组。显然，光栅扫描顺序是先扫描第1个子块的各像素点，然后扫描第2个子块的各像素点，然后扫描第3个子块的各像素点，然后扫描第4个子块的各像素点。因此，参见图6B所示，可以将第1个子块的各像素点划分到第1个像素组，将第2个子块的各像素点划分到第2个像素组，将第3个子块的各像素点划分到第3个像素组，将第4个子块的各像素点划分到第4个像素组。同理，参见图6D所示，针对图6C所示的光栅扫描顺序，可以将当前图像区域划分为2个8*2的像素组。
参见图6E所示，是针对当前图像区域(即当前图像区域的整体)的光栅扫描顺序，可以将当前图像区域划分为4个8*1的像素组，参见图6F所示；也可以将当前图像区域划分为2个16*1的像素组，参见图6G所示。图6E中的光栅扫描顺序是先扫描第一行的16个像素点，然后扫描第2行的16个像素点，因此，可以采用图6F或者图6G的划分方式。
示例性的，当前图像区域的扫描顺序可以是隔行扫描方式，以当前图像区域是16*2的图像块为例，参见图6H所示，是针对当前图像区域的扫描顺序，即先扫描第1行的第1个像素点，然后扫描第2行的第1个像素点，然后扫描第1行的第3个像素点，以此类推。针对图6H所示的扫描顺序，可以将当前图像区域划分为4个4*2的像素组，参见图6I所示，或者，将当前图像区域划分为2个8*2的像素组，参见图6J所示。
参见图6I所示，可以将第1、3、5、7列的像素点组成一个像素组，将2、4、6、8列的像素点组成一个像素组，将第9、11、13、15列的像素点组成一个像素组，将10、12、14、16列的像素点组成一个像素组。参见图6H所示，可以将第1、3、5、7、9、11、13、15列的像素点组成一个像素组，将2、4、6、8、10、12、14、16列的像素点组成一个像素组。
实施例13：针对实施例1至实施例12，对于编码端和解码端来说，可以基于调整值对像素点的重建值进行调整。关于调整值的取值范围，可以是[-7,7]，当然，[-7,7]的取值范围只是示例，对此不做限制，如调整值的取值范围可以是[-4,4]、[-5,5]、[-6,6]、 [-8,8]，调整值的取值范围还可以是[-4,6]、[-6,5]、[-6,8]、[-8,4]，显然，调整值的取值范围可以任意设置。
在一种可能的实施方式中，关于[-7,7]的取值范围的二值化取值，可以参见表1所示。
表1
在一种可能的实施方式中，调整值的取值范围还可以基于量化步长确定，也就是说，调整值的取值范围可以与量化步长有关。比如说，在量化步长为8时，最大的量化误差为4，那么，调整值的取值范围可以是[-4，4]，在该情况下，小于-4或者大于4的调整值是不会出现的。显然，如表2所示，可以对表1所示的二值化进行调整。当然，在实际应用中，针对不同的量化步长，可以配置不同的调整值的取值范围，对此取值范围不做限制。又例如，在量化步长为10时，调整值的取值范围可以是[-5，5]等，以此类推。
表2
在另一种可能的实施方式中，不同量化步长可以对应不同的调整值的取值范围，且调整值的取值范围内的数值数量相同，只是相邻两个数值之间可以间隔数值。比如说，量化步长A对应的取值范围是[-3，3]，一共存在7个数值，如-3、-2、-1、0、1、2、3，而量化步长B(量化步长B可以大于量化步长A)对应的取值范围是[-6，6]，但是只存在7个数值，如-6、-4、-2、0、2、4、6，量化步长C(量化步长C可以大于量化步长B)对应的取值范围是[-9，9]，但是只存在7个数值，如-9、-6、-3、0、3、6、9，以此类推。
实施例14：出于硬件限制的考虑，在一种可能的实施方式中，当前图像区域的滤波后的重建值，不能用于同行的其它图像块的参考，只能用于下一行的其它图像块的参考。对于当前图像区域同行的其它图像块，仅能参考当前图像区域的滤波前的重建值。
实施例15：针对实施例1至实施例13，编码端向解码端发送的码流中需要携带以下内容：
1、调整参数。该调整参数可以包括多个调整值，比如说，针对每个通道，该调整参数可以包括该通道的一个调整值，也可以包括该通道的至少两个调整值，为了方便描述，以一个通道为例。示例性的，当前图像区域可以对应多个像素组，当前图像区域对应的码流中只包括K个像素组对应的调整值，且K个像素组是多个像素组中的部分像素组或者全部像素组。
其中，假设当前图像区域对应的码流中包括K个像素组对应的M个调整值，则M可以为正整数，M可以小于或者等于K，也就是说，M大于等于1，且小于等于K。
比如说，若K个像素组对应同一个调整值，如调整值A，则当前图像区域对应的码流中可以只包括1个调整值，即调整值A，因此，M个调整值就是1个调整值。
若K个像素组对应两个调整值，如像素组1和像素组2对应调整值A，像素组3和像素组4对应调整值B，则当前图像区域对应的码流中可以包括2个调整值，即调整值A和调整值B，因此，M个调整值就是2个调整值。或者，当前图像区域对应的码流中可以包括4个调整值，即像素组1对应的调整值A、像素组2对应的调整值A、像素组3对应的调整值B和像素组4对应的调整值B，因此，M个调整值就是4个调整值。
若K个像素组对应K个调整值，如像素组1对应调整值A，像素组2对应调整值B，像素组3对应调整值C，像素组4对应调整值D，则当前图像区域对应的码流中可以包括4个调整值，即调整值A、调整值B、调整值C和调整值D，因此，M个调整值就是4个调整值。
2、像素组指示信息。在当前图像区域对应多个像素组(如32个像素组)时，像素组指示信息可用于指示全部像素组中的K个像素组，表示码流中携带的是这K个像素组对应的调整值。显然，若K个像素组就是全部像素组，那么，码流中就不需要携带像素组指示信息，解码端可以获知K个像素组就是全部像素组(如32个像素组)。若K个像素组是全部像素组中的部分像素组，则解码端需要获知K个像素组是哪些像素组，此时，可以采用如下方式：
显示方式：编码端向解码端发送当前图像区域对应的码流时，当前图像区域对应的码流中携带像素组指示信息，表示码流中携带的是该像素组指示信息对应的像素组的调整值。解码端可以从当前图像区域对应的码流中解析K个像素组对应的像素组指示信息，获知码流中携带的调整参数是该像素组指示信息对应的K个像素组的调整值。
比如说，像素组指示信息包括K个像素组的索引值，这些索引值表示像素组是所有像素组中的第几个像素组，以K个像素组包括像素组1、像素组2、像素组3和像素组4为例，则像素组指示信息可以包括像素组1的索引值、像素组2的索引值、像素组3的索引值和像素组4的索引值。
又例如，假设K个像素组是连续像素组，该像素组指示信息可以包括K个像素组中部分像素组的索引值，剩余像素组的索引值可以隐式推导出。以K个像素组包括像素组1、像素组2、像素组3和像素组4为例，则像素组指示信息可以只包括像素组1的索引值，由于K个像素组是连续像素组，因此，可以隐式推导出像素组2的索引值、像素组3的索引值和像素组4的索引值。
隐式方式：若K个像素组是所有像素组中的部分像素组，且K个像素组是处于默认位置的K个像素组，如K个像素组固定为前面4个像素组，或K个像素组固定为第1、3、5、7个像素组，或K个像素组固定为后面4个像素组，那么，编码端可以不在当前图像区域对应的码流中编码K个像素组对应的像素组指示信息，解码端也不需要从当前图像区域对应的码流中解析K个像素组对应的像素组指示信息。在此基础上，解码端可以获知码流中携带的调整参数是默认位置的K个像素组的调整值，例如，调整参数是前面4个像素组的调整值，或调整参数是第1、3、5、7个像素组的调整值，或调整 参数是后面4个像素组的调整值。
3、调整值分组指示信息。在当前图像区域对应的码流中携带K个像素组对应的M个调整值时，调整值分组指示信息用于指示M个调整值与K个像素组之间的匹配关系。
在一种可能的实施方式中，若M个调整值只是1个调整值或者K个调整值，则调整值分组指示信息可以是一种标记位，即调整值分组指示信息只有第四取值和第五取值。在该情况下，若K个像素组对应同一个调整值，如K个像素组均对应调整值A，那么，调整值分组指示信息可以是第四取值，通过第四取值表示K个像素组对应同一个调整值。解码端从码流中解析出调整值分组指示信息之后，若获知调整值分组指示信息为第四取值，就可以只从码流中解析出一个调整值(如调整值A)，并将这个调整值作为K个像素组对应的调整值。
若K个像素组对应K个调整值，如K个像素组依次对应调整值A、调整值B、调整值C和调整值D(或者依次对应调整值A、调整值A、调整值B和调整值B)，那么，调整值分组指示信息可以是第五取值，通过第五取值表示K个像素组对应K个调整值。解码端从码流中解析出调整值分组指示信息之后，若获知调整值分组指示信息为第五取值，就需要从码流中解析出K个调整值，如依次解析出调整值A、调整值B、调整值C和调整值D(或者依次解析出调整值A、调整值A、调整值B和调整值B)。此时，第一个解析出的调整值A与第一个像素组(例如像素组1)对应，第二个解析出的调整值B与第二个像素组(例如像素组2)对应，第三个解析出的调整值C与第三个像素组(例如像素组3)对应，第四个解析出的调整值D与第四个像素组(例如像素组4)对应。
示例性的，可以通过表3所示的语法表，表示上述实现过程。
表3
在上述语法表中，same_offset_flag表示调整值分组指示信息，若same_offset_flag的取值是第四取值(如1)，则解码端需要从码流中解析出一个调整值，若same_offset_flag的取值是第五取值(如0)，则解码端需要依次从码流中解析出K个调整值。
针对表3所示的语法表，same_offset_flag是一个决策是否是统一补偿值的标记位，若same_offset_flag为第四取值，则表示统一补偿值，即判定K个像素组对应同一个调整值(本文的调整值也可以称为补偿值)，此时，只需要解析一个调整值，若same_offset_flag为第五取值，则表示非统一补偿值，即判定K个像素组对应K个调整值，此时，需要解析K个调整值。
在另一种可能的实施方式中，若M个调整值可能是1个调整值、2个调整值、…、K个调整值，则调整值分组指示信息可以是多种取值。
在该情况下，若K个像素组对应同一个调整值，那么，调整值分组指示信息可以是第四取值，通过第四取值表示K个像素组对应同一个调整值。在此基础上，解码端获 知调整值分组指示信息是第四取值后，可以获知K个像素组对应同一个调整值。
若K个像素组对应两个调整值，如第一个像素组和第二个像素组对应一个调整值，第三个像素组和第四个像素组对应另一个调整值。那么，调整值分组指示信息可以是第五取值，通过第五取值表示第一个像素组和第二个像素组对应一个调整值，第三个像素组和第四个像素组对应另一个调整值。在此基础上，解码端获知调整值分组指示信息是第五取值后，确定第一个像素组和第二个像素组对应一个调整值，第三个像素组和第四个像素组对应另一个调整值。
若K个像素组对应两个调整值，如第一个像素组和第四个像素组对应一个调整值，第二个像素组和第三个像素组对应另一个调整值，那么，调整值分组指示信息可以是第三取值。在此基础上，解码端获知调整值分组指示信息是第三取值后，确定第一个像素组和第四个像素组对应一个调整值，第二个像素组和第三个像素组对应另一个调整值。
以此类推，调整值分组指示信息的每种取值，就对应一种映射关系，该映射关系可以表示M个调整值与K个像素组之间的匹配关系，关于调整值分组指示信息的取值和映射关系之间的对应关系，可以在编码端和解码端约定，对此不做限制。
综上所述，调整值分组指示信息用于指示M个调整值与K个像素组之间的匹配关系。并且，解码端从码流中解析出调整值分组指示信息之后，就可以基于调整值分组指示信息从当前图像区域对应的码流中解析M个调整值，并基于M个调整值确定K个像素组对应的调整值，即基于M个调整值与K个像素组之间的匹配关系，确定K个像素组对应的调整值。
示例性的，上述各实施例可以单独实现，也可以组合实现，比如说，实施例1至实施例15中的每个实施例，可以单独实现，实施例1至实施例15中的至少两个实施例，可以组合实现。
示例性的，上述各实施例中，编码端的内容也可以应用到解码端，即解码端可以采用相同方式处理，解码端的内容也可以应用到编码端，即编码端可以采用相同方式处理。
实施例16：基于与上述方法同样的申请构思，本申请实施例中还提出一种解码装置，所述解码装置应用于解码端，所述解码装置包括：存储器，其经配置以存储视频数据；解码器，其经配置以实现上述实施例1至实施例15中的解码方法，即解码端的处理流程。
比如说，在一种可能的实施方式中，解码器，其经配置以实现：
基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整；
若确定需要对所述当前图像区域进行重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；
基于所述调整参数对所述当前图像区域的重建值进行调整。
基于与上述方法同样的申请构思，本申请实施例中还提出一种编码装置，所述编码装置应用于编码端，所述编码装置包括：存储器，其经配置以存储视频数据；编码器，其经配置以实现上述实施例1至实施例15中的编码方法，即编码端的处理流程。
比如说，在一种可能的实施方式中，编码器，其经配置以实现：
基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整；
若确定需要对所述当前图像区域进行重建值调整，则获取所述当前图像区域对应的调整参数，所述调整参数用于对所述当前图像区域的重建值进行调整；
在所述当前图像区域对应的码流中编码所述当前图像区域对应的调整参数。
基于与上述方法同样的申请构思，本申请实施例提供的解码端设备(也可以称为视频解码器)，从硬件层面而言，其硬件架构示意图具体可以参见图7A所示。包括：处理器711和机器可读存储介质712，机器可读存储介质712存储有能够被处理器711执行的机器可执行指令；处理器711用于执行机器可执行指令，以实现本申请上述实施例1至15的解码方法。
基于与上述方法同样的申请构思，本申请实施例提供的编码端设备(也可以称为视频编码器)，从硬件层面而言，其硬件架构示意图具体可以参见图7B所示。包括：处理器721和机器可读存储介质722，机器可读存储介质722存储有能够被处理器721执行的机器可执行指令；处理器721用于执行机器可执行指令，以实现本申请上述实施例1至15的编码方法。
基于与上述方法同样的申请构思，本申请实施例还提供一种机器可读存储介质，所述机器可读存储介质上存储有若干计算机指令，所述计算机指令被处理器执行时，能够实现本申请上述示例公开的方法，如上述各实施例中的解码方法或者编码方法。
基于与上述方法同样的申请构思，本申请实施例还提供一种计算机应用程序，所述计算机应用程序令被处理器执行时，能够实现本申请上述示例公开的解码方法或者编码方法。
基于与上述方法同样的申请构思，本申请实施例中还提出一种解码装置，所述解码装置应用于解码端，所述解码装置包括：确定模块，用于基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整；获取模块，用于若确定需要对所述当前图像区域进行重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；调整模块，用于基于所述调整参数对所述当前图像区域的重建值进行调整。
示例性的，所述特征信息包括第一类特征信息，所述确定模块基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整时具体用于：若所述当前图像区域对应的第一类特征信息满足第一特定条件，则从所述当前图像区域对应的码流中获取调整控制开关对应的标记位，基于所述标记位确定是否需要对所述当前图像区域进行重建值调整；其中，若所述标记位为第一取值，确定需要对所述当前图像区域进行重建值调整；若所述标记位为第二取值，确定不需要对所述当前图像区域进行重建值调整。
示例性的，所述确定模块基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整时具体用于：若所述当前图像区域对应的第一类特征信息不满足第一特定条件，则确定不需要对所述当前图像区域进行重建值调整。
示例性的，所述特征信息包括第二类特征信息，所述确定模块基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整时具体用于：若所述当前图像区域对应的第二类特征信息满足第二特定条件，则确定需要对所述当前图像区域进行重建值调整；若所述当前图像区域对应的第二类特征信息不满足第二特定条件，则确定不需要对所述当前图像区域进行重建值调整。
示例性的，所述当前图像区域对应的调整参数包括多个调整值，所述当前图像区域对应多个像素组，所述多个调整值包括K个像素组对应的调整值，K个像素组是所述多个像素组中的全部像素组或部分像素组；所述调整模块基于所述调整参数对所述当前图像区域的重建值进行调整时具体用于：针对K个像素组中的每个像素组，若所述多个调整值包括该像素组对应的调整值，则基于该像素组对应的调整值对该像素组内的像素点的重建值进行调整。
示例性的，所述获取模块，还用于从所述当前图像区域对应的码流中获取调整值分组指示信息；所述调整值分组指示信息用于指示调整值与所述K个像素组之间的映射关系；基于所述调整值分组指示信息从所述当前图像区域对应的码流中解析M个调整值，所述M为正整数，且所述M小于或者等于K；基于所述M个调整值确定所述K个像素组对应的调整值。
示例性的，所述确定模块，还用于采用确定方式确定当前图像区域对应多个像素组：按照各像素点的调整前重建值确定所述当前图像区域对应的多个像素组；或者，基于像素点的周围像素点的调整前重建值确定该像素点的分类值，按照各像素点的分类值确定所述当前图像区域对应的多个像素组；或者，按照各像素点的像素位置确定所述当前图 像区域对应的多个像素组；或者，根据当前图像区域的预测模式确定所述当前图像区域对应的多个像素组；或者，根据当前图像区域的扫描顺序确定所述当前图像区域对应的多个像素组。
示例性的，所述确定模块根据当前图像区域的预测模式确定所述当前图像区域对应的多个像素组时具体用于：根据所述当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式；基于所述划分数量、所述滤波区域和所述划分方式确定所述当前图像区域对应的多个像素组。所述确定模块根据所述当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式时具体用于：若所述当前图像区域的预测模式是水平预测模式，则确定像素组的划分数量是第一划分数量，确定像素组的滤波区域是第一滤波区域，确定划分方式是第一尺寸规格；若所述当前图像区域的预测模式不是水平预测模式，则确定像素组的划分数量是第二划分数量，确定像素组的滤波区域是第二滤波区域，确定划分方式是第二尺寸规格。
基于与上述方法同样的申请构思，本申请实施例中还提出一种编码装置，所述编码装置应用于编码端，所述编码装置包括：确定模块，用于基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整；获取模块，用于若确定需要对所述当前图像区域进行重建值调整，则获取所述当前图像区域对应的调整参数，所述调整参数用于对所述当前图像区域的重建值进行调整；编码模块，用于在所述当前图像区域对应的码流中编码所述当前图像区域对应的调整参数。
示例性的，所述特征信息包括第一类特征信息，所述确定模块基于当前图像区域对应的特征信息确定是否需要对当前图像区域进行重建值调整时具体用于：若当前图像区域对应的第一类特征信息满足第一特定条件，则确定是否需要对所述当前图像区域进行重建值调整，并在所述当前图像区域对应的码流中编码调整控制开关对应的标记位；其中，所述标记位用于指示是否需要对所述当前图像区域进行重建值调整；若当前图像区域对应的第一类特征信息不满足第一特定条件，则确定不需要对所述当前图像区域进行重建值调整。
示例性的，所述当前图像区域对应多个像素组，所述当前图像区域对应的调整参数包括多个调整值，所述多个调整值包括K个像素组对应的调整值，所述K个像素组是所述多个像素组中的全部像素组或部分像素组；所述编码模块在所述当前图像区域对应的码流中编码所述当前图像区域对应的调整参数时具体用于：在所述当前图像区域对应的码流中编码所述K个像素组对应的M个调整值，M为正整数，且M小于或等于K；其中，所述M个调整值是基于所述K个像素组对应的调整值确定；所述编码模块，还用于在所述当前图像区域对应的码流中编码调整值分组指示信息，所述调整值分组指示信息用于指示所述M个调整值与所述K个像素组之间的匹配关系。
示例性的，所述确定模块，还用于采用如下方式确定所述当前图像区域对应多个像素组：按照各像素点的调整前重建值确定所述当前图像区域对应的多个像素组；或者，基于像素点的周围像素点的调整前重建值确定该像素点的分类值，按照各像素点的分类值确定所述当前图像区域对应的多个像素组；或者，按照各像素点的像素位置确定所述当前图像区域对应的多个像素组；或者，根据当前图像区域的预测模式确定所述当前图像区域对应的多个像素组；或者，根据当前图像区域的扫描顺序确定所述当前图像区域对应的多个像素组。
示例性的，所述确定模块根据当前图像区域的预测模式确定所述当前图像区域对应的多个像素组时具体用于：根据所述当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式；基于所述划分数量、所述滤波区域和所述划分方式确定所述当前图像区域对应的多个像素组。所述确定模块根据所述当前图像区域的预测模式确定像素组的划分数量、滤波区域和划分方式时具体用于：若所述当前图像区域的预测模式是水平预测模式，则确定像素组的划分数量是第一划分数量，确定像素组的滤波区域是第一 滤波区域，确定划分方式是第一尺寸规格；若所述当前图像区域的预测模式不是水平预测模式，则确定像素组的划分数量是第二划分数量，确定像素组的滤波区域是第二滤波区域，确定划分方式是第二尺寸规格。
本领域内的技术人员应明白，本申请实施例可提供为方法、系统、或计算机程序产品。本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。本申请实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
以上所述仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。

Claims (24)

  1. 一种解码方法，其特征在于，应用于解码端，所述方法包括：
    基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；
    若确定需要对所述当前图像区域进行所述重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；
    基于所述调整参数对所述当前图像区域的重建值进行调整。
  2. 根据权利要求1所述的方法，其特征在于，所述特征信息包括第一类特征信息，所述基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行所述重建值调整，包括：
    若所述当前图像区域对应的所述第一类特征信息满足第一特定条件，则从所述当前图像区域对应的码流中获取调整控制开关对应的标记位，基于所述标记位确定是否需要对所述当前图像区域进行重建值调整；其中，若所述标记位为第一取值，确定需要对所述当前图像区域进行所述重建值调整；若所述标记位为第二取值，确定不需要对所述当前图像区域进行所述重建值调整。
  3. 根据权利要求2所述的方法，其特征在于，所述基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行所述重建值调整，包括：
    若所述当前图像区域对应的所述第一类特征信息不满足所述第一特定条件，则确定不需要对所述当前图像区域进行所述重建值调整。
  4. 根据权利要求2或3所述的方法，其特征在于，
    所述第一类特征信息包括以下至少一种：预测模式，码流缓冲区内的数据量，量化步长；
    其中，若所述第一类特征信息包括所述预测模式，在所述预测模式是指定预测模式时，确定所述预测模式满足所述第一特定条件，否则，确定所述预测模式不满足所述第一特定条件。
  5. 根据权利要求4所述的方法，其特征在于，
    所述指定预测模式是普通帧内预测模式。
  6. 根据权利要求1所述的方法，其特征在于，所述当前图像区域对应的调整参数包括多个调整值，所述当前图像区域对应多个像素组，所述多个调整值包括K个像素组对应的调整值，所述K个像素组是所述多个像素组中的全部像素组或部分像素组；
    所述基于所述调整参数对所述当前图像区域的重建值进行调整，包括：
    针对所述K个像素组中的每个像素组，若所述多个调整值包括该像素组对应的调整值，则基于该像素组对应的调整值对该像素组内的像素点的所述重建值进行调整，
    其中，K为大于或等于1的整数。
  7. 根据权利要求6所述的方法，其特征在于，若所述K个像素组是所述多个像素组中的部分像素组，所述方法还包括：
    从所述当前图像区域对应的所述码流中获取所述K个像素组对应的像素组指示信息；
    基于所述像素组指示信息从所有像素组中选取所述K个像素组；
    其中，所述像素组指示信息用于区分所有类别的像素组中的目标类别的像素组。
  8. 根据权利要求6所述的方法，其特征在于，
    所述当前图像区域对应多个像素组包括：
    按照所述当前图像区域的各所述像素点的像素位置确定所述当前图像区域对应的所述多个像素组；或者，
    根据所述当前图像区域的预测模式确定所述当前图像区域对应的所述多个像素组。
  9. 根据权利要求8所述的方法，其特征在于，所述根据所述当前图像区域的预测 模式确定所述当前图像区域对应的所述多个像素组，包括：
    根据所述当前图像区域的所述预测模式确定像素组的划分数量、滤波区域和划分方式；
    基于所述划分数量、所述滤波区域和所述划分方式确定所述当前图像区域对应的所述多个像素组。
  10. 根据权利要求9所述的方法，其特征在于，所述根据所述当前图像区域的所述预测模式确定像素组的划分数量、滤波区域和划分方式，包括：
    若所述当前图像区域的所述预测模式是水平预测模式，则确定所述像素组的所述划分数量是第一划分数量，确定所述像素组的所述滤波区域是第一滤波区域，确定所述划分方式是第一尺寸规格；
    若所述当前图像区域的所述预测模式不是所述水平预测模式，则确定所述像素组的所述划分数量是第二划分数量，确定所述像素组的所述滤波区域是第二滤波区域，确定所述划分方式是第二尺寸规格。
  11. 根据权利要求8或9所述的方法，其特征在于，
    若所述当前图像区域是16*2的图像块，所述根据所述当前图像区域的预测模式确定所述当前图像区域对应的所述多个像素组，包括：
    若所述当前图像区域的所述预测模式是水平预测模式，则将所述当前图像区域的所有所述像素点划分至4个像素组，每个所述像素组的尺寸是8*1；
    若所述当前图像区域的所述预测模式不是所述水平预测模式，则将所述当前图像区域的所有所述像素点划分至4个像素组，每个所述像素组的尺寸是4*2。
  12. 一种编码方法，其特征在于，应用于编码端，所述方法包括：
    基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；
    若确定需要对所述当前图像区域进行所述重建值调整，则获取所述当前图像区域对应的调整参数，所述调整参数用于对所述当前图像区域的重建值进行调整；
    在所述当前图像区域对应的码流中编码所述当前图像区域对应的所述调整参数。
  13. 根据权利要求12所述的方法，其特征在于，所述特征信息包括第一类特征信息，所述基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行所述重建值调整，包括：
    若所述当前图像区域对应的所述第一类特征信息满足第一特定条件，则确定是否需要对所述当前图像区域进行所述重建值调整，并在所述当前图像区域对应的所述码流中编码调整控制开关对应的标记位，其中，所述标记位用于指示是否需要对所述当前图像区域进行所述重建值调整；
    若所述当前图像区域对应的所述第一类特征信息不满足所述第一特定条件，则确定不需要对所述当前图像区域进行所述重建值调整。
  14. 根据权利要求13所述的方法，其特征在于，
    所述第一类特征信息包括以下至少一种：预测模式，码流缓冲区内的数据量，量化步长；
    其中，若所述第一类特征信息包括所述预测模式，在所述预测模式是指定预测模式时，确定所述预测模式满足所述第一特定条件，否则，确定所述预测模式不满足所述第一特定条件。
  15. 根据权利要求12所述的方法，其特征在于，所述当前图像区域对应多个像素组，所述当前图像区域对应的所述调整参数包括多个调整值，所述多个调整值包括K个像素组对应的调整值，所述K个像素组是所述多个像素组中的全部像素组或部分像素组。
  16. 根据权利要求15所述的方法，其特征在于，
    所述当前图像区域对应多个像素组包括：
    按照所述当前图像区域的各所述像素点的像素位置确定所述当前图像区域对应的所述多个像素组；或者，
    根据所述当前图像区域的预测模式确定所述当前图像区域对应的所述多个像素组。
  17. 根据权利要求16所述的方法，其特征在于，所述根据所述当前图像区域的预测模式确定所述当前图像区域对应的所述多个像素组，包括：
    根据所述当前图像区域的所述预测模式确定像素组的划分数量、滤波区域和划分方式；
    基于所述划分数量、所述滤波区域和所述划分方式确定所述当前图像区域对应的所述多个像素组。
  18. 根据权利要求17所述的方法，其特征在于，所述根据所述当前图像区域的所述预测模式确定像素组的划分数量、滤波区域和划分方式，包括：
    若所述当前图像区域的所述预测模式是水平预测模式，则确定所述像素组的所述划分数量是第一划分数量，确定所述像素组的所述滤波区域是第一滤波区域，确定所述划分方式是第一尺寸规格；
    若所述当前图像区域的所述预测模式不是所述水平预测模式，则确定所述像素组的所述划分数量是第二划分数量，确定所述像素组的所述滤波区域是第二滤波区域，确定所述划分方式是第二尺寸规格。
  19. 一种解码装置，其特征在于，所述解码装置包括：
    存储器，其经配置以存储视频数据；
    解码器，其经配置以实现：
    基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；
    若确定需要对所述当前图像区域进行所述重建值调整，则从所述当前图像区域对应的码流中获取所述当前图像区域对应的调整参数；
    基于所述调整参数对所述当前图像区域的重建值进行调整。
  20. 一种编码装置，其特征在于，所述编码装置包括：
    存储器，其经配置以存储视频数据；
    编码器，其经配置以实现：
    基于当前图像区域对应的特征信息确定是否需要对所述当前图像区域进行重建值调整；
    若确定需要对所述当前图像区域进行所述重建值调整，则获取所述当前图像区域对应的调整参数，所述调整参数用于对所述当前图像区域的重建值进行调整；
    在所述当前图像区域对应的码流中编码所述当前图像区域对应的所述调整参数。
  21. 一种解码端设备，其特征在于，包括：处理器和机器可读存储介质，所述机器可读存储介质存储有能够被所述处理器执行的机器可执行指令；所述处理器用于执行所述机器可执行指令，以实现权利要求1至11任一项所述的方法。
  22. 一种编码端设备，其特征在于，包括：处理器和机器可读存储介质，所述机器可读存储介质存储有能够被所述处理器执行的机器可执行指令；所述处理器用于执行所述机器可执行指令，以实现权利要求12至18任一项所述的方法。
  23. 一种机器可读存储介质，其特征在于，所述机器可读存储介质上存储有计算机指令，所述计算机指令被至少一个处理器执行时，实现权利要求1至11任一项所述的方法。
  24. 一种机器可读存储介质，其特征在于，所述机器可读存储介质上存储有计算机指令，所述计算机指令被至少一个处理器执行时，实现权利要求12至18任一项所述的方法。
PCT/CN2023/090956 2022-04-27 2023-04-26 一种解码、编码方法、装置及其设备 Ceased WO2023208069A1 (zh)

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