WO2024093994A1 - 编解码方法和装置 - Google Patents

编解码方法和装置 Download PDF

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Publication number
WO2024093994A1
WO2024093994A1 PCT/CN2023/128410 CN2023128410W WO2024093994A1 WO 2024093994 A1 WO2024093994 A1 WO 2024093994A1 CN 2023128410 W CN2023128410 W CN 2023128410W WO 2024093994 A1 WO2024093994 A1 WO 2024093994A1
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block
encoded
image block
coding
prediction
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English (en)
French (fr)
Inventor
王丹妮
杨海涛
罗忆
冯俊凯
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Huawei Technologies Co Ltd
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Huawei Technologies Co Ltd
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Priority to EP23884924.4A priority Critical patent/EP4583507A4/en
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Anticipated expiration legal-status Critical
Priority to US19/198,294 priority patent/US20250267280A1/en
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    • 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
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    • H04N19/51—Motion estimation or motion compensation
    • H04N19/513—Processing of motion vectors
    • H04N19/517—Processing of motion vectors by encoding
    • H04N19/52—Processing of motion vectors by encoding by predictive encoding

Definitions

  • the embodiments of the present application relate to the field of media technology, and in particular to a coding and decoding method and device.
  • the media device uses the display interface when transmitting media content.
  • the display interface transmits media content, it can compress the media content through encoding operations to reduce the bandwidth during the transmission of the media content.
  • the receiving end needs to decode the compressed media content through decoding operations to restore the media content.
  • Bit rate control can adjust the output bit rate during the encoding process. Different bit rate control methods will have a significant impact on the quality of the decoded image.
  • the embodiment of the present application provides a coding and decoding method and device, which can improve the image quality of the image obtained after decoding. To achieve the above purpose, the embodiment of the present application adopts the following technical solutions:
  • an embodiment of the present application provides a coding method, the method comprising: first obtaining an image block to be coded, then determining the coding complexity of the image block to be coded according to multiple prediction modes, then determining the quantization parameter of the image block to be coded according to the coding complexity, and then encoding the image block to be coded according to the quantization parameter to generate a bitstream.
  • the multiple prediction modes include at least one of block-level prediction, point-level prediction, and intra-frame block copy prediction, and the coding complexity is used to characterize the coding difficulty of the image block to be coded.
  • the quantization parameter used in the encoding process will directly affect the image quality of the decoded image.
  • the image quality of the decoded image can be improved by adjusting the quantization parameter through the coding complexity of the image.
  • the related art uses the horizontal and vertical gradients of the image to calculate the coding complexity of the image.
  • the result of the gradient calculation is far different from the prediction error of the weak directional prediction mode.
  • the coding complexity calculated by the gradient and the actual coding complexity of the actual current coding block (image block) in the best prediction mode are far different, which leads to the inaccurate derived quantization parameter, affecting the image quality.
  • the embodiment of the present application determines the coding complexity of the image block to be encoded through multiple prediction modes.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the accuracy of the improved quantization parameter will make the image quality of the decoded image correspondingly improved.
  • a prediction operation can be performed on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode; then, a target parameter corresponding to the image block to be encoded and each prediction mode is determined according to the prediction residual, and the target parameter includes at least one of the sum of absolute errors, the sum of absolute transformation differences, or the number of lossless coding bits; and then, the coding complexity of the image block to be encoded is determined according to the target parameter.
  • the method provided in the embodiment of the present application can perform prediction operations on the image block to be encoded through multiple prediction modes to obtain the sum of absolute errors, the sum of absolute transformation differences or the number of lossless coding bits corresponding to the image block to be encoded and each prediction mode, and then determine the coding complexity of the image block to be encoded based on this information.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will make the image quality of the decoded image correspondingly improved.
  • the first coding complexity of the image block to be encoded can be determined according to the target parameter; the image block to be encoded is divided into a plurality of sub-blocks. A horizontal difference block and a vertical difference block of each of the plurality of sub-blocks are determined. The horizontal difference block and the vertical difference block of the sub-block determine the second coding complexity of the image block to be coded. The coding complexity of the image block to be coded is determined according to the first coding complexity and the second coding complexity.
  • the method provided in the embodiment of the present application can calculate the image coding complexity through multiple prediction modes and the horizontal and vertical gradients of the image. Compared with calculating the image coding complexity only through the horizontal and vertical gradients of the image, the accuracy of the coding complexity of the image block can be improved in the weakly directional prediction mode. By improving the accuracy of the coding complexity, the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will make the image quality of the decoded image correspondingly improved.
  • the coding complexity of the image block to be encoded can be determined according to the target absolute error, the target sum of absolute transformation differences or the target number of lossless coding bits
  • the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode
  • the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode
  • the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the embodiment of the present application determines the target absolute error, the target sum of absolute transformation differences or the target number of lossless coding bits through multiple prediction modes, and then determines the coding complexity of the image block to be encoded through the target absolute error, the target sum of absolute transformation differences or the target number of lossless coding bits.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will lead to a corresponding improvement in the image quality of the decoded image.
  • the image block to be encoded may be divided into a plurality of sub-blocks. Prediction operations are performed on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Target parameters corresponding to each sub-block and each prediction mode are determined according to the prediction residuals, and the target parameters include at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits. The coding complexity of the image block to be encoded is determined according to the target parameters.
  • the method provided in the embodiment of the present application can perform prediction operations on the sub-blocks of the image block to be encoded through multiple prediction modes to obtain the absolute error sum, the absolute transformation difference sum or the number of lossless coding bits corresponding to each sub-block of the image block to be encoded and each prediction mode, and then determine the coding complexity of the image block to be encoded based on this information.
  • the best prediction mode of the current image block is a strong directional prediction mode or a weak directional prediction mode
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will make the image quality of the decoded image correspondingly improved.
  • the image block to be encoded is divided into multiple sub-blocks, and a prediction operation is performed on the multiple sub-blocks of the image block to be encoded through multiple prediction modes. The accuracy of the obtained coding complexity can be further improved.
  • the coding complexity of each sub-block may be determined according to the target parameter.
  • the coding complexity of the image block to be encoded may be determined according to the coding complexity of each sub-block.
  • the method provided in the embodiment of the present application can perform prediction operations on multiple sub-blocks of the image block to be encoded through multiple prediction modes to obtain the coding complexity of each sub-block of the encoded image block, and then calculate the coding complexity of the image block to be encoded through the coding complexity of each sub-block of the image block to be encoded.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will lead to a corresponding improvement in the image quality of the decoded image.
  • a first coding complexity of the image block to be encoded can be determined according to the target parameters; a horizontal difference block and a vertical difference block of each sub-block among the multiple sub-blocks can be determined; a second coding complexity of the image block to be encoded can be determined according to the horizontal difference block and the vertical difference block of each sub-block; and the coding complexity of the image block to be encoded can be determined according to the first coding complexity and the second coding complexity.
  • the method provided in the embodiment of the present application can calculate the image coding complexity through multiple prediction modes and the horizontal and vertical gradients of the image. Compared with calculating the image coding complexity only through the horizontal and vertical gradients of the image, the accuracy of the coding complexity of the image block can be improved in the weakly directional prediction mode. By improving the accuracy of the coding complexity, the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will make the decoded image The image quality is improved accordingly.
  • the coding complexity may be encoded into the code stream.
  • the embodiments of the present application can encode the coding complexity of the image block to be encoded determined by multiple prediction modes into the bitstream, so that the decoding end decodes the bitstream according to the coding complexity in the bitstream to obtain a decoded image.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the improved accuracy of the quantization parameter will lead to a corresponding improvement in the image quality of the decoded image.
  • an embodiment of the present application further provides a decoding method, the method comprising: obtaining the coding complexity of an image block to be encoded, the coding complexity being used to characterize the coding difficulty of the image block to be encoded, the coding complexity being determined by a plurality of prediction modes, the plurality of prediction modes comprising at least one of block-level prediction, point-level prediction and intra-frame block copy prediction.
  • Decode a bitstream according to the quantization parameter to obtain a decoded image block, the bitstream being generated by encoding the image block to be encoded, the decoded image block being the reconstructed image block to be encoded.
  • the quantization parameter used in the encoding process will directly affect the image quality of the decoded image.
  • the image quality of the decoded image can be improved by adjusting the quantization parameter through the coding complexity of the image.
  • the related art uses the horizontal and vertical gradients of the image to calculate the coding complexity of the image.
  • the result of the gradient calculation is far different from the prediction error of the weak directional prediction mode.
  • the coding complexity calculated by the gradient and the actual coding complexity of the actual current coding block (image block) in the best prediction mode are far different, which leads to the inaccurate derived quantization parameter, affecting the image quality.
  • the embodiment of the present application determines the coding complexity of the image block to be encoded through multiple prediction modes.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the accuracy of the improved quantization parameter will make the image quality of the decoded image correspondingly improved.
  • entropy decoding may be performed on the code stream to obtain the coding complexity.
  • a prediction operation may be performed on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode.
  • a target parameter corresponding to the image block to be encoded and each prediction mode is determined according to the prediction residual, and the target parameter includes at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits.
  • the coding complexity of the image block to be encoded is determined according to the target parameter.
  • a first coding complexity of the image block to be encoded is determined according to the target parameter.
  • the image block to be encoded is divided into a plurality of sub-blocks.
  • a horizontal difference block and a vertical difference block of each of the plurality of sub-blocks are determined.
  • a second coding complexity of the image block to be encoded is determined according to the horizontal difference block and the vertical difference block of each sub-block.
  • the coding complexity of the image block to be encoded is determined according to the first coding complexity and the second coding complexity.
  • the coding complexity of the image block to be encoded is determined according to a target absolute error, a target sum of absolute transformation differences or a target number of lossless coding bits, wherein the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode, the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode, and the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the image block to be encoded is divided into a plurality of sub-blocks. Prediction operations are performed on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Target parameters corresponding to each sub-block and each prediction mode are determined according to the prediction residuals, and the target parameters include at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits. The coding complexity of the image block to be encoded is determined according to the target parameters.
  • the coding complexity of each sub-block is determined according to the target parameter.
  • the coding complexity of the image block to be encoded is determined according to the coding complexity of each sub-block.
  • a first coding complexity of the image block to be encoded is determined according to the target parameter.
  • a horizontal difference block and a vertical difference block of each of the multiple sub-blocks are determined.
  • a second coding complexity of the image block to be encoded is determined according to the horizontal difference block and the vertical difference block of each sub-block.
  • the coding complexity of the image block to be encoded is determined according to the first coding complexity and the second coding complexity.
  • an embodiment of the present application further provides a coding device, which includes: an acquisition unit, a first determination unit, a second determination unit and a coding unit.
  • the acquisition unit is used to acquire an image block to be coded.
  • the first determination unit is used to determine the image block according to multiple prediction modes.
  • the method comprises: determining a coding complexity of the image block to be coded, wherein the multiple prediction modes include at least one of block-level prediction, point-level prediction and intra-block copy prediction, and the coding complexity is used to characterize the coding difficulty of the image block to be coded.
  • the second determining unit is used to determine a quantization parameter of the image block to be coded according to the coding complexity.
  • the coding unit is used to encode the image block to be coded according to the quantization parameter to generate a bit stream.
  • the first determination unit is specifically configured to: perform a prediction operation on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode.
  • the first determination unit is specifically used to: determine a first coding complexity of the image block to be encoded according to the target parameter. Divide the image block to be encoded into a plurality of sub-blocks. Determine a horizontal difference block and a vertical difference block of each of the plurality of sub-blocks. Determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each sub-block. Determine the coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • the first determination unit is specifically used to: determine the coding complexity of the image block to be encoded according to a target absolute error, a target sum of absolute transformation differences or a target number of lossless coding bits, wherein the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode, the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode, and the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the first determination unit is specifically configured to: divide the image block to be encoded into a plurality of sub-blocks. Perform prediction operations on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Determine a target parameter corresponding to each sub-block and each prediction mode according to the prediction residual, the target parameter including at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits. Determine the coding complexity of the image block to be encoded according to the target parameter.
  • the first determining unit is specifically configured to: determine the coding complexity of each sub-block according to the target parameter, and determine the coding complexity of the to-be-coded image block according to the coding complexity of each sub-block.
  • the first determining unit is specifically configured to: determine a first coding complexity of the image block to be encoded according to the target parameter; determine a horizontal difference block and a vertical difference block of each of the multiple sub-blocks; determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each sub-block; and determine a coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • the encoding unit is further configured to: encode the encoding complexity into the bitstream.
  • an embodiment of the present application further provides a decoding device, which includes: an acquisition unit, a determination unit and a decoding unit.
  • the acquisition unit is used to acquire the coding complexity of the image block to be encoded
  • the coding complexity is used to characterize the coding difficulty of the image block to be encoded.
  • the coding complexity is determined by multiple prediction modes, and the multiple prediction modes include at least one of block-level prediction, point-level prediction and intra-frame block copy prediction.
  • the determination unit is used to determine the quantization parameter of the image block to be encoded according to the coding complexity.
  • the decoding unit is used to decode the code stream according to the quantization parameter to obtain a decoded image block, and the code stream is generated by encoding the image block to be encoded, and the decoded image block is the reconstructed image block to be encoded.
  • the acquisition unit is specifically configured to: perform entropy decoding on the bit stream to obtain the coding complexity.
  • the acquisition unit is specifically configured to: perform a prediction operation on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode.
  • the acquisition unit is specifically used to: determine a first coding complexity of the image block to be encoded according to the target parameter. Divide the image block to be encoded into a plurality of sub-blocks. Determine a horizontal difference block and a vertical difference block of each of the plurality of sub-blocks. Determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each sub-block. Determine the coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • the acquisition unit is specifically used to: determine the coding complexity of the image block to be encoded based on a target absolute error, a target sum of absolute transformation differences or a target number of lossless coding bits, wherein the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode, the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode, and the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the acquisition unit is specifically used to: divide the image block to be encoded into a plurality of sub-blocks. Perform prediction operations on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Determine a target parameter corresponding to each sub-block and each prediction mode according to the prediction residual, the target parameter including at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits. Determine the coding complexity of the image block to be encoded according to the target parameter.
  • the acquisition unit is specifically configured to: determine the coding complexity of each sub-block according to the target parameter. Determine the coding complexity of the image block to be encoded according to the coding complexity of each sub-block.
  • the acquisition unit is specifically used to: determine a first coding complexity of the image block to be encoded according to the target parameter; determine a horizontal difference block and a vertical difference block of each of the multiple sub-blocks; determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each sub-block; and determine a coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • an embodiment of the present application further provides a coding device, comprising: at least one processor, when the at least one processor executes program code or instructions, it implements the method described in the above first aspect or any possible implementation method thereof.
  • the device may further include at least one memory, and the at least one memory is used to store the program code or instruction.
  • an embodiment of the present application further provides a decoding device, comprising: at least one processor, when the at least one processor executes program code or instructions, it implements the method described in the above second aspect or any possible implementation method thereof.
  • the device may further include at least one memory, and the at least one memory is used to store the program code or instruction.
  • an embodiment of the present application further provides a chip, comprising: an input interface, an output interface, and at least one processor.
  • the chip further comprises a memory.
  • the at least one processor is used to execute the code in the memory, and when the at least one processor executes the code, the chip implements the method described in the first aspect or any possible implementation thereof.
  • the above chip may also be an integrated circuit.
  • an embodiment of the present application further provides a computer-readable storage medium for storing a computer program, wherein the computer program includes methods for implementing the method described in the above-mentioned first aspect or any possible implementation thereof.
  • an embodiment of the present application further provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to implement the method described in the first aspect or any possible implementation thereof.
  • the encoding and decoding device, computer storage medium, computer program product and chip provided in this embodiment are all used to execute the encoding and decoding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the encoding and decoding method provided above, and will not be repeated here.
  • FIG. 1a is an exemplary block diagram of a decoding system provided in an embodiment of the present application.
  • FIG. 1b is an exemplary block diagram of a video decoding system provided in an embodiment of the present application.
  • FIG2 is an exemplary block diagram of a video encoder provided in an embodiment of the present application.
  • FIG3 is an exemplary block diagram of a video decoder provided in an embodiment of the present application.
  • FIG4 is an exemplary schematic diagram of a candidate image block provided in an embodiment of the present application.
  • FIG5 is an exemplary block diagram of a video decoding device provided in an embodiment of the present application.
  • FIG6 is an exemplary block diagram of a device provided in an embodiment of the present application.
  • FIG7 is a schematic diagram of an encoding method provided in an embodiment of the present application.
  • FIG8 is a schematic diagram of a process for determining coding complexity provided by an embodiment of the present application.
  • FIG9 is a schematic diagram of another process for determining coding complexity provided in an embodiment of the present application.
  • FIG10 is a schematic diagram of another process for determining coding complexity provided in an embodiment of the present application.
  • FIG11 is a schematic diagram of another process for determining coding complexity provided in an embodiment of the present application.
  • FIG12 is a schematic diagram of a decoding method provided in an embodiment of the present application.
  • FIG13 is a schematic diagram of an encoding device provided in an embodiment of the present application.
  • FIG14 is a schematic diagram of a decoding device provided in an embodiment of the present application.
  • FIG. 15 is a schematic diagram of the structure of a chip provided in an embodiment of the present application.
  • a and/or B in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist.
  • a and/or B can mean: A exists alone, A and B exist at the same time, and B exists alone.
  • first and second and the like in the description and drawings of the embodiments of the present application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.
  • Interface compression Media devices use display interfaces when transmitting images and videos, and encode image and video content through the display interface.
  • Bit stream A binary stream generated by encoding the image and video content.
  • the input image can be divided into one or more slices. Each slice is divided into one or more coding blocks for encoding.
  • Bit rate control The process of adjusting the output bit rate during the encoding process. It is based on the analysis of the current image content, the remaining amount of the bitstream buffer, etc., and adjusts the output bit rate by changing the encoding quantization parameters, encoding mode, etc. The following is abbreviated as.
  • Quantization Parameter During the encoding process, the residual value generated by the prediction operation or the coefficient generated by the transform operation is quantized and written to the bitstream; during the decoding process, the syntax elements are dequantized to obtain the residual value or coefficient.
  • QP is the parameter used in the quantization process. Generally, the larger the QP value, the more obvious the degree of quantization. Adjusting the QP value will directly affect the length of the encoded bitstream and the quality of the decoded image.
  • Constant Bit Rate A strategy in which the length of the bit stream output by the encoder is consistent per unit time.
  • Intra Block Copy (IBC) prediction mode The current coding block can be divided into one or more sub-blocks.
  • the optimal matching block is found for each sub-block in the search area according to a certain matching criterion.
  • the optimal matching block is the prediction block of the current sub-block, and the block vector is calculated.
  • the block vector is the position vector of the current block and the optimal matching block.
  • Block-level prediction The block is used as the prediction unit.
  • the reconstructed value in the current coding block cannot be used as the prediction reference value for subsequent points in the current block.
  • Point-level prediction With a point as the prediction unit, the reconstructed value in the current coding block can be used as a prediction operation for the reference value of subsequent point predictions in the current block.
  • Data encoding and decoding includes two parts: data encoding and data decoding.
  • Data encoding is performed on the source side (or commonly referred to as the encoder side), and generally includes processing (e.g., compressing) the original data to reduce the amount of data required to represent the original data (thereby more efficiently storing and/or transmitting).
  • Data decoding is performed on the destination side (or commonly referred to as the decoder side), and generally includes inverse processing relative to the encoder side to reconstruct the original data.
  • the "encoding and decoding" of the data involved in the embodiments of the present application should be understood as the "encoding" or "decoding" of the data.
  • the encoding part and the decoding part are also collectively referred to as encoding and decoding (encoding and decoding, CODEC).
  • the original data can be reconstructed, that is, the reconstructed original data has the same quality as the original data (assuming no transmission loss or other data loss during storage or transmission).
  • further compression is performed by quantization, etc. to reduce the amount of data required to represent the original data, but the decoder side cannot completely reconstruct the original data, that is, the quality of the reconstructed original data is lower or worse than the quality of the original data.
  • the embodiments of the present application can be applied to video data and other data with compression/decompression requirements.
  • the following takes the encoding of video data (referred to as video encoding) as an example to illustrate the embodiments of the present application.
  • video encoding For other types of data (such as image data, audio data, integer data and other data with compression/decompression requirements), please refer to the following description, and the embodiments of the present application will not be repeated.
  • the encoding process of audio data and integer data does not require the data to be divided into blocks, but the data can be directly encoded. Encode the data.
  • Video coding generally refers to processing a sequence of images to form a video or video sequence.
  • the terms "picture”, “frame” or “image” can be used as synonyms.
  • Video coding standards belong to the category of "lossy hybrid video codecs" (i.e., combining spatial and temporal prediction in the pixel domain with 2D transform coding in the transform domain for applying quantization).
  • Each picture in a video sequence is usually divided into a set of non-overlapping blocks, which are usually encoded at the block level.
  • the encoder usually processes, i.e., encodes the video at the block (video block) level, for example, by generating a prediction block through spatial (intra-frame) prediction and temporal (inter-frame) prediction; subtracting the prediction block from the current block (currently processed/to be processed block) to obtain a residual block; transforming the residual block in the transform domain and quantizing the residual block to reduce the amount of data to be transmitted (compressed), while the decoder side applies the inverse processing part relative to the encoder to the encoded or compressed block to reconstruct the current block for representation.
  • the encoder needs to repeat the processing steps of the decoder so that the encoder and the decoder generate the same predictions (e.g., intra-frame predictions and inter-frame predictions) and/or reconstructed pixels for processing, i.e., encoding subsequent blocks.
  • the encoder and the decoder generate the same predictions (e.g., intra-frame predictions and inter-frame predictions) and/or reconstructed pixels for processing, i.e., encoding subsequent blocks.
  • the encoder 20 and the decoder 30 are described with reference to FIGS. 1 a to 3 .
  • FIG. 1a is an exemplary block diagram of a decoding system 10 provided in an embodiment of the present application, for example, a video decoding system 10 (or simply a decoding system 10) that can utilize the techniques of the embodiments of the present application.
  • the video encoder 20 (or simply an encoder 20) and the video decoder 30 (or simply a decoder 30) in the video decoding system 10 represent devices that can be used to perform various techniques according to various examples described in the embodiments of the present application.
  • a decoding system 10 includes a source device 12 for providing encoded image data 21 such as an encoded image to a destination device 14 for decoding the encoded image data 21 .
  • the source device 12 includes an encoder 20 , and may additionally or optionally include an image source 16 , a preprocessor (or a preprocessing unit) 18 such as an image preprocessor, and a communication interface (or a communication unit) 22 .
  • a preprocessor or a preprocessing unit 18 such as an image preprocessor
  • a communication interface or a communication unit 22 .
  • the image source 16 may include or may be any type of image capture device for capturing real-world images, etc., and/or any type of image generation device, such as a computer graphics processor for generating computer-animated images or any type of device for acquiring and/or providing real-world images, computer-generated images (e.g., screen content, virtual reality (VR) images, and/or any combination thereof (e.g., augmented reality (AR) images).
  • the image source may be any type of memory or storage for storing any of the above images.
  • the image (or image data) 17 may also be referred to as a raw image (or raw image data) 17 .
  • the preprocessor 18 is used to receive the original image data 17 and preprocess the original image data 17 to obtain a preprocessed image (or preprocessed image data) 19.
  • the preprocessing performed by the preprocessor 18 may include trimming, color format conversion (e.g., from RGB to YCbCr), color adjustment, or denoising. It is understood that the preprocessing unit 18 may be an optional component.
  • the video encoder (or encoder) 20 is used to receive the pre-processed image data 19 and provide encoded image data 21 (which will be further described below with reference to FIG. 2 etc.).
  • the communication interface 22 in the source device 12 can be used to receive the encoded image data 21 and send the encoded image data 21 (or any other processed version) to another device such as the destination device 14 or any other device through the communication channel 13 for storage or direct reconstruction.
  • the destination device 14 includes a decoder 30 and, in addition or alternatively, may include a communication interface (or communication unit) 28 , a post-processor (or post-processing unit) 32 , and a display device 34 .
  • the communication interface 28 in the destination device 14 is used to receive the encoded image data 21 (or any other processed version) directly from the source device 12 or from any other source device such as a storage device, for example, the storage device is a encoded image data storage device, and provide the encoded image data 21 to the decoder 30.
  • the communication interface 22 and the communication interface 28 can be used to send or receive encoded image data (or encoded data) 21 through a direct communication link between the source device 12 and the destination device 14, such as a direct wired or wireless connection, or through any type of network, such as a wired network, a wireless network or any combination thereof, any type of private network and public network or any type of combination thereof.
  • the communication interface 22 may be used to encapsulate the encoded image data 21 into a suitable format such as a message, and/or process the encoded image data using any type of transmission coding or processing for transmission over a communication link or network.
  • the communication interface 28 corresponds to the communication interface 22 , for example, and can be used to receive transmission data and process the transmission data using any type of corresponding transmission decoding or processing and/or decapsulation to obtain the encoded image data 21 .
  • Both the communication interface 22 and the communication interface 28 can be configured as a unidirectional communication interface as indicated by the arrow of the corresponding communication channel 13 pointing from the source device 12 to the destination device 14 in Figure 1a, or a bidirectional communication interface, and can be used to send and receive messages, etc. to establish a connection, confirm and exchange any other information related to the communication link and/or data transmission such as encoded image data transmission, etc.
  • the video decoder (or decoder) 30 is used to receive the encoded image data 21 and provide decoded image data (or decoded image data) 31 (hereinafter referred to as decoder). The surface will be further described according to Figure 3, etc.).
  • the post-processor 32 is used to post-process the decoded image data 31 (also called reconstructed image data) such as the decoded image to obtain the post-processed image data 33 such as the post-processed image.
  • the post-processing performed by the post-processing unit 32 may include, for example, color format conversion (e.g., from YCbCr to RGB), color adjustment, cropping or resampling, or any other processing for generating the decoded image data 31 for display by the display device 34 or the like.
  • the display device 34 is used to receive the post-processed image data 33 to display the image to a user or viewer, etc.
  • the display device 34 can be or include any type of display for displaying the reconstructed image, such as an integrated or external display screen or display.
  • the display screen can include a liquid crystal display (LCD), an organic light emitting diode (OLED) display, a plasma display, a projector, a micro LED display, a liquid crystal on silicon (LCoS), a digital light processor (DLP), or any other type of display screen.
  • the decoding system 10 also includes a training engine 25, which is used to train the encoder 20 (especially the entropy coding unit 270 in the encoder 20) or the decoder 30 (especially the entropy decoding unit 304 in the decoder 30) to perform entropy coding on the image block to be encoded according to the estimated probability distribution.
  • a training engine 25 is used to train the encoder 20 (especially the entropy coding unit 270 in the encoder 20) or the decoder 30 (especially the entropy decoding unit 304 in the decoder 30) to perform entropy coding on the image block to be encoded according to the estimated probability distribution.
  • FIG. 1a shows the source device 12 and the destination device 14 as independent devices
  • the device embodiment may also include the source device 12 and the destination device 14 or the functions of the source device 12 and the destination device 14 at the same time, that is, the source device 12 or the corresponding function and the destination device 14 or the corresponding function at the same time.
  • the source device 12 or the corresponding function and the destination device 14 or the corresponding function may be implemented using the same hardware and/or software or by separate hardware and/or software or any combination thereof.
  • the existence and (accurate) division of different units or functions in the source device 12 and/or the destination device 14 shown in FIG. 1 a may vary according to actual devices and applications, which is obvious to technicians.
  • FIG. 1b is an exemplary block diagram of a video decoding system 40 provided in an embodiment of the present application.
  • the encoder 20 e.g., video encoder 20
  • the decoder 30 e.g., video decoder 30
  • a processing circuit in the video decoding system 40 such as one or more microprocessors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), discrete logic, hardware, video encoding dedicated processors or any combination thereof.
  • DSP digital signal processors
  • ASIC application-specific integrated circuits
  • FPGA field-programmable gate arrays
  • the encoder 20 can be implemented by a processing circuit 46 to include various modules discussed with reference to the encoder 20 of FIG. 2 and/or any other encoder system or subsystem described herein.
  • the decoder 30 can be implemented by a processing circuit 46 to include various modules discussed with reference to the decoder 30 of FIG. 3 and/or any other decoder system or subsystem described herein.
  • the processing circuit 46 can be used to perform various operations discussed below.
  • the device may store the instructions of the software in a suitable non-transitory computer-readable storage medium, and use one or more processors to execute the instructions in hardware, thereby performing the technology of the embodiment of the present application.
  • One of the video encoder 20 and the video decoder 30 may be integrated into a single device as part of a combined codec (encoder/decoder, CODEC), as shown in FIG1 b .
  • the source device 12 and the destination device 14 may include any of a variety of devices, including any type of handheld or fixed device, such as a notebook or laptop computer, a mobile phone, a smart phone, a tablet or a tablet computer, a camera, a desktop computer, a set-top box, a television, a display device, a digital media player, a video game console, a video streaming device (e.g., a content service server or a content distribution server), a broadcast receiving device, a broadcast transmitting device, and a monitoring device, etc., and may not use or use any type of operating system.
  • the source device 12 and the destination device 14 may also be devices in a cloud computing scenario, such as a virtual machine in a cloud computing scenario. In some cases, the source device 12 and the destination device 14 may be equipped with components for wireless communication. Therefore, the source device 12 and the destination device 14 may be wireless communication devices.
  • the source device 12 and the destination device 14 may be installed with virtual scene applications (applications, APPs) such as virtual reality (VR) applications, augmented reality (AR) applications, or mixed reality (MR) applications, and may run VR applications, AR applications, or MR applications based on user operations (e.g., click, touch, slide, shake, voice control, etc.).
  • the source device 12 and the destination device 14 may collect images/videos of any object in the environment through cameras and/or sensors, and then display virtual objects on the display device based on the collected images/videos.
  • the virtual objects may be virtual objects in VR scenes, AR scenes, or MR scenes (i.e., objects in the virtual environment).
  • the virtual scene application in the source device 12 and the destination device 14 can be an application built into the source device 12 and the destination device 14 themselves, or it can be an application provided by a third-party service provider and installed by the user. There is no specific limitation on this.
  • the source device 12 and the destination device 14 may be installed with a real-time video transmission application, such as a live broadcast application.
  • the source device 12 and the destination device 14 may collect images/videos through cameras and then display the collected images/videos on a display device.
  • the video decoding system 10 shown in FIG. 1a is merely exemplary, and the techniques provided in the embodiments of the present application may be applicable to video encoding settings (e.g., video encoding or video decoding), which do not necessarily include any data communication between the encoding device and the decoding device.
  • data is retrieved from a local memory, sent over a network, and so on.
  • the video encoding device can encode the data and store the data in a memory, and/or the video decoding device can retrieve the data from the memory and decode the data.
  • encoding and decoding are performed by devices that do not communicate with each other but only encode data to a memory and/or retrieve and decode data from a memory.
  • FIG. 1b is an exemplary block diagram of a video decoding system 40 provided in an embodiment of the present application.
  • the video decoding system 40 may include an imaging device 41, a video encoder 20, a video decoder 30 (and/or a video encoder/decoder implemented by a processing circuit 46), an antenna 42, one or more processors 43, one or more memory storage devices 44 and/or a display device 45.
  • imaging device 41, antenna 42, processing circuit 46, video encoder 20, video decoder 30, processor 43, memory storage 44 and/or display device 45 can communicate with each other.
  • video decoding system 40 can include only video encoder 20 or only video decoder 30.
  • antenna 42 may be used to transmit or receive a coded bit stream of video data.
  • display device 45 may be used to present video data.
  • Processing circuit 46 may include application-specific integrated circuit (ASIC) logic, a graphics processor, a general purpose processor, etc.
  • Video decoding system 40 may also include an optional processor 43, which may similarly include application-specific integrated circuit (ASIC) logic, a graphics processor, a general purpose processor, etc.
  • memory storage 44 may be any type of memory, such as volatile memory (e.g., static random access memory (SRAM), dynamic random access memory (DRAM), etc.) or non-volatile memory (e.g., flash memory, etc.).
  • memory storage 44 may be implemented by a cache memory.
  • processing circuit 46 may include a memory (e.g., a cache, etc.) for implementing an image buffer, etc.
  • the video encoder 20 implemented by logic circuits may include an image buffer (e.g., implemented by processing circuits 46 or memory storage 44) and a graphics processing unit (e.g., implemented by processing circuits 46).
  • the graphics processing unit may be communicatively coupled to the image buffer.
  • the graphics processing unit may include the video encoder 20 implemented by processing circuits 46 to implement the various modules discussed with reference to FIG. 2 and/or any other encoder system or subsystem described herein.
  • Logic circuits may be used to perform the various operations discussed herein.
  • the video decoder 30 may be implemented by the processing circuit 46 in a similar manner to implement the various modules discussed with reference to the video decoder 30 of FIG. 3 and/or any other decoder system or subsystem described herein.
  • the video decoder 30 implemented by the logic circuit may include an image buffer (implemented by the processing circuit 46 or the memory storage 44) and a graphics processing unit (implemented by the processing circuit 46, for example).
  • the graphics processing unit may be communicatively coupled to the image buffer.
  • the graphics processing unit may include the video decoder 30 implemented by the processing circuit 46 to implement the various modules discussed with reference to FIG. 3 and/or any other decoder system or subsystem described herein.
  • antenna 42 may be used to receive an encoded bitstream of video data.
  • the encoded bitstream may include data related to the encoded video frames discussed herein, indicators, index values, mode selection data, etc., such as data related to the encoded partitions (e.g., transform coefficients or quantized transform coefficients, (as discussed) optional indicators, and/or data defining the encoded partitions).
  • Video decoding system 40 may also include video decoder 30 coupled to antenna 42 and used to decode the encoded bitstream.
  • Display device 45 is used to present the video frames.
  • the video decoder 30 can be used to perform the reverse process. With respect to the signaling syntax elements, the video decoder 30 can be used to receive and parse such syntax elements and decode the related video data accordingly. In some examples, the video encoder 20 can entropy encode the syntax elements into an encoded video bitstream. In such examples, the video decoder 30 can parse such syntax elements and decode the related video data accordingly.
  • VVC universal video coding
  • HEVC high-efficiency video coding
  • JCT-VC video coding experts group
  • MPEG ISO/IEC motion picture experts group
  • the video encoder 20 includes an input end (or input interface) 201, a residual calculation unit 204, a transform processing unit 206, a quantization unit 208, an inverse quantization unit 210, an inverse transform processing unit 212, a reconstruction unit 214, a loop filter 220, a decoded picture buffer (DPB) 230, a mode selection unit 260, an entropy coding unit 270 and an output end (or output interface) 272.
  • Mode selection unit 260 may include inter prediction unit 244, intra prediction unit 254, and segmentation unit 262.
  • Inter prediction unit 244 may include a motion estimation unit and a motion compensation unit (not shown).
  • Video encoder 20 shown in FIG. 2 may also be referred to as a hybrid video encoder or a video encoder based on a hybrid video codec.
  • the inter-frame prediction unit is a trained target model (also called a neural network) that is used to process an input image or image region or image block to generate a prediction value of the input image block.
  • the neural network for inter-frame prediction is used to receive an input image or image region or image block and generate a prediction value of the input image or image region or image block.
  • the residual calculation unit 204, the transform processing unit 206, the quantization unit 208 and the mode selection unit 260 constitute the forward signal path of the encoder 20, while the inverse quantization unit 210, the inverse transform processing unit 212, the reconstruction unit 214, the buffer 216, the loop filter 220, the decoded picture buffer (DPB) 230, the inter-frame prediction unit 244 and the intra-frame prediction unit 254 constitute the backward signal path of the encoder, wherein the backward signal path of the encoder 20 corresponds to the signal path of the decoder (see the decoder 30 in FIG. 3).
  • the inverse quantization unit 210, the inverse transform processing unit 212, the reconstruction unit 214, the loop filter 220, the decoded picture buffer 230, the inter-frame prediction unit 244 and the intra-frame prediction unit 254 also constitute the "built-in decoder" of the video encoder 20.
  • the encoder 20 may be configured to receive, via an input 201 or the like, an image (or image data) 17, e.g., an image in a sequence of images forming a video or a video sequence.
  • the received image or image data may also be a pre-processed image (or pre-processed image data) 19.
  • image 17 may also be referred to as a current image or an image to be encoded (particularly when the current image is to be distinguished from other images in video encoding, such as previously encoded images and/or decoded images in the same video sequence, i.e., a video sequence also including the current image).
  • a (digital) image is or can be considered as a two-dimensional array or matrix of pixels with intensity values.
  • the pixels in the array can also be called pixels (pixel or pel) (short for picture elements).
  • the number of pixels in the array or image in the horizontal and vertical directions (or axes) determines the size and/or resolution of the image.
  • three color components are usually used, that is, the image can be represented as or include three pixel arrays.
  • the image includes corresponding red, green and blue pixel arrays.
  • each pixel is usually represented in a brightness/chrominance format or color space, such as YCbCr, including a brightness component indicated by Y (sometimes also represented by L) and two chrominance components represented by Cb and Cr.
  • the brightness (luma) component Y represents the brightness or grayscale level intensity (for example, the two are the same in grayscale images), while the two chrominance (abbreviated as chroma) components Cb and Cr represent the chrominance or color information components.
  • an image in YCbCr format includes a luminance pixel array of luminance pixel values (Y) and two chrominance pixel arrays of chrominance values (Cb and Cr).
  • RGB format An image in RGB format can be converted or transformed into YCbCr format and vice versa, a process also referred to as color conversion or conversion. If the image is black and white, the image may include only a luminance pixel array. Accordingly, the image may be, for example, a luminance pixel array in a monochrome format or a luminance pixel array and two corresponding chrominance pixel arrays in 4:2:0, 4:2:2 and 4:4:4 color formats.
  • an embodiment of the video encoder 20 may include an image segmentation unit (not shown in FIG. 2 ) for segmenting the image 17 into a plurality of (typically non-overlapping) image blocks 203. These blocks may also be referred to as root blocks, macroblocks (H.264/AVC) or coding tree blocks (CTBs), or coding tree units (CTUs) in the H.265/HEVC and VVC standards.
  • the segmentation unit may be used to use the same block size for all images in a video sequence and a corresponding grid of defined block sizes, or to vary the block size between images or subsets or groups of images, and to segment each image into corresponding blocks.
  • the video encoder may be configured to directly receive a block 203 of the image 17, for example, one, several or all blocks constituting the image 17.
  • the image block 203 may also be referred to as a current image block or an image block to be encoded.
  • image block 203 is also or can be considered as a two-dimensional array or matrix composed of pixels with intensity values (pixel values), but image block 203 is smaller than image 17.
  • block 203 may include one pixel array (e.g., a brightness array in the case of monochrome image 17 or a brightness array or chrominance array in the case of a color image) or three pixel arrays (e.g., one brightness array and two chrominance arrays in the case of a color image 17) or any other number and/or type of arrays according to the color format adopted.
  • the number of pixels in the horizontal and vertical directions (or axes) of block 203 defines the size of block 203. Accordingly, the block can be an M ⁇ N (M columns ⁇ N rows) pixel array, or an M ⁇ N transform coefficient array, etc.
  • the video encoder 20 shown in FIG. 2 is used to encode the image 17 block by block, for example, encoding and prediction are performed on each block 203 .
  • the video encoder 20 shown in FIG. 2 may also be used to partition and/or encode an image using slices (also referred to as video slices), wherein an image may be partitioned or encoded using one or more slices (usually non-overlapping).
  • slices also referred to as video slices
  • Each slice may include one or more blocks (e.g., coding tree units CTUs) or one or more block groups (e.g., coding tiles in the H.265/HEVC/VVC standard and bricks in the VVC standard).
  • the video encoder 20 shown in Figure 2 can also be used to segment and/or encode an image using slices/coding block groups (also called video coding block groups) and/or coding blocks (also called video coding blocks), wherein the image can be segmented or encoded using one or more slices/coding block groups (usually non-overlapping), each slice/coding block group may include one or more blocks (e.g., CTU) or one or more coding blocks, etc., wherein each coding block may be in a rectangular shape, etc., and may include one or more complete or partial blocks (e.g., CTU).
  • slices/coding block groups also called video coding block groups
  • coding blocks also called video coding blocks
  • each slice/coding block group may include one or more blocks (e.g., CTU) or one or more coding blocks, etc., wherein each coding block may be in a rectangular shape, etc., and may include one or more complete or partial blocks (e.g., CTU).
  • the residual calculation unit 204 is used to calculate the residual block 205 (the prediction block 265 is described in detail later) based on the image block (or original block) 203 and the prediction block 265 in the following manner: for example, the pixel value of the prediction block 265 is subtracted from the pixel value of the image block 203 pixel by pixel (pixel by pixel) to obtain the residual block 205 in the pixel domain.
  • the transform processing unit 206 is used to perform discrete cosine transform (DCT) or discrete sine transform (DST) on the pixel values of the residual block 205 to obtain a transform coefficient 207 in the transform domain.
  • the transform coefficient 207 may also be called a transform residual coefficient, which represents the residual block 205 in the transform domain.
  • the transform processing unit 206 may be used to apply an integerized approximation of the DCT/DST, such as the transform specified for H.265/HEVC.
  • This integerized approximation is typically scaled by a factor compared to an orthogonal DCT transform.
  • other scaling factors are used as part of the transform process.
  • the scaling factor is typically selected based on certain constraints, such as whether the scaling factor is a power of 2 for the shift operation, the bit depth of the transform coefficients, a trade-off between accuracy and implementation cost, etc.
  • a specific scaling factor is specified for the inverse transform on the encoder 20 side by the inverse transform processing unit 212 (and for the corresponding inverse transform on the decoder 30 side by, for example, the inverse transform processing unit 312), and correspondingly, a corresponding scaling factor may be specified for the forward transform on the encoder 20 side by the transform processing unit 206.
  • the video encoder 20 (correspondingly, the transform processing unit 206) may be used to output transform parameters such as one or more transform types, for example, directly output or output after encoding or compression by the entropy coding unit 270, for example, so that the video decoder 30 may receive and use the transform parameters for decoding.
  • transform parameters such as one or more transform types, for example, directly output or output after encoding or compression by the entropy coding unit 270, for example, so that the video decoder 30 may receive and use the transform parameters for decoding.
  • the quantization unit 208 is used to quantize the transform coefficient 207 by, for example, scalar quantization or vector quantization to obtain a quantized transform coefficient 209 .
  • the quantized transform coefficient 209 may also be referred to as a quantized residual coefficient 209 .
  • the quantization process may reduce the bit depth associated with some or all of the transform coefficients 207. For example, an n-bit transform coefficient may be rounded down to an m-bit transform coefficient during quantization, where n is greater than m.
  • the degree of quantization may be modified by adjusting a quantization parameter (QP). For example, for scalar quantization, different degrees of scaling may 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.
  • a suitable quantization step size may be indicated by a quantization parameter (QP).
  • a quantization parameter may be an index of a predefined set of suitable quantization step sizes.
  • Quantization may include dividing by a quantization step size, while a corresponding or inverse dequantization performed by the inverse quantization unit 210 or the like may include multiplying by a quantization step size.
  • Embodiments according to some standards, such as HEVC may be used to determine the quantization step size using a quantization parameter.
  • the quantization step size may be calculated using a fixed-point approximation of an equation involving division according to the quantization parameter.
  • scaling factors may be introduced for quantization and dequantization to recover the norm of the residual block that may be modified due to the scaling used in the fixed-point approximation of the equations for the quantization step size and the quantization parameter.
  • the scaling of the inverse transform and dequantization may be combined.
  • a custom quantization table may be used and indicated from the encoder to the decoder in the bitstream, etc.
  • Quantization is a lossy operation, where the larger the quantization step size, the greater the loss.
  • the video encoder 20 may be used to output a quantization parameter (QP), for example, directly output or output after being encoded or compressed by the entropy coding unit 270, such that the video decoder 30 may receive and use the quantization parameter for decoding.
  • QP quantization parameter
  • the inverse quantization unit 210 is used to perform inverse quantization of the quantization unit 208 on the quantized coefficients to obtain dequantized coefficients 211, for example, performing an inverse quantization scheme of the quantization scheme performed by the quantization unit 208 according to or using the same quantization step size as the quantization unit 208.
  • the dequantized coefficients 211 may also be referred to as dequantized residual coefficients 211, corresponding to the transform coefficients 207, but due to the loss caused by quantization, the dequantized coefficients 211 are usually not completely the same as the transform coefficients.
  • the inverse transform processing unit 212 is used to perform an inverse transform of the transform performed by the transform processing unit 206, such as an inverse discrete cosine transform (DCT) or an inverse discrete sine transform (DST), to obtain a reconstructed residual in the pixel domain.
  • DCT inverse discrete cosine transform
  • DST inverse discrete sine transform
  • Block 213 (or the corresponding dequantized coefficients 213 ).
  • the reconstructed residual block 213 may also be referred to as a transformed block 213 .
  • the reconstruction unit 214 (e.g., the summer 214) is used to add the transform block 213 (i.e., the reconstructed residual block 213) to the prediction block 265 to obtain the reconstructed block 215 in the pixel domain, for example, by adding the pixel point values of the reconstructed residual block 213 and the pixel point values of the prediction block 265.
  • the loop filter unit 220 (or simply "loop filter” 220) is used to filter the reconstructed block 215 to obtain the filter block 221, or is generally used to filter the reconstructed pixel points to obtain the filtered pixel point value.
  • the loop filter unit is used to smoothly perform pixel conversion or improve video quality.
  • the loop filter unit 220 may include one or more loop filters, such as a deblocking filter, a sample-adaptive offset (SAO) filter, or one or more other filters, such as an adaptive loop filter (ALF), a noise suppression filter (NSF), or any combination.
  • the loop filter unit 220 may include a deblocking filter, an SAO filter, and an ALF filter.
  • the order of the filtering process may be a deblocking filter, an SAO filter, and an ALF filter.
  • a process called luma mapping with chroma scaling (LMCS) i.e., an adaptive in-loop shaper
  • LMCS luma mapping with chroma scaling
  • This process is performed before deblocking.
  • the deblocking filtering process may also be applied to internal sub-block edges, such as affine sub-block edges, ATMVP sub-block edges, sub-block transform (SBT) edges, and intra sub-partition (ISP) edges.
  • the loop filter unit 220 is shown as a loop filter in FIG. 2 , in other configurations, the loop filter unit 220 may be implemented as a post-loop filter.
  • the filter block 221 may also be referred to as a filter reconstruction block 221.
  • the video encoder 20 may be used to output loop filter parameters (e.g., SAO filter parameters, ALF filter parameters, or LMCS parameters), for example, directly or after being entropy encoded by the entropy encoding unit 270, such that the decoder 30 may receive and use the same or different loop filter parameters for decoding.
  • loop filter parameters e.g., SAO filter parameters, ALF filter parameters, or LMCS parameters
  • the decoded picture buffer (DPB) 230 may be a reference picture memory that stores reference picture data for use by the video encoder 20 when encoding video data.
  • the DPB 230 may be formed by any of a variety of memory devices, such as a dynamic random access memory (DRAM), including synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM), resistive RAM (RRAM), or other types of storage devices.
  • DRAM dynamic random access memory
  • SDRAM synchronous DRAM
  • MRAM magnetoresistive RAM
  • RRAM resistive RAM
  • the decoded picture buffer 230 may be used to store one or more filter blocks 221.
  • the decoded picture buffer 230 may also be used to store other previous filter blocks of the same current image or a different image such as a previous reconstructed image, such as a previously reconstructed and filtered block 221, and may provide a complete previously reconstructed, i.e., decoded image (and corresponding reference blocks and pixels) and/or a partially reconstructed current image (and corresponding reference blocks and pixels), such as for inter-frame prediction.
  • the decoded image buffer 230 may also be used to store one or more unfiltered reconstructed blocks 215, or generally to store unfiltered reconstructed pixels, for example, reconstructed blocks 215 that have not been filtered by the loop filter unit 220, or reconstructed blocks or reconstructed pixels that have not undergone any other processing.
  • the mode selection unit 260 includes a segmentation unit 262, an inter-frame prediction unit 244, and an intra-frame prediction unit 254, which are used to receive or obtain original image data such as an original block 203 (current block 203 of the current image 17) and reconstructed image data from the decoded image buffer 230 or other buffers (e.g., a column buffer, not shown in FIG. 2), such as filtered and/or unfiltered reconstructed pixels or reconstructed blocks of the same (current) image and/or one or more previously decoded images.
  • the reconstructed image data is used as reference image data required for prediction such as inter-frame prediction or intra-frame prediction to obtain a prediction block 265 or a prediction value 265.
  • the mode selection unit 260 may be used to determine or select a partition for the current block (including no partition) and prediction mode (eg, intra-frame or inter-frame prediction mode), generate a corresponding prediction block 265 , calculate the residual block 205 , and reconstruct the reconstruction block 215 .
  • prediction mode eg, intra-frame or inter-frame prediction mode
  • the mode selection unit 260 may be used to select a segmentation and prediction mode (e.g., from prediction modes supported or available by the mode selection unit 260) that provides the best match or minimum residual (minimum residual means better compression in transmission or storage), or provides minimum signaling overhead (minimum signaling overhead means better compression in transmission or storage), or considers or balances both of the above.
  • the mode selection unit 260 may be used to determine the segmentation and prediction mode based on rate distortion optimization (RDO), that is, select the prediction mode that provides minimum rate distortion optimization.
  • RDO rate distortion optimization
  • the partitioning unit 262 may be used to partition a picture in a video sequence into a sequence of coding tree units (CTUs), and the CTU 203 may be further partitioned into smaller block portions or sub-blocks (again forming blocks), for example, by iteratively using quad-tree partitioning (QT), binary-tree partitioning (BT) or triple-tree partitioning (TT). Partitioning or any combination thereof, and for performing prediction on each of the block parts or sub-blocks, for example, wherein mode selection includes selecting a tree structure of the partitioned blocks 203 and selecting a prediction mode to be applied to each of the block parts or sub-blocks.
  • QT quad-tree partitioning
  • BT binary-tree partitioning
  • TT triple-tree partitioning
  • segmentation eg, performed by segmentation unit 262
  • prediction processes eg, performed by inter-prediction unit 244 and intra-prediction unit 254
  • the segmentation unit 262 may segment (or divide) an image block (or CTU) 203 into smaller parts, such as small blocks of square or rectangular shape.
  • a CTU consists of N ⁇ N luminance pixel blocks and two corresponding chrominance pixel blocks.
  • the maximum allowed size of a luminance block in a CTU is specified as 128 ⁇ 128 in the developing universal video coding (VVC) standard, but may be specified as a value different from 128 ⁇ 128 in the future, such as 256 ⁇ 256.
  • VVC developing universal video coding
  • the CTUs of an image may be concentrated/grouped into slices/coding block groups, coding blocks, or bricks.
  • a coding block covers a rectangular area of an image, and a coding block may be divided into one or more bricks.
  • a brick consists of multiple CTU rows within a coding block.
  • a coding block that is not segmented into multiple bricks may be called a brick.
  • a brick is a true subset of a coding block and is therefore not called a coding block.
  • VVC supports two coding block group modes, namely raster scan slice/coding block group mode and rectangular slice mode.
  • raster scan CBG mode a slice/CBG contains a sequence of CBs in a raster scan of CBs of an image.
  • rectangular slice mode a slice contains multiple bricks of an image, which together form a rectangular region of the image. The bricks within a rectangular slice are arranged in the order of the bricks in the slice's raster scan.
  • These smaller blocks can be further split into smaller parts.
  • This is also called tree partitioning or hierarchical tree partitioning, where a root block at root tree level 0 (hierarchy level 0, depth 0), etc., can be recursively split into two or more blocks at the next lower tree level, such as nodes at tree level 1 (hierarchy level 1, depth 1).
  • These blocks can be split into two or more blocks at the next lower level, such as tree level 2 (hierarchy level 2, depth 2), etc., until the partitioning ends (because the end criteria are met, such as reaching the maximum tree depth or minimum block size).
  • Blocks that are not further partitioned are also called leaf blocks or leaf nodes of the tree.
  • a tree divided into two parts is called a binary tree (BT)
  • TT ternary tree
  • QT quadtree
  • a coding tree unit may be or include a CTB of luma pixels, two corresponding CTBs of chroma pixels of an image with three pixel arrays, or a CTB of pixels of a monochrome image, or a CTB of pixels of an image encoded using three independent color planes and syntax structures (for encoding pixels).
  • a coding tree block may be an N ⁇ N pixel block, where N may be set to a value such that the component is divided into CTBs, which is segmentation.
  • a coding unit may be or include a coding block of luma pixels, two corresponding coding blocks of chroma pixels of an image with three pixel arrays, or a coding block of pixels of a monochrome image, or a coding block of pixels of an image encoded using three independent color planes and syntax structures (for encoding pixels).
  • a coding block may be an M ⁇ N pixel block, where M and N may be set to a value such that the CTB is divided into coding blocks, which is segmentation.
  • a coding tree unit may be divided into multiple CUs using a quadtree structure represented as a coding tree.
  • a decision is made at the leaf-CU level whether to use inter-frame (temporal) prediction or intra-frame (spatial) prediction to encode an image area.
  • Each leaf-CU may be further divided into one, two, or four PUs according to the PU partition type. The same prediction process is used within a PU, and relevant information is transmitted to the decoder in units of PUs. After the prediction process is applied according to the PU partition type to obtain the residual block, the leaf-CU may be partitioned into transform units (TUs) according to other quadtree structures similar to the coding tree for the CU.
  • transform units TUs
  • VVC Versatile Video Coding
  • a segment structure for segmenting a coding tree unit is partitioned using a combined quadtree of nested multi-type trees (e.g., binary and ternary trees).
  • the CU may be square or rectangular.
  • a coding tree unit (CTU) is first segmented by a quadtree structure.
  • the quadtree leaf nodes are further segmented by a multi-type tree structure.
  • the multi-type tree structure has four types of segmentation: vertical binary tree segmentation (SPLIT_BT_VER), horizontal binary tree segmentation (SPLIT_BT_HOR), vertical ternary tree segmentation (SPLIT_TT_VER), and horizontal ternary tree segmentation (SPLIT_TT_HOR).
  • the multi-type leaf nodes are called coding units (CUs), and unless the CU is too large for the maximum transform length, such segmentation is used for prediction and transform processing without any other segmentation. In most cases, this means that the block sizes of CU, PU, and TU in the coding block structure of the quadtree nested multi-type tree are the same.
  • VVC has developed a unique signaling mechanism for segmentation information in a coding structure with a quadtree nested multi-type tree.
  • the signaling mechanism the coding tree unit (CTU) is first split by the quadtree structure as the root of the quadtree. Then each quadtree leaf node (when large enough) is further split into a multi-type tree structure.
  • the first flag mtt_split_cu_flag is used to indicate whether the node is further split.
  • the decoder can derive the multi-type tree division mode (MttSplitMode) of the CU based on predefined rules or tables.
  • the 64 ⁇ 64 luma block and 32 ⁇ 32 chroma pipeline design in the hardware decoder does not allow TT splitting when the width or height of the luma coding block is greater than 64. TT splitting is also not allowed when the width or height of the chroma coding block is greater than 32.
  • the pipeline design divides the image into multiple virtual pipeline data units (VPDUs), and each VPDU is defined as a non-overlapping unit in the image.
  • VPDU size is roughly proportional to the buffer size, so it is necessary to keep the VPDU small.
  • the VPDU size can be set to the maximum transform block (TB) size.
  • TT ternary tree
  • BT binary tree
  • the tree node block is forcibly divided until all the pixels of each coding CU are located within the image boundary.
  • the intra sub-partitions (ISP) tool can divide the luma intra prediction block vertically or horizontally into two or four sub-partitions according to the block size.
  • mode select unit 260 of video encoder 20 may be used to perform any combination of the segmentation techniques described above.
  • the video encoder 20 is operable to determine or select the best or optimal prediction mode from a (predetermined) set of prediction modes.
  • the set of prediction modes may include, for example, an intra prediction mode and/or an inter prediction mode.
  • the intra prediction mode set may include 35 different intra prediction modes, for example, non-directional modes like DC (or mean) mode and planar mode, or directional modes as defined in HEVC, or may include 67 different intra prediction modes, for example, non-directional modes like DC (or mean) mode and planar mode, or directional modes as defined in VVC.
  • non-directional modes like DC (or mean) mode and planar mode, or directional modes as defined in VVC.
  • several traditional angle intra prediction modes are adaptively replaced with wide-angle intra prediction modes for non-square blocks defined in VVC.
  • the intra prediction result of the planar mode can also be modified using the position dependent intra prediction combination (PDPC) method.
  • PDPC position dependent intra prediction combination
  • the intra prediction unit 254 is configured to generate an intra prediction block 265 by reconstructing pixels in adjacent blocks of the same current image according to an intra prediction mode in the intra prediction mode set.
  • the intra-frame prediction unit 254 (or generally the mode selection unit 260) is also used to output intra-frame prediction parameters (or generally information indicating the selected intra-frame prediction mode of the block) in the form of syntax elements 266 to the entropy coding unit 270 for inclusion in the encoded image data 21, so that the video decoder 30 can perform operations, such as receiving and using the prediction parameters for decoding.
  • the intra prediction modes in HEVC include DC prediction mode, plane prediction mode and 33 angle prediction modes, with a total of 35 candidate prediction modes.
  • the current block can use the pixels of the reconstructed image blocks on the left and above as references for intra prediction.
  • the image blocks in the surrounding area of the current block used for intra prediction of the current block are called reference blocks, and the pixels in the reference blocks are called reference pixels.
  • the DC prediction mode is applicable to the area with flat texture in the current block, and all pixels in this area use the average value of the reference pixels in the reference block as prediction;
  • the plane prediction mode is applicable to image blocks with smoothly changing textures.
  • the current block that meets this condition uses the reference pixels in the reference block for bilinear interpolation as the prediction of all pixels in the current block; the angle prediction mode uses the characteristics that the texture of the current block is highly correlated with the texture of the adjacent reconstructed image block, and copies the values of the reference pixels in the corresponding reference block along a certain angle as the prediction of all pixels in the current block.
  • the HEVC encoder selects an optimal intra-frame prediction mode for the current block from 35 candidate prediction modes and writes the optimal intra-frame prediction mode into the video bitstream.
  • the encoder/decoder derives three most likely modes from the optimal intra-frame prediction modes of the reconstructed image blocks in the surrounding area using intra-frame prediction.
  • a first index is encoded to indicate that the selected optimal intra-frame prediction mode is one of the three most likely modes; if the selected optimal intra-frame prediction mode is not one of the three most likely modes, a second index is encoded to indicate that the selected optimal intra-frame prediction mode is one of the other 32 modes (other modes among the 35 candidate prediction modes except the aforementioned three most likely modes).
  • the HEVC standard uses a 5-bit fixed-length code as the aforementioned second index.
  • the method by which the HEVC encoder derives the three most likely modes includes: selecting the optimal intra-frame prediction modes of the left adjacent image block and the upper adjacent image block of the current block and putting them into a set. If the two optimal intra-frame prediction modes are the same, only one is retained in the set. If the two optimal intra-frame prediction modes are the same and both are angle prediction modes, two angle prediction modes adjacent to the angle direction are selected to be added to the set; otherwise, the plane prediction mode, the DC mode, and the vertical prediction mode are selected in turn to be added to the set until the number of modes in the set reaches 3.
  • the HEVC decoder After the HEVC decoder performs entropy decoding on the bitstream, it obtains the mode information of the current block, which includes an indication flag indicating whether the optimal intra-frame prediction mode of the current block is among the three most likely modes, and the index of the optimal intra-frame prediction mode of the current block among the three most likely modes or the index of the optimal intra-frame prediction mode of the current block among the other 32 modes.
  • the set of inter-frame prediction modes depends on the available reference image (i.e., at least part of the previously decoded image stored in DBP 230 as mentioned above) and other inter-frame prediction parameters, for example, on whether to use the entire reference image or only a part of the reference image, such as a search window area near the area of the current block, to search for the best matching reference block, and/or on whether to perform pixel interpolation such as half-pixel, quarter-pixel and/or 16th interpolation, for example.
  • the available reference image i.e., at least part of the previously decoded image stored in DBP 230 as mentioned above
  • other inter-frame prediction parameters for example, on whether to use the entire reference image or only a part of the reference image, such as a search window area near the area of the current block, to search for the best matching reference block, and/or on whether to perform pixel interpolation such as half-pixel, quarter-pixel and/or 16th interpolation, for example.
  • skip mode and/or direct mode may also be employed.
  • the merge candidate list of this mode consists of the following five candidate types in order: spatial MVP from spatial neighboring CU, temporal MVP from collocated CU, history-based MVP from FIFO table, pairwise average MVP and zero MV.
  • Decoder side motion vector refinement (DMVR) based on bilateral matching can be used to increase the accuracy of MV in merge mode.
  • Merge mode with MVD (MMVD) is derived from merge mode with motion vector difference. The MMVD flag is sent immediately after the skip flag and merge flag are sent to specify whether the CU uses MMVD mode.
  • the CU-level adaptive motion vector resolution (AMVR) scheme can be used. AMVR supports the MVD of the CU to be encoded with different precisions.
  • the MVD of the current CU is adaptively selected according to the prediction mode of the current CU.
  • the combined inter/intra prediction (CIIP) mode can be applied to the current CU.
  • the CIIP prediction is obtained by weighted averaging the inter- and intra-prediction signals.
  • the affine motion field of the block is described by the motion information of 2 control points (4 parameters) or 3 control points (6 parameters) motion vectors.
  • Subblock-based temporal motion vector prediction (SbTMVP) is similar to temporal motion vector prediction (TMVP) in HEVC, but predicts the motion vector of the sub-CU within the current CU.
  • Bidirectional optical flow (BDOF), formerly known as BIO, is a simplified version that reduces calculations, especially in terms of the number of multiplications and the size of the multipliers.
  • BDOF Bidirectional optical flow
  • the CU In triangle partitioning mode, the CU is evenly divided into two triangular parts in two ways: diagonal partitioning and anti-diagonal partitioning.
  • the bidirectional prediction mode is extended on the basis of simple averaging to support weighted averaging of two prediction signals.
  • the inter-frame prediction unit 244 may include a motion estimation (ME) unit and a motion compensation (MC) unit (both not shown in FIG. 2 ).
  • the motion estimation unit may be used to receive or obtain an image block 203 (a current image block 203 of a current image 17) and a decoded image 231, or at least one or more previously reconstructed blocks, for example, reconstructed blocks of one or more other/different previously decoded images 231, for motion estimation.
  • a video sequence may include a current image and a previously decoded image 231, or in other words, the current image and the previously decoded image 231 may be part of or form a sequence of images forming the video sequence.
  • the encoder 20 may be configured to select a reference block from a plurality of reference blocks of the same or different images in a plurality of other images, and provide the reference image (or reference image index) and/or the offset (spatial offset) between the position (x, y coordinates) of the reference block and the position of the current block as an inter-frame prediction parameter to the motion estimation unit.
  • the offset is also referred to as a motion vector (MV).
  • the motion compensation unit is used to obtain, for example, receive, inter-frame prediction parameters, and perform inter-frame prediction based on or using the inter-frame prediction parameters to obtain an inter-frame prediction block 246.
  • the motion compensation performed by the motion compensation unit may include extracting or generating a prediction block based on a motion/block vector determined by motion estimation, and may also include performing interpolation with sub-pixel accuracy. Interpolation filtering can generate pixel points of other pixels from pixel points of known pixels, thereby potentially increasing the number of candidate prediction blocks that can be used to encode the image block.
  • the motion compensation unit can locate the prediction block pointed to by the motion vector in one of the reference image lists.
  • the motion compensation unit may also generate syntax elements associated with blocks and video slices for use by the video decoder 30 when decoding image blocks of the video slice.
  • syntax elements associated with blocks and video slices for use by the video decoder 30 when decoding image blocks of the video slice.
  • coding block groups and/or coding blocks and corresponding syntax elements may be generated or used.
  • motion vectors (MVs) that can be added to the candidate motion vector list as alternatives include MVs of spatially adjacent and temporally adjacent image blocks of the current block, wherein the MVs of spatially adjacent image blocks can include MVs of left candidate image blocks located on the left side of the current block and MVs of upper candidate image blocks located above the current block.
  • FIG. 4 is an exemplary schematic diagram of candidate image blocks provided in an embodiment of the present application. As shown in FIG.
  • the set of left candidate image blocks includes ⁇ A0, A1 ⁇
  • the set of upper candidate image blocks includes ⁇ B0, B1, B2 ⁇
  • the set of temporally adjacent candidate image blocks includes ⁇ C, T ⁇ . All three sets can be added to the candidate motion vector list as alternatives.
  • the maximum length of the candidate motion vector list of AMVP is 2, so it is necessary to determine the MVs of up to two image blocks to be added to the candidate motion vector list from the three sets according to the prescribed order.
  • the order may be to give priority to the set of candidate image blocks to the left of the current block ⁇ A0, A1 ⁇ (consider A0 first, and consider A1 if A0 is not available), then consider the set of candidate image blocks above the current block ⁇ B0, B1, B2 ⁇ (consider B0 first, and consider B1 if B0 is not available, and consider B2 if B1 is not available), and finally consider the set of candidate image blocks adjacent to the current block in the time domain ⁇ C, T ⁇ (consider T first, and consider C if T is not available).
  • the rate distortion cost (RD cost) is used to select the candidate motion vector from the candidate motion vector list.
  • the optimal MV is determined in the above formula, and the candidate motion vector with the smallest RD cost is used as the motion vector predictor (MVP) of the current block.
  • J represents RD cost
  • SAD is the sum of absolute differences (SAD) between the pixel value of the predicted block obtained after motion estimation using the candidate motion vector and the pixel value of the current block
  • R represents the bit rate
  • ⁇ represents the Lagrange multiplier
  • the encoder passes the index of the determined MVP in the candidate motion vector list to the decoder. Furthermore, a motion search can be performed in the neighborhood centered on the MVP to obtain the actual motion vector of the current block.
  • the encoder calculates the motion vector difference (MVD) between the MVP and the actual motion vector, and also passes the MVD to the decoder.
  • the decoder parses the index, finds the corresponding MVP in the candidate motion vector list based on the index, parses the MVD, and adds the MVD to the MVP to obtain the actual motion vector of the current block.
  • the motion information that can be added to the candidate motion information list as an alternative includes the motion information of the image blocks adjacent to the current block in the spatial domain or in the temporal domain, wherein the image blocks adjacent to the spatial domain and the image blocks adjacent to the temporal domain can refer to FIG. 4.
  • the candidate motion information corresponding to the spatial domain in the candidate motion information list comes from the five spatially adjacent blocks (A0, A1, B0, B1 and B2). If the spatially adjacent block is not available or is intra-predicted, its motion information is not added to the candidate motion information list.
  • the candidate motion information in the temporal domain of the current block is obtained by scaling the MV of the block at the corresponding position in the reference frame according to the picture order count (POC) of the reference frame and the current frame. First, it is determined whether the block at position T in the reference frame is available. If not, the block at position C is selected. After obtaining the above candidate motion information list, the optimal motion information is determined from the candidate motion information list through RD cost as the motion information of the current block. The encoder transmits the index value of the position of the optimal motion information in the candidate motion information list (referred to as merge index) to the decoder.
  • merge index the index value of the position of the optimal motion information in the candidate motion information list
  • the entropy coding unit 270 is used to apply an entropy coding algorithm or scheme (for example, a variable length coding (VLC) scheme, a context adaptive VLC scheme (CALVC), an arithmetic coding scheme, a binarization algorithm, context adaptive binary arithmetic coding (CABAC), syntax-based context-adaptive binary arithmetic coding (SBAC), probability interval partitioning entropy (PIPE) coding or other entropy coding methods or techniques) to the quantized residual coefficients 209, inter-frame prediction parameters, intra-frame prediction parameters, loop filter parameters and/or other syntax elements to obtain the encoded image data 21 that can be output through the output terminal 272 in the form of an encoded bit stream 21, etc., so that the video decoder 30, etc. can receive and use the parameters for decoding.
  • the encoded bitstream 21 may be transmitted to the video decoder 30 , or stored in memory for later transmission or retrieval by the video decoder 30 .
  • a non-transform based encoder 20 may directly quantize the residual signal without a transform processing unit 206 for certain blocks or frames.
  • the encoder 20 may have a quantization unit 208 and an inverse quantization unit 210 combined into a single unit.
  • the video decoder 30 is used to receive the coded image data 21 (e.g., the coded bitstream 21) encoded by the encoder 20, and obtain a decoded image 331.
  • the coded image data or bitstream includes information for decoding the coded image data, such as data representing image blocks of a coded video slice (and/or a coding block group or coding block) and related syntax elements.
  • decoder 30 includes an entropy decoding unit 304, an inverse quantization unit 310, an inverse transform processing unit 312, a reconstruction unit 314 (e.g., summer 314), a loop filter 320, a decoded picture buffer (DBP) 330, a mode application unit 360, an inter-prediction unit 344, and an intra-prediction unit 354.
  • Inter-prediction unit 344 may be or include a motion compensation unit.
  • video decoder 30 may perform a decoding process that is generally the opposite of the encoding process described with reference to video encoder 100 of FIG. 2.
  • inverse quantization unit 210 may be functionally identical to inverse quantization unit 110
  • inverse transform processing unit 312 may be functionally identical to inverse transform processing unit 122
  • reconstruction unit 314 may be functionally identical to reconstruction unit 214
  • loop filter 320 may be functionally identical to loop filter 220
  • decoded picture buffer 330 may be functionally identical to decoded picture buffer 230. Therefore, the explanation of the corresponding units and functions of video encoder 20 applies accordingly to the corresponding units and functions of video decoder 30.
  • the entropy decoding unit 304 is used to parse the bit stream 21 (or generally the encoded image data 21) and perform entropy decoding on the encoded image data 21 to obtain quantization coefficients 309 and/or decoded encoding parameters (not shown in FIG. 3), such as any one or all of inter-frame prediction parameters (such as reference image index and motion vector), intra-frame prediction parameters (such as intra-frame prediction mode or index), transform parameters, quantization parameters, loop filter parameters and/or other syntax elements.
  • the entropy decoding unit 304 can be used to apply the encoding scheme of the entropy encoding unit 270 of the encoder 20 to the encoded image data 21.
  • the entropy decoding unit 304 may also be used to provide inter-frame prediction parameters, intra-frame prediction parameters and/or other syntax elements to the mode application unit 360, and to provide other parameters to other units of the decoder 30.
  • the video decoder 30 may receive syntax elements at the video slice and/or video block level. In addition, or as an alternative to slices and corresponding syntax elements, coding block groups and/or coding blocks and corresponding syntax elements may be received or used.
  • the inverse quantization unit 310 may be configured to receive a quantization parameter (QP) (or generally information related to inverse quantization) and a quantization coefficient from the encoded image data 21 (e.g., parsed and/or decoded by the entropy decoding unit 304), and to inverse quantize the decoded quantization coefficient 309 based on the quantization parameter to obtain an inverse quantization coefficient 311, which may also be referred to as a transform coefficient 311.
  • the inverse quantization process may include using the quantization parameter calculated by the video encoder 20 for each video block in the video slice to determine a degree of quantization, and also determine a degree of inverse quantization that needs to be performed.
  • the inverse transform processing unit 312 may be configured to receive the dequantized coefficients 311, also referred to as transform coefficients 311, and apply a transform to the dequantized coefficients 311 to obtain a reconstructed residual block 213 in the pixel domain.
  • the reconstructed residual block 213 may also be referred to as a transform block 313.
  • the transform may be an inverse transform, such as an inverse DCT, an inverse DST, an inverse integer transform, or a conceptually similar inverse transform process.
  • the inverse transform processing unit 312 may also be configured to receive transform parameters or corresponding information from the encoded image data 21 (e.g., parsed and/or decoded by the entropy decoding unit 304) to determine the transform applied to the dequantized coefficients 311.
  • the reconstruction unit 314 (eg, the summer 314 ) is used to add the reconstructed residual block 313 to the prediction block 365 to obtain the reconstructed block 315 in the pixel domain, for example, by adding the pixel point values of the reconstructed residual block 313 and the pixel point values of the prediction block 365 .
  • the loop filter unit 320 (in or after the encoding loop) is used to filter the reconstruction block 315 to obtain a filter block 321, so as to smoothly perform pixel conversion or improve video quality.
  • the loop filter unit 320 may include one or more loop filters, such as a deblocking filter, a sample-adaptive offset (SAO) filter, or one or more other filters, such as an adaptive loop filter (ALF), a noise suppression filter (NSF), or any combination.
  • the loop filter unit 220 may include a deblocking filter, an SAO filter, and an ALF filter.
  • the order of the filtering process may be a deblocking filter, an SAO filter, and an ALF filter.
  • LMCS luma mapping with chroma scaling
  • SBT sub-block transform
  • ISP intra sub-partition
  • the decoded video blocks 321 in one picture are then stored in a decoded picture buffer 330 which stores the decoded pictures 331 as reference pictures for subsequent motion compensation of other pictures and/or for respective output display.
  • the decoder 30 is used to output the decoded image 311 through the output terminal 312, etc., to be displayed to the user or for the user to view.
  • the inter-frame prediction unit 344 may be functionally the same as the inter-frame prediction unit 244 (particularly the motion compensation unit), and the intra-frame prediction unit 354 may be functionally the same as the inter-frame prediction unit 254, and may determine the division or segmentation and perform prediction based on the segmentation and/or prediction parameters or corresponding information received from the coded image data 21 (e.g., parsed and/or decoded by the entropy decoding unit 304).
  • the mode application unit 360 may be used to perform prediction (intra-frame or inter-frame prediction) of each block according to the reconstructed image, block or corresponding pixel point (filtered or unfiltered), and obtain a prediction block 365.
  • the intra prediction unit 354 in the mode application unit 360 is used to generate a prediction block 365 for the image block of the current video slice based on the indicated intra prediction mode and data from a previously decoded block of the current image.
  • the inter prediction unit 344 e.g., a motion compensation unit
  • the mode application unit 360 is used to generate a prediction block 365 for the video block of the current video slice based on the motion vector and other syntax elements received from the entropy decoding unit 304.
  • these prediction blocks can be generated from one of the reference images in one of the reference image lists.
  • the video decoder 30 can construct reference frame list 0 and list 1 using a default construction technique based on the reference images stored in the DPB 330.
  • the same or similar processes may be applied to embodiments of coding block groups (e.g., video coding block groups) and/or coding blocks (e.g., video coding blocks) in addition to or as an alternative to slices (e.g., video slices), for example, a video may be encoded using I, P or B coding block groups and/or coding blocks.
  • the mode application unit 360 is used to determine prediction information for a video block of a current video slice by parsing motion vectors and other syntax elements. And use the prediction information to generate a prediction block for the current video block being decoded. For example, the mode application unit 360 uses some of the received syntax elements to determine the prediction mode (e.g., intra-frame prediction or inter-frame prediction) for encoding the video block of the video slice, the inter-frame prediction slice type (e.g., B slice, P slice, or GPB slice), construction information of one or more reference image lists for the slice, motion vectors for each inter-frame coded video block for the slice, inter-frame prediction status for each inter-frame coded video block for the slice, and other information to decode the video block within the current video slice.
  • the prediction mode e.g., intra-frame prediction or inter-frame prediction
  • the inter-frame prediction slice type e.g., B slice, P slice, or GPB slice
  • construction information of one or more reference image lists for the slice motion vectors for each inter
  • coding block groups e.g., video coding block groups
  • coding blocks e.g., video coding blocks
  • a video can be encoded using I, P, or B coding block groups and/or coding blocks.
  • the video encoder 30 of FIG. 3 may also be used to segment and/or decode an image using slices (also referred to as video slices), where an image may be segmented or decoded using one or more slices (usually non-overlapping).
  • slices also referred to as video slices
  • Each slice may include one or more blocks (e.g., CTUs) or one or more block groups (e.g., coding blocks in the H.265/HEVC/VVC standard and bricks in the VVC standard).
  • the video decoder 30 shown in Figure 3 can also be used to segment and/or decode an image using slices/coding block groups (also called video coding block groups) and/or coding blocks (also called video coding blocks), wherein the image can be segmented or decoded using one or more slices/coding block groups (usually non-overlapping), each slice/coding block group may include one or more blocks (e.g., CTU) or one or more coding blocks, etc., wherein each coding block may be in a rectangular shape, etc., and may include one or more complete or partial blocks (e.g., CTU).
  • slices/coding block groups also called video coding block groups
  • coding blocks also called video coding blocks
  • each slice/coding block group may include one or more blocks (e.g., CTU) or one or more coding blocks, etc., wherein each coding block may be in a rectangular shape, etc., and may include one or more complete or partial blocks (e.g., CTU).
  • the video decoder 30 may be used to decode the encoded image data 21.
  • the decoder 30 may generate an output video stream without the loop filter unit 320.
  • a non-transform based decoder 30 may directly dequantize the residual signal without the inverse transform processing unit 312 for certain blocks or frames.
  • the video decoder 30 may have the dequantization unit 310 and the inverse transform processing unit 312 combined into a single unit.
  • processing result of the current step can be further processed in the encoder 20 and the decoder 30 and then output to the next step.
  • the processing result of interpolation filtering, motion vector derivation or loop filtering can be further operated, such as clipping or shifting operation.
  • the derived motion vector of the current block can be further operated.
  • the value of the motion vector is limited to a predefined range according to the representation bit of the motion vector. If the representation bit of the motion vector is bitDepth, the range is -2 ⁇ (bitDepth-1) to 2 ⁇ (bitDepth-1)-1, where " ⁇ " represents the power. For example, if bitDepth is set to 16, the range is -32768 to 32767; if bitDepth is set to 18, the range is -131072 to 131071.
  • the value of the derived motion vector (e.g., the MV of 4 4 ⁇ 4 sub-blocks in an 8 ⁇ 8 block) is limited so that the maximum difference between the integer parts of the 4 4 ⁇ 4 sub-block MVs does not exceed N pixels, for example, not more than 1 pixel.
  • bitDepth Two methods of limiting motion vectors according to bitDepth are provided here.
  • the embodiments of the decoding system 10 can also be used for still image processing or coding and decoding, that is, the processing or coding and decoding of a single image in video coding and decoding that is independent of any previous or consecutive images.
  • the inter-frame prediction unit 244 encoder
  • the inter-frame prediction unit 344 decoder
  • All other functions (also called tools or techniques) of the video encoder 20 and the video decoder 30 can also be used for still image processing, such as residual calculation 204/304, transformation 206, quantization 208, inverse quantization 210/310, (inverse) transformation 212/312, segmentation 262/362, intra-frame prediction 254/354 and/or loop filtering 220/320, entropy coding 270 and entropy decoding 304.
  • FIG. 5 is an exemplary block diagram of a video decoding device 500 provided in an embodiment of the present application.
  • the video decoding device 500 is suitable for implementing the disclosed embodiments described herein.
  • the video decoding device 500 can be a decoder, such as the video decoder 30 in FIG. 1a, or an encoder, such as the video encoder 20 in FIG. 1a.
  • the video decoding device 500 includes: an input port 510 (or input port 510) and a receiving unit (receiver unit, Rx) 520 for receiving data; a processor, a logic unit or a central processing unit (CPU) 530 for processing data; for example, the processor 530 here can be a neural network processor 530; a transmitter unit (transmitter unit, Tx) 540 and an output port 550 (or output port 550) for transmitting data; and a memory 560 for storing data.
  • the video decoding device 500 may also include an optical-to-electrical (OE) component and an electrical-to-optical (EO) component coupled to the input port 510, the receiving unit 520, the transmitting unit 540 and the output port 550 for the exit or entrance of optical signals or electrical signals.
  • OE optical-to-electrical
  • EO electrical-to-optical
  • the processor 530 is implemented by hardware and software.
  • the processor 530 can be implemented as one or more processor chips, cores (e.g., multi-core processors), FPGAs, ASICs, and DSPs.
  • the processor 530 communicates with the input port 510, the receiving unit 520, the sending unit 540, the output port 550, and the memory 560.
  • the processor 530 includes a decoding module 570 (e.g., a decoding module 570 based on a neural network).
  • the decoding module 570 implements the embodiments disclosed above. For example, the decoding module 570 performs, processes, prepares, or provides various encoding operations.
  • the decoding module 570 provides substantial improvements to the functions of the video decoding device 500 and affects the switching of the video decoding device 500 to different states.
  • the decoding module 570 is implemented by instructions stored in the memory 560 and executed by the processor 530 .
  • the memory 560 includes one or more disks, tape drives, and solid-state drives, and can be used as an overflow data storage device for storing programs when such programs are selected for execution, and for storing instructions and data read during program execution.
  • the memory 560 can be volatile and/or non-volatile, and can be a read-only memory (ROM), a random access memory (RAM), a ternary content-addressable memory (TCAM), and/or a static random-access memory (SRAM).
  • FIG. 6 is an exemplary block diagram of an apparatus 600 provided in an embodiment of the present application.
  • the apparatus 600 can be used as either or both of the source device 12 and the destination device 14 in FIG. 1 a .
  • the processor 602 in the device 600 may be a central processing unit.
  • the processor 602 may be any other type of device or devices that are currently available or will be developed in the future and are capable of manipulating or processing information.
  • a single processor such as the processor 602 shown in the figure may be used to implement the disclosed implementation, using more than one processor is faster and more efficient.
  • the memory 604 in the apparatus 600 may be a read-only memory (ROM) device or a random access memory (RAM) device. Any other suitable type of storage device may be used as the memory 604.
  • the memory 604 may include code and data 606 accessed by the processor 602 via a bus 612.
  • the memory 604 may also include an operating system 608 and an application 610, which includes at least one program that allows the processor 602 to perform the methods described herein.
  • the application 610 may include applications 1 to N, and also include a video decoding application that performs the methods described herein.
  • the apparatus 600 may also include one or more output devices, such as a display 618.
  • the display 618 may be a touch-sensitive display that combines a display with a touch-sensitive element that may be used to sense touch input.
  • the display 618 may be coupled to the processor 602 via the bus 612.
  • bus 612 in the device 600 is described herein as a single bus, the bus 612 may include multiple buses.
  • the auxiliary storage may be directly coupled to other components of the device 600 or accessed through a network, and may include a single integrated unit such as a memory card or multiple units such as multiple memory cards. Therefore, the device 600 may have a variety of configurations.
  • Figure 7 is a coding method provided by an embodiment of the present application. As shown in Figure 7, the coding method may include:
  • the image to be encoded may be divided into a plurality of continuous image blocks (encoding blocks), and the image block to be encoded may be any image block among the plurality of image blocks.
  • S702 Determine the coding complexity of the image block to be coded according to multiple prediction modes.
  • the above-mentioned multiple prediction modes include at least one of block-level prediction, point-level prediction and intra-block copy (IBC) prediction.
  • the above-mentioned coding complexity is used to characterize the coding difficulty of the above-mentioned image block to be coded.
  • a prediction operation may be performed on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode. Then, a target parameter corresponding to the image block to be encoded and each prediction mode is determined according to the prediction residual. Then, a coding complexity of the image block to be encoded is determined according to the target parameter.
  • the target parameter includes at least one of the sum of absolute differences (SAD), the sum of absolute transformed differences (SATD) or the number of lossless coding bits.
  • SAD sum of absolute differences
  • SATD sum of absolute transformed differences
  • the prediction operation can be based on original or reconstructed pixels.
  • prediction operations can be performed on the image block to be encoded through block-level prediction, point-level prediction and intra-frame block copy prediction respectively to obtain the prediction block corresponding to the image block to be encoded and the block-level prediction, the prediction block corresponding to the image block to be encoded and the block-level prediction, and the prediction block corresponding to the image block to be encoded and the intra-frame block copy.
  • the difference between the prediction block of the image block to be encoded and the original block of the image block to be encoded is calculated to obtain the prediction residual (prediction residual 1) corresponding to the image block to be encoded and the block-level prediction, the prediction residual (prediction residual 2) corresponding to the image block to be encoded and the block-level prediction, and the prediction residual (prediction residual 3) corresponding to the image block to be encoded and the intra-frame block copy.
  • target parameters absolute error sum, absolute transform difference sum or lossless coding bit number
  • target parameter 1 is determined according to prediction residual 1
  • target parameter 2 is determined according to prediction residual 2
  • target parameter 3 is determined according to prediction residual 3.
  • the coding complexity of the image block to be encoded is determined according to the target parameters corresponding to the image block to be encoded and each prediction mode.
  • the coding complexity of the image block to be encoded may be determined according to a target absolute error, a target sum of absolute transform differences, or a target number of lossless coding bits.
  • the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode
  • the sum of the absolute transformation differences is the minimum sum of the absolute transformation differences corresponding to the image block to be encoded and each prediction mode
  • the target lossless coding bit number is the minimum lossless coding bit number among the lossless coding bit numbers corresponding to the image block to be encoded and each prediction mode.
  • the image block to be encoded is subjected to block-level prediction, point-level prediction and intra-frame block copy prediction respectively to obtain the absolute error corresponding to the image block to be encoded and the block-level prediction, the absolute error corresponding to the image block to be encoded and the block point-level prediction, and the absolute error corresponding to the image block to be encoded and the intra-frame block copy prediction. Then, the smallest absolute error among the absolute error corresponding to the block-level prediction, the absolute error corresponding to the image block to be encoded and the block point-level prediction, and the absolute error corresponding to the image block to be encoded and the intra-frame block copy prediction is taken as the target absolute error.
  • the coding complexity of the image block to be encoded is determined by comparing the target absolute error with a preset absolute error numerical range.
  • the preset absolute error numerical range includes multiple numerical ranges, and the multiple numerical ranges correspond one-to-one to multiple coding complexities (i.e., coding complexity levels).
  • the coding complexity corresponding to the above-mentioned image block to be encoded and each prediction mode can be determined according to the target parameters corresponding to the above-mentioned image block to be encoded and each prediction mode, and then the coding complexity of the image block to be encoded can be determined according to the coding complexity corresponding to the above-mentioned image block to be encoded and each prediction mode.
  • block-level prediction, point-level prediction and intra-block copy prediction are performed on the image block to be encoded respectively to obtain the sum of the absolute transformation differences between the image block to be encoded and the block-level prediction, the sum of the absolute transformation differences between the image block to be encoded and the block point-level prediction, and the sum of the absolute transformation differences between the image block to be encoded and the intra-block copy prediction.
  • the preset absolute transformation difference sum value range includes multiple value ranges, and the multiple value ranges correspond to multiple coding complexities (i.e., coding complexity levels) one by one.
  • the coding complexity corresponding to the image block to be encoded and the block-level prediction, the coding complexity corresponding to the image block to be encoded and the block point-level prediction, and the coding complexity corresponding to the image block to be encoded and the intra-frame block copy prediction are processed (such as selecting the minimum coding complexity, weighted summation of the coding complexity, etc.) to obtain the coding complexity of the image block to be encoded (i.e., the coding complexity level).
  • the first coding complexity of the image block to be encoded can be determined according to the target parameter.
  • the image block to be encoded is divided into a plurality of sub-blocks.
  • the horizontal difference block and the vertical difference block of each of the plurality of sub-blocks are determined.
  • the second coding complexity of the image block to be encoded is determined according to the horizontal difference block and the vertical difference block of each of the sub-blocks.
  • the coding complexity of the image block to be encoded is determined according to the first coding complexity and the second coding complexity.
  • prediction operations can be performed on the image block to be encoded through block-level prediction, point-level prediction and intra-frame block copy prediction respectively to obtain the prediction block corresponding to the image block to be encoded and the block-level prediction, the prediction block corresponding to the image block to be encoded and the block-level prediction, and the prediction block corresponding to the image block to be encoded and the intra-frame block copy.
  • the difference between the prediction block of the image block to be encoded and the original block of the image block to be encoded is calculated to obtain the prediction residual (prediction residual 1) corresponding to the image block to be encoded and the block-level prediction, the prediction residual (prediction residual 2) corresponding to the image block to be encoded and the block-level prediction, and the prediction residual (prediction residual 3) corresponding to the image block to be encoded and the intra-frame block copy.
  • the target parameters (the sum of absolute errors, the sum of absolute transformation differences or the number of lossless coding bits) of the above-mentioned image block to be encoded and corresponding to each prediction mode are determined according to the prediction residual.
  • the first coding complexity of the image block to be encoded is determined according to the target parameters corresponding to the image block to be encoded and each prediction mode.
  • the image block to be encoded is divided into multiple sub-blocks. Assuming that the size of the image block to be encoded is W ⁇ H, where W is the width of the image block and H is the height of the image block, in the embodiment of the present application, the image block to be encoded can be divided into N sub-blocks of (W/N) ⁇ H size.
  • horizontal and vertical difference calculations are performed, that is, for each sub-block, the differences between adjacent pixel values are calculated step by step from the horizontal and vertical directions to obtain a horizontal difference block and a vertical difference block of the sub-block.
  • the second coding complexity of each sub-block is calculated.
  • the SAD values of the horizontal difference block and the vertical difference block of each sub-block are calculated respectively to obtain the horizontal complexity value and the vertical complexity value of each sub-block, and the horizontal complexity value and the vertical complexity value are compared with the preset absolute error and the numerical range respectively to obtain the second coding complexity (second coding complexity level) of the sub-block.
  • the second coding complexity of the plurality of sub-blocks of the image to be coded is processed (such as selecting the minimum coding complexity, weighted summing the coding complexity, etc.) to obtain the second coding complexity of the image to be coded
  • the first coding complexity of the image to be coded and the second coding complexity of the image to be coded are processed (such as selecting the minimum coding complexity, weighted summing the coding complexities, etc.) to obtain the coding complexity of the image to be coded.
  • the above-mentioned image block to be encoded may be divided into a plurality of sub-blocks.
  • the plurality of sub-blocks are predicted by performing prediction operations to obtain prediction residuals corresponding to each sub-block and each prediction mode.
  • a target parameter corresponding to each sub-block and each prediction mode is determined according to the prediction residuals, wherein the target parameter includes at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits.
  • the coding complexity of the image block to be encoded is determined according to the target parameter.
  • the image block to be encoded can be divided into N sub-blocks, and each sub-block is predicted by block-level prediction, point-level prediction and intra-block copy prediction to obtain the prediction residual corresponding to each sub-block and each prediction mode.
  • the target parameters corresponding to each sub-block and each prediction mode are determined according to the prediction residual.
  • the coding complexity of the image block to be encoded is determined according to the target parameters.
  • the coding complexity of each of the sub-blocks may be determined according to the target parameter.
  • the coding complexity of the image block to be coded may be determined according to the coding complexity of each of the sub-blocks.
  • the coding complexity of each sub-block of the image to be encoded can be determined according to the above-mentioned target parameters, and then the coding complexity of each sub-block is processed (such as selecting the minimum coding complexity, weighted summing the coding complexities, etc.) to obtain the coding complexity of the image to be encoded.
  • the first coding complexity of the image block to be encoded can be determined according to the target parameter. Then, the horizontal difference block and the vertical difference block of each of the multiple sub-blocks are determined. Then, the second coding complexity of the image block to be encoded is determined according to the horizontal difference block and the vertical difference block of each of the sub-blocks. The coding complexity of the image block to be encoded is determined according to the first coding complexity and the second coding complexity.
  • the image block to be encoded may be divided into N sub-blocks.
  • each sub-block is predicted by block-level prediction, point-level prediction and intra-block copy prediction to obtain the prediction residual corresponding to each sub-block and each prediction mode.
  • the target parameters corresponding to each sub-block and each prediction mode are determined according to the prediction residual.
  • the first coding complexity of the image block to be encoded is determined according to the target parameters.
  • each sub-block horizontal and vertical difference calculations are performed on each sub-block, that is, for each sub-block, the differences between adjacent pixel values are calculated step by step in both horizontal and vertical directions to obtain a horizontal difference block and a vertical difference block of the sub-block.
  • the second coding complexity of each sub-block is calculated.
  • the SAD values of the horizontal difference block and the vertical difference block of each sub-block are calculated respectively to obtain the horizontal complexity value and the vertical complexity value of each sub-block, and the horizontal complexity value and the vertical complexity value are compared with the preset absolute error and the numerical range respectively to obtain the second coding complexity (second coding complexity level) of the sub-block.
  • the second coding complexity of the plurality of sub-blocks of the image to be coded is processed (such as selecting the minimum coding complexity, weighted summing the coding complexity, etc.) to obtain the second coding complexity of the image to be coded
  • the first coding complexity of the image to be coded and the second coding complexity of the image to be coded are processed (such as selecting the minimum coding complexity, weighted summing the coding complexities, etc.) to obtain the coding complexity of the image to be coded.
  • the above-mentioned division of the image to be encoded into multiple sub-blocks can be specifically as follows: assuming that the size of the current image block (i.e., the image to be encoded) is W ⁇ H, where W is the width of the image block and H is the height of the image block, in this embodiment, the image block is first divided into 2 small blocks of (W/2) ⁇ (H) size, from left to right, the first sub-block is called the left small block, and the second sub-block is called the right small block.
  • the above IBC prediction mode includes an IBC prediction mode applied to image blocks in the first column but not the first row of a slice, an IBC prediction mode applied to image blocks in the non-first column of a slice, and an IBC prediction mode applied to image blocks in the first row and first column of a slice.
  • the search area for the N/2 (W/N) ⁇ H sized sub-blocks of the left small block is: the S ⁇ H area to the left of the current (W/2) ⁇ (H) sized left small block
  • the search area for the N/2 (W/N) ⁇ H sized sub-blocks of the right small block is: the S ⁇ H area to the left of the current (W/2) ⁇ (H) sized right small block.
  • the search area of the N/2 (2*W/N) ⁇ (H/2)-sized sub-blocks of the left and right small blocks is the L ⁇ (H/2) area of the previous row of the current image block;
  • the search area of the N/4 (2*W/N) ⁇ H-sized sub-blocks of the left and right small blocks is the L ⁇ 1 area of the previous row of the current image block;
  • the search area of the N/2 (W/N) ⁇ H sub-blocks of the right small block is: the (W/2) ⁇ H area to the left of the current (P) ⁇ (H) size right small block.
  • the widths of the search areas of the sub-blocks may be the same, different, or partially the same.
  • the matching criterion for finding the best matching block in the search area is to minimize SAD, that is, the matching block with the smallest sum of the absolute values of the differences between the original values of the pixels at the corresponding positions in the current sub-block in the search area is the best matching block, wherein the matching block can be the difference between the original value of the pixel and the original value of the pixel of the current sub-block to calculate SAD, and the matching block can also be the difference between the reconstructed pixel value and the original value of the pixel of the current sub-block to calculate SAD.
  • the complexity level 1 of the image block is obtained by performing regular operations on the complexity of the N sub-blocks.
  • the specific process is as follows:
  • the coding complexity (coding complexity level) of the image block can be divided into CL types.
  • the group complexity of each group is compared with the agreed threshold, and the first coding complexity of the image block is derived from the CL types of coding complexity (coding complexity level).
  • the encoding complexity of the image block in the embodiment of the present application can be divided into five levels, namely 0, 1, 2, 3 and 4.
  • the coding complexity of the image block may be obtained according to the following rules.
  • the first coding complexity is set to 0
  • the first coding complexity is set to 1.
  • the first coding complexity is set to 2;
  • the first coding complexity is set to 0;
  • the first coding complexity is set to 1.
  • the first coding complexity is set to 2.
  • the first coding complexity is set to 3.
  • the first coding complexity is set to 2.
  • the first coding complexity is set to 3.
  • the first coding complexity is set to 4.
  • S703 Determine a quantization parameter of the image block to be encoded according to the encoding complexity of the image to be encoded.
  • the quantization parameter of the image block to be encoded may be determined according to the encoding complexity of the image to be encoded according to the following process.
  • Step 1 Calculate the buffer fullness.
  • the above buffer fullness calculation method can be: take out the physical buffer fullness PhyBufT at the specified time T from the physical buffer fullness record array, and the above physical buffer fullness record array saves the amount of data in the physical buffer when each previous coding block is encoded or decoded.
  • RcBufT PhyBufT + X0, where X0 is an agreed parameter.
  • F RcBufT/RcBufMAX, where RcBufMAX is the maximum value of the buffer.
  • Step 2 Calculate the expected block bit quantity, wherein the expected block bit quantity Bpp represents the expected coding bits of the current coding block without considering the image content.
  • Bpp 8 * BppINI + BppADJ.
  • BppINI is the initial value of the expected amount, which is obtained by multiplying the original number of bits of the input image block and the target compression rate.
  • BppADJ is the adjustment value of the expected amount, which is proportional to (RcBufEND-RcBufT), where RcBufEND is the expected buffer fullness at the end of the encoding or decoding process, and RcBufT is the buffer fullness obtained in the above step 1.
  • the expected amount of block bits may not be calculated.
  • Step 3 Calculate the information ratio, where the information ratio R represents the ratio of the information retained by the quantized coded block to the original coded block.
  • the information ratio is calculated as follows:
  • bitsOffset BitsOffset - X1*bpp + X2, where BitsOffset is the initial value of the bit offset, and X1 and X2 are agreed parameters.
  • Bpp is the expected amount of block bits obtained in the above step 2
  • InvTab is the agreed parameter table
  • X3, X4 and X5 are agreed parameters.
  • Step 4 Obtain the number of lossless coding bits, wherein the number of lossless coding bits BLL represents an estimated value of the number of coding bits of the coding block in a non-quantized state.
  • BLL RecordBLL[T][k], where T represents the specified time, and k represents the coding complexity of the input image block (ie, the coding complexity level).
  • Step 5 Calculate the target number of bits, where the target number of bits BTGT represents the number of bits that the coding block should obtain through the code control module.
  • R is the information ratio obtained in the above step 3
  • BLL is the number of lossless coding bits obtained in the above step 4
  • bitsOffset is the bit offset calculated in the above step 3
  • X6 and X7 are agreed parameters.
  • Step 6 Clamp the target bit number.
  • the minimum target bit BMIN and the maximum target bit BMAX can be calculated according to the expected block bit quantity Bpp, the lossless coding bit number BLL and the buffer fullness F, and the target bit number BTGT can be clamped using the range.
  • the target bit number may not be clamped.
  • Step 7 Calculate the quantization parameters.
  • BLL is the number of lossless coding bits obtained in the above step 4
  • BTGT is the target number of bits obtained in the above step 5
  • X8, X9 and X10 are agreed parameters.
  • the encoded image block is predicted, and then the image block to be encoded is quantized by the quantization parameter of the image block to be encoded, and then the image block to be encoded is entropy encoded to obtain a bit stream corresponding to the image block to be encoded.
  • the bit streams corresponding to all the encoded image blocks of the image to be encoded can be connected in series to obtain a bit stream corresponding to the image to be encoded.
  • the encoded image block is any image block among the multiple image blocks obtained by dividing the image block to be encoded.
  • the quantization parameter used in the encoding process will directly affect the image quality of the decoded image.
  • the image quality of the decoded image can be improved by adjusting the quantization parameter through the coding complexity of the image.
  • the related art uses the horizontal and vertical gradients of the image to calculate the coding complexity of the image.
  • the result of the gradient calculation is far different from the prediction error of the weak directional prediction mode.
  • the coding complexity calculated by the gradient and the actual coding complexity of the actual current coding block (image block) in the best prediction mode are far different, which leads to the inaccurate derived quantization parameter, affecting the image quality.
  • the embodiment of the present application determines the coding complexity of the image block to be encoded through multiple prediction modes.
  • the coding complexity of the image block can be accurately obtained based on the prediction effects of multiple prediction modes, thereby improving the accuracy of the coding complexity of the image block.
  • the quantization parameter obtained according to the coding complexity can be made more accurate. Since the accuracy of the quantization parameter is positively correlated with the image quality of the decoded image, the accuracy of the improved quantization parameter will make the image quality of the decoded image correspondingly improved.
  • the coding control parameter may be updated according to the number of coding bits of the image block to be encoded, wherein the coding control parameter includes at least one of an average lossless coding bit number record table, a lossless coding bit number record table, a physical buffer fullness record table, or a record table position.
  • the coding control parameters may be updated according to the number of coding bits of the image block to be coded according to the following process.
  • Process 1 Calculate the number of lossless coding bits.
  • BCU is the actual number of coding bits obtained after encoding or decoding the current coding block (i.e., the image block to be encoded)
  • QP is the quantization parameter used by the current block (i.e., the image block to be encoded)
  • X8, X9 and X11 are agreed parameters.
  • Process 2 Calculate the location of the record table.
  • the record table position TCUR represents the current coding block moment
  • the record table position TPRE represents the previous coding block moment
  • TPRE (TCUR + N-1)% N, where N is the interval value between the coding block to which the coding bit number in the code control input belongs and the image block to which the image block coding complexity (coding complexity level) belongs.
  • Process 3 Update the average lossless coding bit number record table.
  • RecordBAVG is an array of length N
  • RecordBAVG[t] represents the value of the tth position.
  • RecordBAVG[TCUR] (RecordBAVG[TPRE]+X12*BLC)*X13,
  • TCUR and TPRE are the record table positions calculated in the above process 2
  • BLC is the number of lossless coding bits calculated in the above process 1
  • X12 and X13 are agreed parameters.
  • Process 4 Update the lossless coding bit number record table.
  • the lossless coding bit number record table RecordBLL is a two-dimensional array of size N*K, and RecordBLL[t][k] represents the value of the image block coding complexity (coding complexity level) at the t-th position k.
  • TCUR and TPRE are the record table positions calculated in process 2
  • BLC is the number of lossless coding bits calculated in process 1
  • X14 and X15 are agreed parameters.
  • Process 5 Update the physical buffer fullness record table.
  • the physical buffer fullness record table RecordPHY is an array of length N, and RecordPHY[t] represents the value of the tth position.
  • the value of RecordPHY[TCUR] is updated to the actual value of the current physical buffer fullness.
  • the decoding method may include:
  • the bitstream may be entropy decoded to obtain the above coding complexity, wherein the bitstream is generated by encoding the above image block to be encoded.
  • S1202 Determine a quantization parameter of the image block to be encoded according to the encoding complexity of the image block to be encoded.
  • a prediction operation may be performed on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode.
  • a target parameter corresponding to the image block to be encoded and each prediction mode is determined according to the prediction residual, and the target parameter includes at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits.
  • the coding complexity of the image block to be encoded is determined according to the target parameter.
  • the first coding complexity of the image block to be encoded is determined according to the target parameter.
  • the image block to be encoded is divided into a plurality of sub-blocks.
  • the horizontal difference block and the vertical difference block of each of the plurality of sub-blocks are determined.
  • the second coding complexity of the image block to be encoded is determined according to the horizontal difference block and the vertical difference block of each of the sub-blocks.
  • the coding complexity of the image block to be encoded is determined according to the first coding complexity and the second coding complexity.
  • the coding complexity of the image block to be encoded is determined according to a target absolute error, a target sum of absolute transformation differences or a target number of lossless coding bits, wherein the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode, the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode, and the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the image block to be encoded is divided into a plurality of sub-blocks. Prediction operations are performed on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Target parameters corresponding to each sub-block and each prediction mode are determined according to the prediction residuals, and the target parameters include at least one of the sum of absolute errors, the sum of absolute transformation differences, or the number of lossless coding bits. The coding complexity of the image block to be encoded is determined according to the target parameters.
  • the coding complexity of each of the sub-blocks is determined according to the target parameter.
  • the coding complexity of the to-be-coded image block is determined according to the coding complexity of each of the sub-blocks.
  • a first coding complexity of the image block to be encoded is determined according to the target parameter.
  • a horizontal difference block and a vertical difference block of each of the multiple sub-blocks are determined.
  • a second coding complexity of the image block to be encoded is determined according to the horizontal difference block and the vertical difference block of each of the sub-blocks.
  • the coding complexity of the image block to be encoded is determined according to the first coding complexity and the second coding complexity.
  • S1202 can refer to the above S702, which will not be repeated here.
  • the code stream is generated by encoding the image block to be encoded.
  • the decoded image block is the reconstructed image block to be encoded.
  • the above-mentioned code stream can be entropy decoded to obtain the quantization parameters of the image block to be encoded, and then the code stream is dequantized according to the quantization parameters of the image block to be encoded, and then the code stream is decoded, and finally the above-mentioned image block to be encoded is output.
  • the encoding device includes hardware and/or software modules corresponding to the execution of each function.
  • the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to exceed the scope of the embodiments of the present application.
  • the embodiment of the present application can divide the functional modules of the encoding device according to the above method example.
  • each functional module can be divided corresponding to each function, or two or more functions can be integrated into one processing module.
  • the above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.
  • Figure 13 shows a possible composition diagram of the encoding device involved in the above embodiment.
  • the encoding device 1300 may include: an acquisition unit 1301, a first determination unit 1302, a second determination unit 1303 and an encoding unit 1304.
  • the acquisition unit 1301 is used to acquire the image block to be encoded.
  • the above-mentioned first determination unit 1302 is used to determine the coding complexity of the above-mentioned image block to be encoded according to multiple prediction modes, and the above-mentioned multiple prediction modes include at least one of block-level prediction, point-level prediction and intra-frame block copy prediction.
  • the above-mentioned coding complexity is used to characterize the coding difficulty of the above-mentioned image block to be encoded.
  • the second determining unit 1303 is configured to determine the quantization parameter of the to-be-encoded image block according to the encoding complexity.
  • the encoding unit 1304 is configured to encode the to-be-encoded image block according to the quantization parameter to generate a bit stream.
  • the first determination unit 1302 is specifically used to: perform a prediction operation on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode.
  • the first determination unit 1302 is specifically used to: determine the first coding complexity of the image block to be encoded according to the target parameter. Divide the image block to be encoded into a plurality of sub-blocks. Determine a horizontal difference block and a vertical difference block of each of the plurality of sub-blocks. Determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each of the sub-blocks. Determine the coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • the first determination unit 1302 is specifically used to determine the coding complexity of the image block to be encoded according to a target absolute error, a target sum of absolute transformation differences or a target number of lossless coding bits, wherein the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode, the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode, and the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the first determination unit 1302 is specifically used to: divide the image block to be encoded into a plurality of sub-blocks. Perform prediction operations on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Determine a target parameter corresponding to each sub-block and each prediction mode according to the prediction residuals, wherein the target parameter includes at least one of a sum of absolute errors, a sum of absolute transformation differences, or a number of lossless coding bits. Determine the coding complexity of the image block to be encoded according to the target parameters.
  • the first determining unit 1302 is specifically used to: determine a first coding complexity of the image block to be encoded according to the target parameter; determine a horizontal difference block and a vertical difference block of each of the multiple sub-blocks; determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each of the sub-blocks; and determine a coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • the encoding unit 1304 is further configured to: encode the encoding complexity into the bitstream.
  • a decoding device for executing the above decoding method will be introduced below in conjunction with FIG. 14 .
  • the decoding device includes hardware and/or software modules corresponding to the execution of each function.
  • the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to exceed the scope of the embodiments of the present application.
  • the embodiment of the present application can divide the functional modules of the decoding device according to the above method example.
  • each functional module can be divided according to each function, or two or more functions can be integrated into one processing module.
  • the above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.
  • Figure 14 shows a possible composition diagram of the decoding device involved in the above embodiment.
  • the decoding device 1400 may include: an acquisition unit 1401, a determination unit 1402 and a decoding unit 1403.
  • the acquisition unit 1401 is used to acquire the coding complexity of the image block to be encoded.
  • the coding complexity is used to characterize the coding difficulty of the image block to be encoded.
  • the coding complexity is determined by multiple prediction modes, and the multiple prediction modes include at least one of block-level prediction, point-level prediction and intra-frame block copy prediction.
  • the determination unit 1402 is configured to determine a quantization parameter of the to-be-encoded image block according to the encoding complexity.
  • the decoding unit 1403 is used to decode the code stream according to the quantization parameter to obtain a decoded image block, the code stream is generated by encoding the image block to be encoded, and the decoded image block is the reconstructed image block to be encoded.
  • the acquisition unit 1401 is specifically configured to: perform entropy decoding on the bit stream to obtain the coding complexity.
  • the acquisition unit 1401 is specifically used to: perform a prediction operation on the image block to be encoded according to the multiple prediction modes to obtain a prediction residual corresponding to the image block to be encoded and each prediction mode.
  • the acquisition unit 1401 is specifically used to: determine the first coding complexity of the image block to be encoded according to the target parameter. Divide the image block to be encoded into a plurality of sub-blocks. Determine the horizontal difference block and the vertical difference block of each of the plurality of sub-blocks. Determine the second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each of the sub-blocks. Determine the coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • the acquisition unit 1401 is specifically used to determine the coding complexity of the image block to be encoded according to a target absolute error, a target sum of absolute transformation differences or a target number of lossless coding bits, wherein the target absolute error is the minimum absolute error among the absolute errors corresponding to the image block to be encoded and each prediction mode, the sum of absolute transformation differences is the minimum sum of absolute transformation differences among the sums of absolute transformation differences corresponding to the image block to be encoded and each prediction mode, and the target number of lossless coding bits is the minimum number of lossless coding bits among the numbers of lossless coding bits corresponding to the image block to be encoded and each prediction mode.
  • the acquisition unit 1401 is specifically used to: divide the image block to be encoded into a plurality of sub-blocks. Perform prediction operations on the plurality of sub-blocks according to the plurality of prediction modes to obtain prediction residuals corresponding to each sub-block and each prediction mode. Determine target parameters corresponding to each sub-block and each prediction mode according to the prediction residuals, wherein the target parameters include at least one of the sum of absolute errors, the sum of absolute transformation differences, or the number of lossless coding bits. Determine the coding complexity of the image block to be encoded according to the target parameters.
  • the acquisition unit 1401 is specifically used to: determine the coding complexity of each sub-block according to the target parameter. Determine the coding complexity of the to-be-coded image block according to the coding complexity of each sub-block.
  • the acquisition unit 1401 is specifically used to: determine a first coding complexity of the image block to be encoded according to the target parameter; determine a horizontal difference block and a vertical difference block of each of the multiple sub-blocks; determine a second coding complexity of the image block to be encoded according to the horizontal difference block and the vertical difference block of each of the sub-blocks; and determine a coding complexity of the image block to be encoded according to the first coding complexity and the second coding complexity.
  • An embodiment of the present application also provides an encoding device, which includes: at least one processor, when the at least one processor executes program code or instructions, it implements the above-mentioned related method steps to implement the encoding method in the above-mentioned embodiment.
  • the device may further include at least one memory, and the at least one memory is used to store the program code or instruction.
  • An embodiment of the present application also provides a decoding device, which includes: at least one processor, when the at least one processor executes program code or instructions, it implements the above-mentioned related method steps to implement the decoding method in the above-mentioned embodiment.
  • the device may further include at least one memory, and the at least one memory is used to store the program code or instruction.
  • An embodiment of the present application also provides a computer storage medium, in which computer instructions are stored.
  • the encoding device executes the above-mentioned related method steps to implement the encoding and decoding method in the above-mentioned embodiment.
  • the embodiment of the present application also provides a computer program product.
  • the computer program product When the computer program product is run on a computer, the computer is enabled to execute the above-mentioned related steps to implement the encoding and decoding method in the above-mentioned embodiment.
  • the embodiment of the present application also provides a coding and decoding device, which can be a chip, an integrated circuit, a component or a module.
  • the device may include a connected processor and a memory for storing instructions, or the device includes at least one processor for obtaining instructions from an external memory.
  • the processor can execute instructions so that the chip executes the coding and decoding methods in the above-mentioned method embodiments.
  • FIG15 shows a schematic diagram of the structure of a chip 1500.
  • the chip 1500 includes one or more processors 1501 and an interface circuit 1502.
  • the chip 1500 may further include a bus 1503.
  • the processor 1501 may be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above encoding and decoding method may be completed by an integrated logic circuit of hardware in the processor 1501 or by instructions in the form of software.
  • the processor 1501 may be a general purpose processor, a digital signal processing (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • DSP digital signal processing
  • ASIC application specific integrated circuit
  • FPGA field programmable gate array
  • the general purpose processor may be a microprocessor or the processor may be any conventional processor, etc.
  • the interface circuit 1502 can be used to send or receive data, instructions or information.
  • the processor 1501 can use the data, instructions or other information received by the interface circuit 1502 to process, and can send the processing completion information through the interface circuit 1502.
  • the chip also includes a memory, which may include a read-only memory and a random access memory, and provides operation instructions and data to the processor.
  • a portion of the memory may also include a non-volatile random access memory (NVRAM).
  • NVRAM non-volatile random access memory
  • the memory stores executable software modules or data structures
  • the processor can perform corresponding operations by calling operation instructions stored in the memory (the operation instructions can be stored in the operating system).
  • the chip can be used in the encoding device or DOP involved in the embodiment of the present application.
  • the interface circuit 1502 can be used to output the execution result of the processor 1501.
  • processor 1501 and the interface circuit 1502 can be implemented through hardware design, software design, or a combination of hardware and software, and there is no limitation here.
  • the device, computer storage medium, computer program product or chip provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.
  • the size of the serial numbers of the above-mentioned processes does not mean the order of execution.
  • the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
  • the disclosed systems, devices and methods can be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.
  • Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.
  • the units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple network units. Select some or all of the units to achieve the purpose of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the above methods of each embodiment of the embodiment of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

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Abstract

本申请实施例公开了编解码方法和装置，涉及媒体技术领域，能够提升解码后得到图像的图像质量。该方法包括：首先获取待编码图像块，然后根据多个预测模式确定待编码图像块的编码复杂度，之后根据上述编码复杂度确定上述待编码图像块的量化参数，然后根据上述量化参数对上述待编码图像块进行编码生成码流。其中，上述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项，上述编码复杂度用于表征上述待编码图像块编码难度。

Description

编解码方法和装置
本申请要求于2022年11月04日提交中国专利局、申请号为202211373846.0、申请名称为“编解码方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请实施例涉及媒体技术领域，尤其涉及编解码方法和装置。
背景技术
媒体设备在传输媒体内容时会使用到显示接口。显示接口在传输媒体内容时，可以通过编码操作对媒体内容进行压缩以降低媒体内容传输过程中的带宽量。接收端在收到压缩后的媒体内容后需要通过解码操作对压缩后的媒体内容进行解码还原媒体内容。
码率控制可以在编码过程中对输出码率进行调整，不同的码率控制手段会对解码后的图像质量造成较大影响。
因此，如何在编码过程中提升码率控制效果，以提升解码后得到图像的图像质量是本领域技术人员亟须解决的问题之一。
发明内容
本申请实施例提供了编解码方法和装置，能够提升解码后得到图像的图像质量。为达到上述目的，本申请实施例采用如下技术方案：
第一方面，本申请实施例提供了一种编码方法，该方法包括：首先获取待编码图像块，然后根据多个预测模式确定待编码图像块的编码复杂度，之后根据上述编码复杂度确定上述待编码图像块的量化参数，然后根据上述量化参数对上述待编码图像块进行编码生成码流。其中，上述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项，上述编码复杂度用于表征上述待编码图像块编码难度。
需要说明的是，编码过程中使用的量化参数会直接影响解码得到的图像的图像质量。通过图像的编码复杂度调整量化参数可以提高解码得到的图像的图像质量。但相关技术采用图像水平和垂直梯度计算图像编码复杂度，对于弱方向性的预测模式，梯度计算的结果与弱方向性预测模式的预测误差相差较远，此时会导致梯度计算出的编码复杂度和实际当前编码块(图像块)在最佳预测模式下的实际编码复杂度相差较远，进而导致推导出的量化参数不准，影响图像质量。而本申请实施例通过多个预测模式确定待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在一种可能的实现方式中，可以根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差；然后根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；之后根据所述目标参数确定所述待编码图像块的编码复杂度。
可以看出，本申请实施例提供的方法可以通过多个预测模式对所述待编码图像块进行预测操作以得到待编码图像块与每一预测模式对应的绝对误差和、绝对变换差之和或无损编码比特数，然后根据这些信息确定待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在一种可能的实现方式中，可以根据所述目标参数确定所述待编码图像块的第一编码复杂度；将所述待编码图像块划分为多个子块。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一 子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
可以看出，本申请实施例提供的方法可以通过多种预测模式和图像水平和垂直梯度计算图像编码复杂度，相较于仅通过图像水平和垂直梯度计算图像编码复杂度，可以在弱方向性的预测模式，提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在另一种可能的实现方式中，可以根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
可以看出，本申请实施例通过多个预测模式确定目标绝对误差、目标绝对变换差之和或目标无损编码比特数，然后通过目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在另一种可能的实现方式中，可以将所述待编码图像块划分为多个子块。根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
可以看出，本申请实施例提供的方法可以通过多个预测模式对所述待编码图像块的子块进行预测操作以得到待编码图像块的每一子块与每一预测模式对应的绝对误差和、绝对变换差之和或无损编码比特数，然后根据这些信息确定待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。另外，相比于通过多个预测模式对所述待编码图像块进行预测操作，将待编码图像块切分为多个子块，通过多个预测模式对所述待编码图像块的多个子块进行预测操作可以进一步提高得到的编码复杂度的准确性。
在一种可能的实现方式中，可以根据所述目标参数确定所述每一子块的编码复杂度。根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
可以看出，本申请实施例提供的方法可以通过多个预测模式对所述待编码图像块的多个子块进行预测操作以得到编码图像块的每一子块的编码复杂度，然后通过待编码图像块的每一子块的编码复杂度计算出待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在一种可能的实现方式中，可以根据所述目标参数确定所述待编码图像块的第一编码复杂度；确定所述多个子块中每一子块的水平差值块和垂直差值块；根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
可以看出，本申请实施例提供的方法可以通过多种预测模式和图像水平和垂直梯度计算图像编码复杂度，相较于仅通过图像水平和垂直梯度计算图像编码复杂度，可以在弱方向性的预测模式，提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图 像的图像质量相应提高。
在一种可能的实现方式中，可以将所述编码复杂度编入所述码流。
可以看出，本申请实施例可以将通过多个预测模式确定待编码图像块的编码复杂度编入码流，使解码端根据码流中的编码复杂度解码码流得到解码图像，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
第二方面，本申请实施例还提供了一种解码方法，该方法包括：获取待编码图像块的编码复杂度，所述编码复杂度用于表征待编码图像块编码难度，所述编码复杂度由多个预测模式确定，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项。根据所述编码复杂度确定所述待编码图像块的量化参数。根据所述量化参数对码流进行解码以得到解码图像块，所述码流由所述待编码图像块编码生成，所述解码图像块为重建后的所述待编码图像块。
需要说明的是，编码过程中使用的量化参数会直接影响解码得到的图像的图像质量。通过图像的编码复杂度调整量化参数可以提高解码得到的图像的图像质量。但相关技术采用图像水平和垂直梯度计算图像编码复杂度，对于弱方向性的预测模式，梯度计算的结果与弱方向性预测模式的预测误差相差较远，此时会导致梯度计算出的编码复杂度和实际当前编码块(图像块)在最佳预测模式下的实际编码复杂度相差较远，进而导致推导出的量化参数不准，影响图像质量。而本申请实施例通过多个预测模式确定待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在一种可能的实现方式中，可以对所述码流进行熵解码以得到所述编码复杂度。
在一种可能的实现方式中，可以根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差。根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据所述目标参数确定所述待编码图像块的第一编码复杂度。将所述待编码图像块划分为多个子块。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
在一种可能的实现方式中，将所述待编码图像块划分为多个子块。根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据所述目标参数确定所述每一子块的编码复杂度。根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据所述目标参数确定所述待编码图像块的第一编码复杂度。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
第三方面，本申请实施例还提供了一种编码装置，该装置包括：获取单元，第一确定单元、第二确定单元和编码单元。所述获取单元，用于获取待编码图像块。所述第一确定单元，用于根据多个预测模式确 定所述待编码图像块的编码复杂度，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项，所述编码复杂度用于表征所述待编码图像块编码难度。所述第二确定单元，用于根据所述编码复杂度确定所述待编码图像块的量化参数。所述编码单元，用于根据所述量化参数对所述待编码图像块进行编码生成码流。
在一种可能的实现方式中，所述第一确定单元具体用于：根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差。根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述第一确定单元具体用于：根据所述目标参数确定所述待编码图像块的第一编码复杂度。将所述待编码图像块划分为多个子块。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述第一确定单元具体用于：根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
在一种可能的实现方式中，所述第一确定单元具体用于：将所述待编码图像块划分为多个子块。根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述第一确定单元具体用于：根据所述目标参数确定所述每一子块的编码复杂度。根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述第一确定单元具体用于：根据所述目标参数确定所述待编码图像块的第一编码复杂度。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述编码单元还用于：将所述编码复杂度编入所述码流。
第四方面，本申请实施例还提供了一种解码装置，该装置包括：获取单元、确定单元和解码单元。所述获取单元，用于获取待编码图像块的编码复杂度，所述编码复杂度用于表征待编码图像块编码难度，所述编码复杂度由多个预测模式确定，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项。所述确定单元，用于根据所述编码复杂度确定所述待编码图像块的量化参数。所述解码单元，用于根据所述量化参数对码流进行解码以得到解码图像块，所述码流由所述待编码图像块编码生成，所述解码图像块为重建后的所述待编码图像块。
在一种可能的实现方式中，所述获取单元具体用于：对所述码流进行熵解码以得到所述编码复杂度。
在一种可能的实现方式中，所述获取单元具体用于：根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差。根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述获取单元具体用于：根据所述目标参数确定所述待编码图像块的第一编码复杂度。将所述待编码图像块划分为多个子块。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述获取单元具体用于：根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
在一种可能的实现方式中，所述获取单元具体用于：将所述待编码图像块划分为多个子块。根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据所述目标参数确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，在一种可能的实现方式中，所述获取单元具体用于：根据所述目标参数确定所述每一子块的编码复杂度。根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
在一种可能的实现方式中，所述获取单元具体用于。根据所述目标参数确定所述待编码图像块的第一编码复杂度。确定所述多个子块中每一子块的水平差值块和垂直差值块。根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度。根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
第五方面，本申请实施例还提供一种编码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述第一方面或其任意可能的实现方式中所述的方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
第六方面，本申请实施例还提供一种解码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述第二方面或其任意可能的实现方式中所述的方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
第七方面，本申请实施例还提供一种芯片，包括：输入接口、输出接口、至少一个处理器。可选地，该芯片还包括存储器。该至少一个处理器用于执行该存储器中的代码，当该至少一个处理器执行该代码时，该芯片实现上述第一方面或其任意可能的实现方式中所述的方法。
可选地，上述芯片还可以为集成电路。
第八方面，本申请实施例还提供一种计算机可读存储介质，用于存储计算机程序，该计算机程序包括用于实现上述第一方面或其任意可能的实现方式中所述的方法。
第九方面，本申请实施例还提供一种包含指令的计算机程序产品，当其在计算机上运行时，使得计算机实现上述第一方面或其任意可能的实现方式中所述的方法。
本实施例提供的编解码装置、计算机存储介质、计算机程序产品和芯片均用于执行上文所提供的编解码方法，因此，其所能达到的有益效果可参考上文所提供的编解码方法中的有益效果，此处不再赘述。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请实施例的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1a为本申请实施例提供的译码系统的一种示例性框图；
图1b为本申请实施例提供的视频译码系统的一种示例性框图；
图2为本申请实施例提供的视频编码器的一种示例性框图；
图3为本申请实施例提供的视频解码器的一种示例性框图；
图4为本申请实施例提供的候选图像块的一种示例性的示意图；
图5为本申请实施例提供的视频译码设备的一种示例性框图；
图6为本申请实施例提供的装置的一种示例性框图；
图7为本申请实施例提供的一种编码方法的示意图；
图8为本申请实施例提供的一种确定编码复杂度的流程示意图；
图9为本申请实施例提供的另一种确定编码复杂度的流程示意图；
图10为本申请实施例提供的又一种确定编码复杂度的流程示意图；
图11为本申请实施例提供的又一种确定编码复杂度的流程示意图；
图12为本申请实施例提供的一种解码方法的示意图；
图13为本申请实施例提供的一种编码装置的示意图；
图14为本申请实施例提供的一种解码装置的示意图；
图15为本申请实施例提供的一种芯片的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请实施例一部分实施例，而不是全部的实施例。基于本申请实施例中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请实施例保护的范围。
本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
本申请实施例的说明书以及附图中的术语“第一”和“第二”等是用于区别不同的对象，或者用于区别对同一对象的不同处理，而不是用于描述对象的特定顺序。
此外，本申请实施例的描述中所提到的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选的还包括其他没有列出的步骤或单元，或可选的还包括对于这些过程、方法、产品或设备固有的其他步骤或单元。
需要说明的是，本申请实施例的描述中，“示例性地”或者“例如”等词用于表示作例子、例证或说明。本申请实施例中被描述为“示例性地”或者“例如”的任何实施例或设计方案不应被解释为比其他实施例或设计方案更优选或更具优势。确切而言，使用“示例性地”或者“例如”等词旨在以具体方式呈现相关概念。
在本申请实施例的描述中，除非另有说明，“多个”的含义是指两个或两个以上。
首先对本申请实施例涉及的术语进行解释。
接口压缩：媒体设备在传输图像、视频时会使用到显示接口，对通过显示接口的图像视比特流：对图像、视频内容进行编码后生成的二进制流。
切片：输入图像可被划分为一个或多个切片。每个切片划分为一个或多个编码块进行编码。
码率控制：在编码过程中对输出码率进行调整的过程，基于对当前的图像内容、比特流缓冲区余量等信息进行分析，通过改变编码的量化参数、编码模式等手段，起到调整输出码率的作用。以下简写为。
量化参数(Quantization Parameter，QP)：在编码过程中，预测操作产生的残差值或变换操作产生的系数进行量化后写入比特流；在解码过程中对语法元素进行反量化得到残差值或系数。QP为该量化过程使用的参数，通常QP值越大、量化的程度越明显。调整QP值会直接影响编码后比特流的长度和解码后的图像质量。
恒定码率策略(Constant Bit Rate，CBR)：一种策略，其特点是在单位时间内，编码器输出的比特流长度一致。
块复制帧内(Intra Block Copy，IBC)预测模式：当前编码块可划分为一个或多个子块，在搜索区域内以一定的匹配准则为每个子块寻找最优匹配块，最优匹配块即为当前子块的预测块，并计算块向量。其中，块向量为当前块与最优匹配块的位置向量。
块级预测：以块为预测单元，当前编码块内的重建值不能作为当前块内后续点预测参考值的预测操作。
点级预测：以点为预测单元，当前编码块内的重建值可作为当前块内后续点预测参考值的预测操作。
数据编解码包括数据编码和数据解码两部分。数据编码在源侧(或通常称为编码器侧)执行，通常包括处理(例如，压缩)原始数据以减少表示该原始数据所需的数据量(从而更高效存储和/或传输)。数据解码在目的地侧(或通常称为解码器侧)执行，通常包括相对于编码器侧作逆处理，以重建原始数据。本申请实施例涉及的数据的“编解码”应理解为数据的“编码”或“解码”。编码部分和解码部分也合称为编解码(编码和解码，CODEC)。
在无损数据编码情况下，可以重建原始数据，即重建的原始数据与原始数据具有相同的质量(假设存储或传输期间没有传输损耗或其他数据丢失)。在有损数据编码情况下，通过量化等执行进一步压缩，来减少表示原始数据所需的数据量，而解码器侧无法完全重建原始数据，即重建的原始数据的质量比原始数据的质量低或差。
本申请实施例可以应用于对视频数据以及其他具有压缩/解压缩需求的数据等。以下以视频数据的编码(简称视频编码)为例对本申请实施例进行说明，其他类型的数据(例如图像数据、音频数据、整数型数据以及其他具有压缩/解压缩需求的数据)可以参考以下描述，本申请实施例对此不再赘述。需要说明的是，相对于视频编码，音频数据以及整数型数据等数据的编码过程中无需将数据分割为块，而是可以直接对数 据进行编码。
视频编码通常是指处理形成视频或视频序列的图像序列。在视频编码领域，术语“图像(picture)”、“帧(frame)”或“图片(image)”可以用作同义词。
几个视频编码标准属于“有损混合型视频编解码”(即，将像素域中的空间和时间预测与变换域中用于应用量化的2D变换编码结合)。视频序列中的每个图像通常分割成不重叠的块集合，通常在块级上进行编码。换句话说，编码器通常在块(视频块)级处理即编码视频，例如，通过空间(帧内)预测和时间(帧间)预测来产生预测块；从当前块(当前处理/待处理的块)中减去预测块，得到残差块；在变换域中变换残差块并量化残差块，以减少待传输(压缩)的数据量，而解码器侧将相对于编码器的逆处理部分应用于编码或压缩的块，以重建用于表示的当前块。另外，编码器需要重复解码器的处理步骤，使得编码器和解码器生成相同的预测(例如，帧内预测和帧间预测)和/或重建像素，用于处理，即编码后续块。
在以下译码系统10的实施例中，编码器20和解码器30根据图1a至图3进行描述。
图1a为本申请实施例提供的译码系统10的一种示例性框图，例如可以利用本申请实施例技术的视频译码系统10(或简称为译码系统10)。视频译码系统10中的视频编码器20(或简称为编码器20)和视频解码器30(或简称为解码器30)代表可用于根据本申请实施例中描述的各种示例执行各技术的设备等。
如图1a所示，译码系统10包括源设备12，源设备12用于将编码图像等编码图像数据21提供给用于对编码图像数据21进行解码的目的设备14。
源设备12包括编码器20，另外即可选地，可包括图像源16、图像预处理器等预处理器(或预处理单元)18、通信接口(或通信单元)22。
图像源16可包括或可以为任意类型的用于捕获现实世界图像等的图像捕获设备，和/或任意类型的图像生成设备，例如用于生成计算机动画图像的计算机图形处理器或任意类型的用于获取和/或提供现实世界图像、计算机生成图像(例如，屏幕内容、虚拟现实(virtual reality，VR)图像和/或其任意组合(例如增强现实(augmented reality，AR)图像)的设备。所述图像源可以为存储上述图像中的任意图像的任意类型的内存或存储器。
为了区分预处理器(或预处理单元)18执行的处理，图像(或图像数据)17也可称为原始图像(或原始图像数据)17。
预处理器18用于接收原始图像数据17，并对原始图像数据17进行预处理，得到预处理图像(或预处理图像数据)19。例如，预处理器18执行的预处理可包括修剪、颜色格式转换(例如从RGB转换为YCbCr)、调色或去噪。可以理解的是，预处理单元18可以为可选组件。
视频编码器(或编码器)20用于接收预处理图像数据19并提供编码图像数据21(下面将根据图2等进一步描述)。
源设备12中的通信接口22可用于：接收编码图像数据21并通过通信信道13向目的设备14等另一设备或任何其他设备发送编码图像数据21(或其他任意处理后的版本)，以便存储或直接重建。
目的设备14包括解码器30，另外即可选地，可包括通信接口(或通信单元)28、后处理器(或后处理单元)32和显示设备34。
目的设备14中的通信接口28用于直接从源设备12或从存储设备等任意其他源设备接收编码图像数据21(或其他任意处理后的版本)，例如，存储设备为编码图像数据存储设备，并将编码图像数据21提供给解码器30。
通信接口22和通信接口28可用于通过源设备12与目的设备14之间的直连通信链路，例如直接有线或无线连接等，或者通过任意类型的网络，例如有线网络、无线网络或其任意组合、任意类型的私网和公网或其任意类型的组合，发送或接收编码图像数据(或编码数据)21。
例如，通信接口22可用于将编码图像数据21封装为报文等合适的格式，和/或使用任意类型的传输编码或处理来处理所述编码后的图像数据，以便在通信链路或通信网络上进行传输。
通信接口28与通信接口22对应，例如，可用于接收传输数据，并使用任意类型的对应传输解码或处理和/或解封装对传输数据进行处理，得到编码图像数据21。
通信接口22和通信接口28均可配置为如图1a中从源设备12指向目的设备14的对应通信信道13的箭头所指示的单向通信接口，或双向通信接口，并且可用于发送和接收消息等，以建立连接，确认并交换与通信链路和/或例如编码后的图像数据传输等数据传输相关的任何其他信息，等等。
视频解码器(或解码器)30用于接收编码图像数据21并提供解码图像数据(或解码图像数据)31(下 面将根据图3等进一步描述)。
后处理器32用于对解码后的图像等解码图像数据31(也称为重建后的图像数据)进行后处理，得到后处理后的图像等后处理图像数据33。后处理单元32执行的后处理可以包括例如颜色格式转换(例如从YCbCr转换为RGB)、调色、修剪或重采样，或者用于产生供显示设备34等显示的解码图像数据31等任何其他处理。
显示设备34用于接收后处理图像数据33，以向用户或观看者等显示图像。显示设备34可以为或包括任意类型的用于表示重建后图像的显示器，例如，集成或外部显示屏或显示器。例如，显示屏可包括液晶显示器(liquid crystal display，LCD)、有机发光二极管(organic light emitting diode，OLED)显示器、等离子显示器、投影仪、微型LED显示器、硅基液晶显示器(liquid crystal on silicon，LCoS)、数字光处理器(digital light processor，DLP)或任意类型的其他显示屏。
译码系统10还包括训练引擎25，训练引擎25用于训练编码器20(尤其是编码器20中的熵编码单元270)或解码器30(尤其是解码器30中的熵解码单元304)，以根据估计得到的估计概率分布对待编码图像块进行熵编码，训练引擎25的详细说明请参考下述方法测试施例。
尽管图1a示出了源设备12和目的设备14作为独立的设备，但设备实施例也可以同时包括源设备12和目的设备14或同时包括源设备12和目的设备14的功能，即同时包括源设备12或对应功能和目的设备14或对应功能。在这些实施例中，源设备12或对应功能和目的设备14或对应功能可以使用相同硬件和/或软件或通过单独的硬件和/或软件或其任意组合来实现。
根据描述，图1a所示的源设备12和/或目的设备14中的不同单元或功能的存在和(准确)划分可能根据实际设备和应用而有所不同，这对技术人员来说是显而易见的。
请参考图1b，图1b为本申请实施例提供的视频译码系统40的一种示例性框图，编码器20(例如视频编码器20)或解码器30(例如视频解码器30)或两者都可通过如图1b所示的视频译码系统40中的处理电路实现，例如一个或多个微处理器、数字信号处理器(digital signal processor，DSP)、专用集成电路(application-specific integrated circuit，ASIC)、现场可编程门阵列(field-programmable gate array，FPGA)、离散逻辑、硬件、视频编码专用处理器或其任意组合。请参考图2和图3，图2为本申请实施例提供的视频编码器的一种示例性框图，图3为本申请实施例提供的视频解码器的一种示例性框图。编码器20可以通过处理电路46实现，以包含参照图2编码器20论述的各种模块和/或本文描述的任何其他编码器系统或子系统。解码器30可以通过处理电路46实现，以包含参照图3解码器30论述的各种模块和/或本文描述的任何其他解码器系统或子系统。所述处理电路46可用于执行下文论述的各种操作。如图5所示，如果部分技术在软件中实施，则设备可以将软件的指令存储在合适的非瞬时性计算机可读存储介质中，并且使用一个或多个处理器在硬件中执行指令，从而执行本申请实施例技术。视频编码器20和视频解码器30中的其中一个可作为组合编解码器(encoder/decoder，CODEC)的一部分集成在单个设备中，如图1b所示。
源设备12和目的设备14可包括各种设备中的任一种，包括任意类型的手持设备或固定设备，例如，笔记本电脑或膝上型电脑、手机、智能手机、平板或平板电脑、相机、台式计算机、机顶盒、电视机、显示设备、数字媒体播放器、视频游戏控制台、视频流设备(例如，内容业务服务器或内容分发服务器)、广播接收设备、广播发射设备以及监控设备等等，并可以不使用或使用任意类型的操作系统。源设备12和目的设备14也可以是云计算场景中的设备，例如云计算场景中的虚拟机等。在一些情况下，源设备12和目的设备14可配备用于无线通信的组件。因此，源设备12和目的设备14可以是无线通信设备。
源设备12和目的设备14可以安装虚拟现实(virtual reality，VR)应用、增强现实(augmented reality，AR)应用或者混合现实(mixed reality，MR)应用等虚拟场景应用程序(application，APP)，并可以基于用户的操作(例如点击、触摸、滑动、抖动、声控等)运行VR应用、AR应用或者MR应用。源设备12和目的设备14可以通过摄像头和/或传感器采集环境中任意物体的图像/视频，再根据采集的图像/视频在显示设备上显示虚拟物体，该虚拟物体可以是VR场景、AR场景或MR场景中的虚拟物体(即虚拟环境中的物体)。
需要说明的是，本申请实施例中，源设备12和目的设备14中的虚拟场景应用程序可以是源设备12和目的设备14自身内置的应用程序，也可以是用户自行安装的第三方服务商提供的应用程序，对此不做具体限定。
此外，源设备12和目的设备14可以安装实时视频传输应用，例如直播应用。源设备12和目的设备14可以通过摄像头采集图像/视频，再将采集的图像/视频在显示设备上显示。
在一些情况下，图1a所示的视频译码系统10仅仅是示例性的，本申请实施例提供的技术可适用于视频编码设置(例如，视频编码或视频解码)，这些设置不一定包括编码设备与解码设备之间的任何数据通信。在其他示例中，数据从本地存储器中检索，通过网络发送，等等。视频编码设备可以对数据进行编码并将数据存储到存储器中，和/或视频解码设备可以从存储器中检索数据并对数据进行解码。在一些示例中，编码和解码由相互不通信而只是编码数据到存储器和/或从存储器中检索并解码数据的设备来执行。
请参考图1b，图1b为本申请实施例提供的视频译码系统40的一种示例性框图，如图1b所示，视频译码系统40可以包含成像设备41、视频编码器20、视频解码器30(和/或藉由处理电路46实施的视频编/解码器)、天线42、一个或多个处理器43、一个或多个内存存储器44和/或显示设备45。
如图1b所示，成像设备41、天线42、处理电路46、视频编码器20、视频解码器30、处理器43、内存存储器44和/或显示设备45能够互相通信。在不同实例中，视频译码系统40可以只包含视频编码器20或只包含视频解码器30。
在一些实例中，天线42可以用于传输或接收视频数据的经编码比特流。另外，在一些实例中，显示设备45可以用于呈现视频数据。处理电路46可以包含专用集成电路(application-specific integrated circuit，ASIC)逻辑、图形处理器、通用处理器等。视频译码系统40也可以包含可选的处理器43，该可选处理器43类似的可以包含专用集成电路(application-specific integrated circuit，ASIC)逻辑、图形处理器、通用处理器等。另外，内存存储器44可以是任何类型的存储器，例如易失性存储器(例如，静态随机存取存储器(static random access memory，SRAM)、动态随机存储器(dynamic random access memory，DRAM)等)或非易失性存储器(例如，闪存等)等。在非限制性实例中，内存存储器44可以由超速缓存内存实施。在其他实例中，处理电路46可以包含存储器(例如，缓存等)用于实施图像缓冲器等。
在一些实例中，通过逻辑电路实施的视频编码器20可以包含(例如，通过处理电路46或内存存储器44实施的)图像缓冲器和(例如，通过处理电路46实施的)图形处理单元。图形处理单元可以通信耦合至图像缓冲器。图形处理单元可以包含通过处理电路46实施的视频编码器20，以实施参照图2和/或本文中所描述的任何其他编码器系统或子系统所论述的各种模块。逻辑电路可以用于执行本文所论述的各种操作。
在一些实例中，视频解码器30可以以类似方式通过处理电路46实施，以实施参照图3的视频解码器30和/或本文中所描述的任何其他解码器系统或子系统所论述的各种模块。在一些实例中，逻辑电路实施的视频解码器30可以包含(通过处理电路46或内存存储器44实施的)图像缓冲器和(例如，通过处理电路46实施的)图形处理单元。图形处理单元可以通信耦合至图像缓冲器。图形处理单元可以包含通过处理电路46实施的视频解码器30，以实施参照图3和/或本文中所描述的任何其他解码器系统或子系统所论述的各种模块。
在一些实例中，天线42可以用于接收视频数据的经编码比特流。如所论述，经编码比特流可以包含本文所论述的与编码视频帧相关的数据、指示符、索引值、模式选择数据等，例如与编码分割相关的数据(例如，变换系数或经量化变换系数，(如所论述的)可选指示符，和/或定义编码分割的数据)。视频译码系统40还可包含耦合至天线42并用于解码经编码比特流的视频解码器30。显示设备45用于呈现视频帧。
应理解，本申请实施例中对于参考视频编码器20所描述的实例，视频解码器30可以用于执行相反过程。关于信令语法元素，视频解码器30可以用于接收并解析这种语法元素，相应地解码相关视频数据。在一些例子中，视频编码器20可以将语法元素熵编码成经编码视频比特流。在此类实例中，视频解码器30可以解析这种语法元素，并相应地解码相关视频数据。
为便于描述，参考通用视频编码(versatile video coding，VVC)参考软件或由ITU-T视频编码专家组(video coding experts group，VCEG)和ISO/IEC运动图像专家组(motion picture experts group，MPEG)的视频编码联合工作组(joint collaboration team on video coding，JCT-VC)开发的高性能视频编码(high-efficiency video coding，HEVC)描述本申请实施例。本领域普通技术人员理解本申请实施例不限于HEVC或VVC。
编码器和编码方法
如图2所示，视频编码器20包括输入端(或输入接口)201、残差计算单元204、变换处理单元206、量化单元208、反量化单元210、逆变换处理单元212、重建单元214、环路滤波器220、解码图像缓冲器(decoded picture buffer，DPB)230、模式选择单元260、熵编码单元270和输出端(或输出接口)272。 模式选择单元260可包括帧间预测单元244、帧内预测单元254和分割单元262。帧间预测单元244可包括运动估计单元和运动补偿单元(未示出)。图2所示的视频编码器20也可称为混合型视频编码器或基于混合型视频编解码器的视频编码器。
参见图2，帧间预测单元为经过训练的目标模型(亦称为神经网络)，该神经网络用于处理输入图像或图像区域或图像块，以生成输入图像块的预测值。例如，用于帧间预测的神经网络用于接收输入的图像或图像区域或图像块，并且生成输入的图像或图像区域或图像块的预测值。
残差计算单元204、变换处理单元206、量化单元208和模式选择单元260组成编码器20的前向信号路径，而反量化单元210、逆变换处理单元212、重建单元214、缓冲器216、环路滤波器220、解码图像缓冲器(decoded picture buffer，DPB)230、帧间预测单元244和帧内预测单元254组成编码器的后向信号路径，其中编码器20的后向信号路径对应于解码器的信号路径(参见图3中的解码器30)。反量化单元210、逆变换处理单元212、重建单元214、环路滤波器220、解码图像缓冲器230、帧间预测单元244和帧内预测单元254还组成视频编码器20的“内置解码器”。
图像和图像分割(图像和块)
编码器20可用于通过输入端201等接收图像(或图像数据)17，例如，形成视频或视频序列的图像序列中的图像。接收的图像或图像数据也可以是预处理后的图像(或预处理后的图像数据)19。为简单起见，以下描述使用图像17。图像17也可称为当前图像或待编码的图像(尤其是在视频编码中将当前图像与其他图像区分开时，其他图像例如同一视频序列，即也包括当前图像的视频序列，中的之前编码后图像和/或解码后图像)。
(数字)图像为或可以视为具有强度值的像素点组成的二维阵列或矩阵。阵列中的像素点也可以称为像素(pixel或pel)(图像元素的简称)。阵列或图像在水平方向和垂直方向(或轴线)上的像素点数量决定了图像的大小和/或分辨率。为了表示颜色，通常采用三个颜色分量，即图像可以表示为或包括三个像素点阵列。在RBG格式或颜色空间中，图像包括对应的红色、绿色和蓝色像素点阵列。但是，在视频编码中，每个像素通常以亮度/色度格式或颜色空间表示，例如YCbCr，包括Y指示的亮度分量(有时也用L表示)以及Cb、Cr表示的两个色度分量。亮度(luma)分量Y表示亮度或灰度水平强度(例如，在灰度等级图像中两者相同)，而两个色度(chrominance，简写为chroma)分量Cb和Cr表示色度或颜色信息分量。相应地，YCbCr格式的图像包括亮度像素点值(Y)的亮度像素点阵列和色度值(Cb和Cr)的两个色度像素点阵列。RGB格式的图像可以转换或变换为YCbCr格式，反之亦然，该过程也称为颜色变换或转换。如果图像是黑白的，则该图像可以只包括亮度像素点阵列。相应地，图像可以为例如单色格式的亮度像素点阵列或4:2:0、4:2:2和4:4:4彩色格式的亮度像素点阵列和两个相应的色度像素点阵列。
在一个实施例中，视频编码器20的实施例可包括图像分割单元(图2中未示出)，用于将图像17分割成多个(通常不重叠)图像块203。这些块在H.265/HEVC和VVC标准中也可以称为根块、宏块(H.264/AVC)或编码树块(coding tree block，CTB)，或编码树单元(coding tree unit，CTU)。分割单元可用于对视频序列中的所有图像使用相同的块大小和使用限定块大小的对应网格，或在图像或图像子集或图像组之间改变块大小，并将每个图像分割成对应块。
在其他实施例中，视频编码器可用于直接接收图像17的块203，例如，组成所述图像17的一个、几个或所有块。图像块203也可以称为当前图像块或待编码图像块。
与图像17一样，图像块203同样是或可认为是具有强度值(像素点值)的像素点组成的二维阵列或矩阵，但是图像块203的比图像17的小。换句话说，块203可包括一个像素点阵列(例如，单色图像17情况下的亮度阵列或彩色图像情况下的亮度阵列或色度阵列)或三个像素点阵列(例如，彩色图像17情况下的一个亮度阵列和两个色度阵列)或根据所采用的颜色格式的任何其他数量和/或类型的阵列。块203的水平方向和垂直方向(或轴线)上的像素点数量限定了块203的大小。相应地，块可以为M×N(M列×N行)个像素点阵列，或M×N个变换系数阵列等。
在一个实施例中，图2所示的视频编码器20用于逐块对图像17进行编码，例如，对每个块203执行编码和预测。
在一个实施例中，图2所示的视频编码器20还可以用于使用片(也称为视频片)分割和/或编码图像，其中图像可以使用一个或多个片(通常为不重叠的)进行分割或编码。每个片可包括一个或多个块(例如，编码树单元CTU)或一个或多个块组(例如H.265/HEVC/VVC标准中的编码区块(tile)和VVC标准中的砖(brick)。
在一个实施例中，图2所示的视频编码器20还可以用于使用片/编码区块组(也称为视频编码区块组)和/或编码区块(也称为视频编码区块)对图像进行分割和/或编码，其中图像可以使用一个或多个片/编码区块组(通常为不重叠的)进行分割或编码，每个片/编码区块组可包括一个或多个块(例如CTU)或一个或多个编码区块等，其中每个编码区块可以为矩形等形状，可包括一个或多个完整或部分块(例如CTU)。
残差计算
残差计算单元204用于通过如下方式根据图像块(或原始块)203和预测块265来计算残差块205(后续详细介绍了预测块265)：例如，逐个像素点(逐个像素)从图像块203的像素点值中减去预测块265的像素点值，得到像素域中的残差块205。
变换
变换处理单元206用于对残差块205的像素点值执行离散余弦变换(discrete cosine transform，DCT)或离散正弦变换(discrete sine transform，DST)等，得到变换域中的变换系数207。变换系数207也可称为变换残差系数，表示变换域中的残差块205。
变换处理单元206可用于应用DCT/DST的整数化近似，例如为H.265/HEVC指定的变换。与正交DCT变换相比，这种整数化近似通常由某一因子按比例缩放。为了维持经过正变换和逆变换处理的残差块的范数，使用其他比例缩放因子作为变换过程的一部分。比例缩放因子通常是根据某些约束条件来选择的，例如比例缩放因子是用于移位运算的2的幂、变换系数的位深度、准确性与实施成本之间的权衡等。例如，在编码器20侧通过逆变换处理单元212为逆变换(以及在解码器30侧通过例如逆变换处理单元312为对应逆变换)指定具体的比例缩放因子，以及相应地，可以在编码器20侧通过变换处理单元206为正变换指定对应比例缩放因子。
在一个实施例中，视频编码器20(对应地，变换处理单元206)可用于输出一种或多种变换的类型等变换参数，例如，直接输出或由熵编码单元270进行编码或压缩后输出，例如使得视频解码器30可接收并使用变换参数进行解码。
量化
量化单元208用于通过例如标量量化或矢量量化对变换系数207进行量化，得到量化变换系数209。量化变换系数209也可称为量化残差系数209。
量化过程可减少与部分或全部变换系数207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，可以应用不同程度的比例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。可通过量化参数(quantization parameter，QP)指示合适的量化步长。例如，量化参数可以为合适的量化步长的预定义集合的索引。例如，较小的量化参数可对应精细量化(较小量化步长)，较大的量化参数可对应粗糙量化(较大量化步长)，反之亦然。量化可包括除以量化步长，而反量化单元210等执行的对应或逆解量化可包括乘以量化步长。根据例如HEVC一些标准的实施例可用于使用量化参数来确定量化步长。一般而言，可以根据量化参数使用包含除法的等式的定点近似来计算量化步长。可以引入其他比例缩放因子来进行量化和解量化，以恢复可能由于在用于量化步长和量化参数的等式的定点近似中使用的比例而修改的残差块的范数。在一种示例性实现方式中，可以合并逆变换和解量化的比例。或者，可以使用自定义量化表并在比特流中等将其从编码器向解码器指示。量化是有损操作，其中量化步长越大，损耗越大。
在一个实施例中，视频编码器20(对应地，量化单元208)可用于输出量化参数(quantization parameter，QP)，例如，直接输出或由熵编码单元270进行编码或压缩后输出，例如使得视频解码器30可接收并使用量化参数进行解码。
反量化
反量化单元210用于对量化系数执行量化单元208的反量化，得到解量化系数211，例如，根据或使用与量化单元208相同的量化步长执行与量化单元208所执行的量化方案的反量化方案。解量化系数211也可称为解量化残差系数211，对应于变换系数207，但是由于量化造成损耗，反量化系数211通常与变换系数不完全相同。
逆变换
逆变换处理单元212用于执行变换处理单元206执行的变换的逆变换，例如，逆离散余弦变换(discrete cosine transform，DCT)或逆离散正弦变换(discrete sine transform，DST)，以在像素域中得到重建残差 块213(或对应的解量化系数213)。重建残差块213也可称为变换块213。
重建
重建单元214(例如，求和器214)用于将变换块213(即重建残差块213)添加到预测块265，以在像素域中得到重建块215，例如，将重建残差块213的像素点值和预测块265的像素点值相加。
滤波
环路滤波器单元220(或简称“环路滤波器”220)用于对重建块215进行滤波，得到滤波块221，或通常用于对重建像素点进行滤波以得到滤波像素点值。例如，环路滤波器单元用于顺利进行像素转变或提高视频质量。环路滤波器单元220可包括一个或多个环路滤波器，例如去块滤波器、像素点自适应偏移(sample-adaptive offset，SAO)滤波器或一个或多个其他滤波器，例如自适应环路滤波器(adaptive loop filter，ALF)、噪声抑制滤波器(noise suppression filter，NSF)或任意组合。例如，环路滤波器单元220可以包括去块滤波器、SAO滤波器和ALF滤波器。滤波过程的顺序可以是去块滤波器、SAO滤波器和ALF滤波器。再例如，增加一个称为具有色度缩放的亮度映射(luma mapping with chroma scaling，LMCS)(即自适应环内整形器)的过程。该过程在去块之前执行。再例如，去块滤波过程也可以应用于内部子块边缘，例如仿射子块边缘、ATMVP子块边缘、子块变换(sub-block transform，SBT)边缘和内子部分(intra sub-partition，ISP)边缘。尽管环路滤波器单元220在图2中示为环路滤波器，但在其他配置中，环路滤波器单元220可以实现为环后滤波器。滤波块221也可称为滤波重建块221。
在一个实施例中，视频编码器20(对应地，环路滤波器单元220)可用于输出环路滤波器参数(例如SAO滤波参数、ALF滤波参数或LMCS参数)，例如，直接输出或由熵编码单元270进行熵编码后输出，例如使得解码器30可接收并使用相同或不同的环路滤波器参数进行解码。
解码图像缓冲器
解码图像缓冲器(decoded picture buffer，DPB)230可以是存储参考图像数据以供视频编码器20在编码视频数据时使用的参考图像存储器。DPB 230可以由多种存储器设备中的任一种形成，例如动态随机存取存储器(dynamic random access memory，DRAM)，包括同步DRAM(synchronous DRAM，SDRAM)、磁阻RAM(magnetoresistive RAM，MRAM)、电阻RAM(resistive RAM，RRAM)或其他类型的存储设备。解码图像缓冲器230可用于存储一个或多个滤波块221。解码图像缓冲器230还可用于存储同一当前图像或例如之前的重建图像等不同图像的其他之前的滤波块，例如之前重建和滤波的块221，并可提供完整的之前重建即解码图像(和对应参考块和像素点)和/或部分重建的当前图像(和对应参考块和像素点)，例如用于帧间预测。解码图像缓冲器230还可用于存储一个或多个未经滤波的重建块215，或一般存储未经滤波的重建像素点，例如，未被环路滤波单元220滤波的重建块215，或未进行任何其他处理的重建块或重建像素点。
模式选择(分割和预测)
模式选择单元260包括分割单元262、帧间预测单元244和帧内预测单元254，用于从解码图像缓冲器230或其他缓冲器(例如，列缓冲器，图2中未显示)接收或获得原始块203(当前图像17的当前块203)和重建图像数据等原始图像数据，例如，同一(当前)图像和/或一个或多个之前解码图像的滤波和/或未经滤波的重建像素点或重建块。重建图像数据用作帧间预测或帧内预测等预测所需的参考图像数据，以得到预测块265或预测值265。
模式选择单元260可用于为当前块(包括不分割)和预测模式(例如帧内或帧间预测模式)确定或选择一种分割，生成对应的预测块265，以对残差块205进行计算和对重建块215进行重建。
在一个实施例中，模式选择单元260可用于选择分割和预测模式(例如，从模式选择单元260支持的或可用的预测模式中)，所述预测模式提供最佳匹配或者说最小残差(最小残差是指传输或存储中更好地压缩)，或者提供最小信令开销(最小信令开销是指传输或存储中更好地压缩)，或者同时考虑或平衡以上两者。模式选择单元260可用于根据码率失真优化(rate distortion Optimization，RDO)确定分割和预测模式，即选择提供最小码率失真优化的预测模式。本文“最佳”、“最低”、“最优”等术语不一定指总体上“最佳”、“最低”、“最优”的，但也可以指满足终止或选择标准的情况，例如，超过或低于阈值的值或其他限制可能导致“次优选择”，但会降低复杂度和处理时间。
换言之，分割单元262可用于将视频序列中的图像分割为编码树单元(coding tree unit，CTU)序列，CTU 203可进一步被分割成较小的块部分或子块(再次形成块)，例如，通过迭代使用四叉树(quad-tree partitioning，QT)分割、二叉树(binary-tree partitioning，BT)分割或三叉树(triple-tree partitioning，TT) 分割或其任意组合，并且用于例如对块部分或子块中的每一个执行预测，其中模式选择包括选择分割块203的树结构和选择应用于块部分或子块中的每一个的预测模式。
下文将详细地描述由视频编码器20执行的分割(例如，由分割单元262执行)和预测处理(例如，由帧间预测单元244和帧内预测单元254执行)。
分割
分割单元262可将一个图像块(或CTU)203分割(或划分)为较小的部分，例如正方形或矩形形状的小块。对于具有三个像素点阵列的图像，一个CTU由N×N个亮度像素点块和两个对应的色度像素点块组成。CTU中亮度块的最大允许大小在正在开发的通用视频编码(versatile video coding，VVC)标准中被指定为128×128，但是将来可指定为不同于128×128的值，例如256×256。图像的CTU可以集中/分组为片/编码区块组、编码区块或砖。一个编码区块覆盖着一个图像的矩形区域，一个编码区块可以分成一个或多个砖。一个砖由一个编码区块内的多个CTU行组成。没有分割为多个砖的编码区块可以称为砖。但是，砖是编码区块的真正子集，因此不称为编码区块。VVC支持两种编码区块组模式，分别为光栅扫描片/编码区块组模式和矩形片模式。在光栅扫描编码区块组模式，一个片/编码区块组包含一个图像的编码区块光栅扫描中的编码区块序列。在矩形片模式中，片包含一个图像的多个砖，这些砖共同组成图像的矩形区域。矩形片内的砖按照片的砖光栅扫描顺序排列。这些较小块(也可称为子块)可进一步分割为更小的部分。这也称为树分割或分层树分割，其中在根树级别0(层次级别0、深度0)等的根块可以递归的分割为两个或两个以上下一个较低树级别的块，例如树级别1(层次级别1、深度1)的节点。这些块可以又分割为两个或两个以上下一个较低级别的块，例如树级别2(层次级别2、深度2)等，直到分割结束(因为满足结束标准，例如达到最大树深度或最小块大小)。未进一步分割的块也称为树的叶块或叶节点。分割为两个部分的树称为二叉树(binary-tree，BT)，分割为三个部分的树称为三叉树(ternary-tree，TT)，分割为四个部分的树称为四叉树(quad-tree，QT)。
例如，编码树单元(CTU)可以为或包括亮度像素点的CTB、具有三个像素点阵列的图像的色度像素点的两个对应CTB、或单色图像的像素点的CTB或使用三个独立颜色平面和语法结构(用于编码像素点)编码的图像的像素点的CTB。相应地，编码树块(CTB)可以为N×N个像素点块，其中N可以设为某个值使得分量划分为CTB，这就是分割。编码单元(coding unit，CU)可以为或包括亮度像素点的编码块、具有三个像素点阵列的图像的色度像素点的两个对应编码块、或单色图像的像素点的编码块或使用三个独立颜色平面和语法结构(用于编码像素点)编码的图像的像素点的编码块。相应地，编码块(CB)可以为M×N个像素点块，其中M和N可以设为某个值使得CTB划分为编码块，这就是分割。
例如，在实施例中，根据HEVC可通过使用表示为编码树的四叉树结构将编码树单元(CTU)划分为多个CU。在叶CU级作出是否使用帧间(时间)预测或帧内(空间)预测对图像区域进行编码的决定。每个叶CU可以根据PU划分类型进一步划分为一个、两个或四个PU。一个PU内使用相同的预测过程，并以PU为单位向解码器传输相关信息。在根据PU划分类型应用预测过程得到残差块之后，可以根据类似于用于CU的编码树的其他四叉树结构将叶CU分割为变换单元(TU)。
例如，在实施例中，根据当前正在开发的最新视频编码标准(称为通用视频编码(VVC)，使用嵌套多类型树(例如二叉树和三叉树)的组合四叉树来划分用于分割编码树单元的分段结构。在编码树单元内的编码树结构中，CU可以为正方形或矩形。例如，编码树单元(CTU)首先由四叉树结构进行分割。四叉树叶节点进一步由多类型树结构分割。多类型树形结构有四种划分类型：垂直二叉树划分(SPLIT_BT_VER)、水平二叉树划分(SPLIT_BT_HOR)、垂直三叉树划分(SPLIT_TT_VER)和水平三叉树划分(SPLIT_TT_HOR)。多类型树叶节点称为编码单元(CU)，除非CU对于最大变换长度而言太大，这样的分段用于预测和变换处理，无需其他任何分割。在大多数情况下，这表示CU、PU和TU在四叉树嵌套多类型树的编码块结构中的块大小相同。当最大支持变换长度小于CU的彩色分量的宽度或高度时，就会出现该异常。VVC制定了具有四叉树嵌套多类型树的编码结构中的分割划分信息的唯一信令机制。在信令机制中，编码树单元(CTU)作为四叉树的根首先被四叉树结构分割。然后每个四叉树叶节点(当足够大可以被)被进一步分割为一个多类型树结构。在多类型树结构中，通过第一标识(mtt_split_cu_flag)指示节点是否进一步分割，当对节点进一步分割时，先用第二标识(mtt_split_cu_vertical_flag)指示划分方向，再用第三标识(mtt_split_cu_binary_flag)指示划分是二叉树划分或三叉树划分。根据mtt_split_cu_vertical_flag和mtt_split_cu_binary_flag的值，解码器可以基于预定义规则或表格推导出CU的多类型树划分模式(MttSplitMode)。需要说明的是，对于某种设计，例如VVC 硬件解码器中的64×64的亮度块和32×32的色度流水线设计，当亮度编码块的宽度或高度大于64时，不允许进行TT划分。当色度编码块的宽度或高度大于32时，也不允许TT划分。流水线设计将图像分为多个虚拟流水线数据单元(virtual pipeline data unit，VPDU)，每个VPDU在图像中定义为互不重叠的单元。在硬件解码器中，连续的VPDU在多个流水线阶段同时处理。在大多数流水线阶段，VPDU大小与缓冲器大小大致成正比，因此需要保持较小的VPDU。在大多数硬件解码器中，VPDU大小可以设置为最大变换块(transform block，TB)大小。但是，在VVC中，三叉树(TT)和二叉树(BT)的分割可能会增加VPDU的大小。
另外，需要说明的是，当树节点块的一部分超出底部或图像右边界时，强制对该树节点块进行划分，直到每个编码CU的所有像素点都位于图像边界内。
例如，所述帧内子分割(intra sub-partitions，ISP)工具可以根据块大小将亮度帧内预测块垂直或水平的分为两个或四个子部分。
在一个示例中，视频编码器20的模式选择单元260可以用于执行上文描述的分割技术的任意组合。
如上所述，视频编码器20用于从(预定的)预测模式集合中确定或选择最好或最优的预测模式。预测模式集合可包括例如帧内预测模式和/或帧间预测模式。
帧内预测
帧内预测模式集合可包括35种不同的帧内预测模式，例如，像DC(或均值)模式和平面模式的非方向性模式，或如HEVC定义的方向性模式，或者可包括67种不同的帧内预测模式，例如，像DC(或均值)模式和平面模式的非方向性模式，或如VVC中定义的方向性模式。例如，若干传统角度帧内预测模式自适应地替换为VVC中定义的非正方形块的广角帧内预测模式。又例如，为了避免DC预测的除法运算，仅使用较长边来计算非正方形块的平均值。并且，平面模式的帧内预测结果还可以使用位置决定的帧内预测组合(position dependent intra prediction combination，PDPC)方法修改。
帧内预测单元254用于根据帧内预测模式集合中的帧内预测模式使用同一当前图像的相邻块地重建像素点来生成帧内预测块265。
帧内预测单元254(或通常为模式选择单元260)还用于输出帧内预测参数(或通常为指示块的选定帧内预测模式的信息)以语法元素266的形式发送到熵编码单元270，以包含到编码图像数据21中，从而视频解码器30可执行操作，例如接收并使用用于解码的预测参数。
HEVC中的帧内预测模式包括直流预测模式，平面预测模式和33种角度预测模式，共计35个候选预测模式。当前块可以使用左侧和上方已重建图像块的像素作为参考进行帧内预测。当前块的周边区域中用来对当前块进行帧内预测的图像块成为参考块，参考块中的像素称为参考像素。35个候选预测模式中，直流预测模式适用于当前块中纹理平坦的区域，该区域中所有像素均使用参考块中的参考像素的平均值作为预测；平面预测模式适用于纹理平滑变化的图像块，符合该条件的当前块使用参考块中的参考像素进行双线性插值作为当前块中的所有像素的预测；角度预测模式利用当前块的纹理与相邻已重建图像块的纹理高度相关的特性，沿某一角度复制对应的参考块中的参考像素的值作为当前块中的所有像素的预测。
HEVC编码器给当前块从35个候选预测模式中选择一个最优帧内预测模式，并将该最优帧内预测模式写入视频码流。为提升帧内预测的编码效率，编码器/解码器会从周边区域中、采用帧内预测的已重建图像块各自的最优帧内预测模式中推导出3个最可能模式，如果给当前块选择的最优帧内预测模式是这3个最可能模式的其中之一，则编码一个第一索引指示所选择的最优帧内预测模式是这3个最可能模式的其中之一；如果选中的最优帧内预测模式不是这3个最可能模式，则编码一个第二索引指示所选择的最优帧内预测模式是其他32个模式(35个候选预测模式中除前述3个最可能模式外的其他模式)的其中之一。HEVC标准使用5比特的定长码作为前述第二索引。
HEVC编码器推导出3个最可能模式的方法包括：选取当前块的左相邻图像块和上相邻图像块的最优帧内预测模式放入集合，如果这两个最优帧内预测模式相同，则集合中只保留一个即可。如果这两个最优帧内预测模式相同且均为角度预测模式，则再选取与该角度方向邻近的两个角度预测模式加入集合；否则，依次选择平面预测模式、直流模式和竖直预测模式加入集合，直到集合中的模式数量达到3。
HEVC解码器对码流做熵解码后，获得当前块的模式信息，该模式信息包括指示当前块的最优帧内预测模式是否在3个最可能模式中的指示标识，以及当前块的最优帧内预测模式在3个最可能模式中的索引或者当前块的最优帧内预测模式在其他32个模式中的索引。
帧间预测
在可能的实现中，帧间预测模式集合取决于可用参考图像(即，例如前述存储在DBP 230中的至少部分之前解码的图像)和其他帧间预测参数，例如取决于是否使用整个参考图像或只使用参考图像的一部分，例如当前块的区域附近的搜索窗口区域，来搜索最佳匹配参考块，和/或例如取决于是否执行半像素、四分之一像素和/或16分之一内插的像素内插。
除上述预测模式外，还可以采用跳过模式和/或直接模式。
例如，扩展合并预测，这个模式的合并候选列表由以下五个候选类型按顺序组成：来自空间相邻CU的空间MVP、来自并置CU的时间MVP、来自FIFO表的基于历史的MVP、成对平均MVP和零MV。可以使用基于双边匹配的解码器侧运动矢量修正(decoder side motion vector refinement，DMVR)来增加合并模式的MV的准确度。带有MVD的合并模式(merge mode with MVD，MMVD)来自有运动矢量差异的合并模式。在发送跳过标志和合并标志之后立即发送MMVD标志，以指定CU是否使用MMVD模式。可以使用CU级自适应运动矢量分辨率(adaptive motion vector resolution，AMVR)方案。AMVR支持CU的MVD以不同的精度进行编码。根据当前CU的预测模式，自适应地选择当前CU的MVD。当CU以合并模式进行编码时，可以将合并的帧间/帧内预测(combined inter/intra prediction，CIIP)模式应用于当前CU。对帧间和帧内预测信号进行加权平均，得到CIIP预测。对于仿射运动补偿预测，通过2个控制点(4参数)或3个控制点(6参数)运动矢量的运动信息来描述块的仿射运动场。基于子块的时间运动矢量预测(subblock-based temporal motion vector prediction，SbTMVP)，与HEVC中的时间运动矢量预测(temporal motion vector prediction，TMVP)类似，但预测的是当前CU内的子CU的运动矢量。双向光流(bi-directional optical flow，BDOF)以前称为BIO，是一种减少计算的简化版本，特别是在乘法次数和乘数大小方面的计算。在三角形分割模式中，CU以对角线划分和反对角线划分两种划分方式被均匀划分为两个三角形部分。此外，双向预测模式在简单平均的基础上进行了扩展，以支持两个预测信号的加权平均。
帧间预测单元244可包括运动估计(motion estimation，ME)单元和运动补偿(motion compensation，MC)单元(两者在图2中未示出)。运动估计单元可用于接收或获取图像块203(当前图像17的当前图像块203)和解码图像231，或至少一个或多个之前重建块，例如，一个或多个其他/不同之前解码图像231的重建块，来进行运动估计。例如，视频序列可包括当前图像和之前的解码图像231，或换句话说，当前图像和之前的解码图像231可以为形成视频序列的图像序列的一部分或形成该图像序列。
例如，编码器20可用于从多个其他图像中的同一或不同图像的多个参考块中选择参考块，并将参考图像(或参考图像索引)和/或参考块的位置(x、y坐标)与当前块的位置之间的偏移(空间偏移)作为帧间预测参数提供给运动估计单元。该偏移也称为运动矢量(motion vector，MV)。
运动补偿单元用于获取，例如接收，帧间预测参数，并根据或使用该帧间预测参数执行帧间预测，得到帧间预测块246。由运动补偿单元执行的运动补偿可能包含根据通过运动估计确定的运动/块矢量来提取或生成预测块，还可能包括对子像素精度执行内插。内插滤波可从已知像素的像素点中产生其他像素的像素点，从而潜在地增加可用于对图像块进行编码的候选预测块的数量。一旦接收到当前图像块的PU对应的运动矢量时，运动补偿单元可在其中一个参考图像列表中定位运动矢量指向的预测块。
运动补偿单元还可以生成与块和视频片相关的语法元素，以供视频解码器30在解码视频片的图像块时使用。此外，或者作为片和相应语法元素的替代，可以生成或使用编码区块组和/或编码区块以及相应语法元素。
在获取先进的运动矢量预测(advanced motion vector prediction，AMVP)模式中的候选运动矢量列表的过程中，作为备选可以加入候选运动矢量列表的运动矢量(motion vector，MV)包括当前块的空域相邻和时域相邻的图像块的MV，其中空域相邻的图像块的MV又可以包括位于当前块左侧的左方候选图像块的MV和位于当前块上方的上方候选图像块的MV。示例性的，请参考图4，图4为本申请实施例提供的候选图像块的一种示例性的示意图，如图4所示，左方候选图像块的集合包括{A0，A1}，上方候选图像块的集合包括{B0，B1，B2}，时域相邻的候选图像块的集合包括{C，T}，这三个集合均可以作为备选被加入到候选运动矢量列表中，但是根据现有编码标准，AMVP的候选运动矢量列表的最大长度为2，因此需要根据规定的顺序从三个集合中确定在候选运动矢量列表中加入最多两个图像块的MV。该顺序可以是优先考虑当前块的左方候选图像块的集合{A0，A1}(先考虑A0，A0不可得再考虑A1)，其次考虑当前块的上方候选图像块的集合{B0，B1，B2}(先考虑B0，B0不可得再考虑B1，B1不可得再考虑B2)，最后考虑当前块的时域相邻的候选图像块的集合{C，T}(先考虑T，T不可得再考虑C)。
得到上述候选运动矢量列表后，通过率失真代价(rate distortion cost，RD cost)从候选运动矢量列表 中确定最优的MV，将RD cost最小的候选运动矢量作为当前块的运动矢量预测值(motion vector predictor，MVP)。率失真代价由以下公式计算获得：
J＝SAD+λR
其中，J表示RD cost，SAD为使用候选运动矢量进行运动估计后得到的预测块的像素值与当前块的像素值之间的绝对误差和(sum of absolute differences，SAD)，R表示码率，λ表示拉格朗日乘子。
编码端将确定出的MVP在候选运动矢量列表中的索引传递到解码端。进一步地，可以在MVP为中心的邻域内进行运动搜索获得当前块实际的运动矢量，编码端计算MVP与实际的运动矢量之间的运动矢量差值(motion vector difference，MVD)，并将MVD也传递到解码端。解码端解析索引，根据该索引在候选运动矢量列表中找到对应的MVP，解析MVD，将MVD与MVP相加得到当前块实际的运动矢量。
在获取融合(Merge)模式中的候选运动信息列表的过程中，作为备选可以加入候选运动信息列表的运动信息包括当前块的空域相邻或时域相邻的图像块的运动信息，其中空域相邻的图像块和时域相邻的图像块可参照图4，候选运动信息列表中对应于空域的候选运动信息来自于空间相邻的5个块(A0、A1、B0、B1和B2)，若空域相邻块不可得或者为帧内预测，则其运动信息不加入候选运动信息列表。当前块的时域的候选运动信息根据参考帧和当前帧的图序计数(picture order count，POC)对参考帧中对应位置块的MV进行缩放后获得，先判断参考帧中位置为T的块是否可得，若不可得则选择位置为C的块。得到上述候选运动信息列表后，通过RD cost从候选运动信息列表中确定最优的运动信息作为当前块的运动信息。编码端将最优的运动信息在候选运动信息列表中位置的索引值(记为merge index)传递到解码端。
熵编码
熵编码单元270用于将熵编码算法或方案(例如，可变长度编码(variable length coding，VLC)方案、上下文自适应VLC方案(context adaptive VLC，CALVC)、算术编码方案、二值化算法、上下文自适应二进制算术编码(context adaptive binary arithmetic coding，CABAC)、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)、概率区间分割熵(probability interval partitioning entropy，PIPE)编码或其他熵编码方法或技术)应用于量化残差系数209、帧间预测参数、帧内预测参数、环路滤波器参数和/或其他语法元素，得到可以通过输出端272以编码比特流21等形式输出的编码图像数据21，使得视频解码器30等可以接收并使用用于解码的参数。可将编码比特流21传输到视频解码器30，或将其保存在存储器中稍后由视频解码器30传输或检索。
视频编码器20的其他结构变体可用于对视频流进行编码。例如，基于非变换的编码器20可以在某些块或帧没有变换处理单元206的情况下直接量化残差信号。在另一种实现方式中，编码器20可以具有组合成单个单元的量化单元208和反量化单元210。
解码器和解码方法
如图3所示，视频解码器30用于接收例如由编码器20编码的编码图像数据21(例如编码比特流21)，得到解码图像331。编码图像数据或比特流包括用于解码所述编码图像数据的信息，例如表示编码视频片(和/或编码区块组或编码区块)的图像块的数据和相关的语法元素。
在图3的示例中，解码器30包括熵解码单元304、反量化单元310、逆变换处理单元312、重建单元314(例如求和器314)、环路滤波器320、解码图像缓冲器(DBP)330、模式应用单元360、帧间预测单元344和帧内预测单元354。帧间预测单元344可以为或包括运动补偿单元。在一些示例中，视频解码器30可执行大体上与参照图2的视频编码器100描述的编码过程相反的解码过程。
如编码器20所述，反量化单元210、逆变换处理单元212、重建单元214、环路滤波器220、解码图像缓冲器DPB230、帧间预测单元344和帧内预测单元354还组成视频编码器20的“内置解码器”。相应地，反量化单元310在功能上可与反量化单元110相同，逆变换处理单元312在功能上可与逆变换处理单元122相同，重建单元314在功能上可与重建单元214相同，环路滤波器320在功能上可与环路滤波器220相同，解码图像缓冲器330在功能上可与解码图像缓冲器230相同。因此，视频编码器20的相应单元和功能的解释相应地适用于视频解码器30的相应单元和功能。
熵解码
熵解码单元304用于解析比特流21(或一般为编码图像数据21)并对编码图像数据21执行熵解码，得到量化系数309和/或解码后的编码参数(图3中未示出)等，例如帧间预测参数(例如参考图像索引和运动矢量)、帧内预测参数(例如帧内预测模式或索引)、变换参数、量化参数、环路滤波器参数和/或其他语法元素等中的任一个或全部。熵解码单元304可用于应用编码器20的熵编码单元270的编码方案对 应的解码算法或方案。熵解码单元304还可用于向模式应用单元360提供帧间预测参数、帧内预测参数和/或其他语法元素，以及向解码器30的其他单元提供其他参数。视频解码器30可以接收视频片和/或视频块级的语法元素。此外，或者作为片和相应语法元素的替代，可以接收或使用编码区块组和/或编码区块以及相应语法元素。
反量化
反量化单元310可用于从编码图像数据21(例如通过熵解码单元304解析和/或解码)接收量化参数(quantization parameter，QP)(或一般为与反量化相关的信息)和量化系数，并基于所述量化参数对所述解码的量化系数309进行反量化以获得反量化系数311，所述反量化系数311也可以称为变换系数311。反量化过程可包括使用视频编码器20为视频片中的每个视频块计算的量化参数来确定量化程度，同样也确定需要执行的反量化的程度。
逆变换
逆变换处理单元312可用于接收解量化系数311，也称为变换系数311，并对解量化系数311应用变换以得到像素域中的重建残差块213。重建残差块213也可称为变换块313。变换可以为逆变换，例如逆DCT、逆DST、逆整数变换或概念上类似的逆变换过程。逆变换处理单元312还可以用于从编码图像数据21(例如通过熵解码单元304解析和/或解码)接收变换参数或相应信息，以确定应用于解量化系数311的变换。
重建
重建单元314(例如，求和器314)用于将重建残差块313添加到预测块365，以在像素域中得到重建块315，例如，将重建残差块313的像素点值和预测块365的像素点值相加。
滤波
环路滤波器单元320(在编码环路中或之后)用于对重建块315进行滤波，得到滤波块321，从而顺利进行像素转变或提高视频质量等。环路滤波器单元320可包括一个或多个环路滤波器，例如去块滤波器、像素点自适应偏移(sample-adaptive offset，SAO)滤波器或一个或多个其他滤波器，例如自适应环路滤波器(adaptive loop filter，ALF)、噪声抑制滤波器(noise suppression filter，NSF)或任意组合。例如，环路滤波器单元220可以包括去块滤波器、SAO滤波器和ALF滤波器。滤波过程的顺序可以是去块滤波器、SAO滤波器和ALF滤波器。再例如，增加一个称为具有色度缩放的亮度映射(luma mapping with chroma scaling，LMCS)(即自适应环内整形器)的过程。该过程在去块之前执行。再例如，去块滤波过程也可以应用于内部子块边缘，例如仿射子块边缘、ATMVP子块边缘、子块变换(sub-block transform，SBT)边缘和内子部分(intra sub-partition，ISP)边缘。尽管环路滤波器单元320在图3中示为环路滤波器，但在其他配置中，环路滤波器单元320可以实现为环后滤波器。
解码图像缓冲器
随后将一个图像中的解码视频块321存储在解码图像缓冲器330中，解码图像缓冲器330存储作为参考图像的解码图像331，参考图像用于其他图像和/或分别输出显示的后续运动补偿。
解码器30用于通过输出端312等输出解码图像311，向用户显示或供用户查看。
预测
帧间预测单元344在功能上可与帧间预测单元244(特别是运动补偿单元)相同，帧内预测单元354在功能上可与帧间预测单元254相同，并基于从编码图像数据21(例如通过熵解码单元304解析和/或解码)接收的分割和/或预测参数或相应信息决定划分或分割和执行预测。模式应用单元360可用于根据重建图像、块或相应的像素点(已滤波或未滤波)执行每个块的预测(帧内或帧间预测)，得到预测块365。
当将视频片编码为帧内编码(intra coded，I)片时，模式应用单元360中的帧内预测单元354用于根据指示的帧内预测模式和来自当前图像的之前解码块的数据生成用于当前视频片的图像块的预测块365。当视频图像编码为帧间编码(即，B或P)片时，模式应用单元360中的帧间预测单元344(例如运动补偿单元)用于根据运动矢量和从熵解码单元304接收的其他语法元素生成用于当前视频片的视频块的预测块365。对于帧间预测，可从其中一个参考图像列表中的其中一个参考图像产生这些预测块。视频解码器30可以根据存储在DPB 330中的参考图像，使用默认构建技术来构建参考帧列表0和列表1。除了片(例如视频片)或作为片的替代，相同或类似的过程可应用于编码区块组(例如视频编码区块组)和/或编码区块(例如视频编码区块)的实施例，例如视频可以使用I、P或B编码区块组和/或编码区块进行编码。
模式应用单元360用于通过解析运动矢量和其他语法元素，确定用于当前视频片的视频块的预测信息， 并使用预测信息产生用于正在解码的当前视频块的预测块。例如，模式应用单元360使用接收到的一些语法元素确定用于编码视频片的视频块的预测模式(例如帧内预测或帧间预测)、帧间预测片类型(例如B片、P片或GPB片)、用于片的一个或多个参考图像列表的构建信息、用于片的每个帧间编码视频块的运动矢量、用于片的每个帧间编码视频块的帧间预测状态、其他信息，以解码当前视频片内的视频块。除了片(例如视频片)或作为片的替代，相同或类似的过程可应用于编码区块组(例如视频编码区块组)和/或编码区块(例如视频编码区块)的实施例，例如视频可以使用I、P或B编码区块组和/或编码区块进行编码。
在一个实施例中，图3的视频编码器30还可以用于使用片(也称为视频片)分割和/或解码图像，其中图像可以使用一个或多个片(通常为不重叠的)进行分割或解码。每个片可包括一个或多个块(例如CTU)或一个或多个块组(例如H.265/HEVC/VVC标准中的编码区块和VVC标准中的砖。
在一个实施例中，图3所示的视频解码器30还可以用于使用片/编码区块组(也称为视频编码区块组)和/或编码区块(也称为视频编码区块)对图像进行分割和/或解码，其中图像可以使用一个或多个片/编码区块组(通常为不重叠的)进行分割或解码，每个片/编码区块组可包括一个或多个块(例如CTU)或一个或多个编码区块等，其中每个编码区块可以为矩形等形状，可包括一个或多个完整或部分块(例如CTU)。
视频解码器30的其他变型可用于对编码图像数据21进行解码。例如，解码器30可以在没有环路滤波器单元320的情况下产生输出视频流。例如，基于非变换的解码器30可以在某些块或帧没有逆变换处理单元312的情况下直接反量化残差信号。在另一种实现方式中，视频解码器30可以具有组合成单个单元的反量化单元310和逆变换处理单元312。
应理解，在编码器20和解码器30中，可以对当前步骤的处理结果进一步处理，然后输出到下一步骤。例如，在插值滤波、运动矢量推导或环路滤波之后，可以对插值滤波、运动矢量推导或环路滤波的处理结果进行进一步的运算，例如裁剪(clip)或移位(shift)运算。
应该注意的是，可以对当前块的推导运动矢量(包括但不限于仿射模式的控制点运动矢量、仿射、平面、ATMVP模式的子块运动矢量、时间运动矢量等)进行进一步运算。例如，根据运动矢量的表示位将运动矢量的值限制在预定义范围。如果运动矢量的表示位为bitDepth，则范围为-2^(bitDepth-1)至2^(bitDepth-1)-1，其中“^”表示幂次方。例如，如果bitDepth设置为16，则范围为-32768～32767；如果bitDepth设置为18，则范围为-131072～131071。例如，推导运动矢量的值(例如一个8×8块中的4个4×4子块的MV)被限制，使得所述4个4×4子块MV的整数部分之间的最大差值不超过N个像素，例如不超过1个像素。这里提供了两种根据bitDepth限制运动矢量的方法。
尽管上述实施例主要描述了视频编解码，但应注意的是，译码系统10、编码器20和解码器30的实施例以及本文描述的其他实施例也可以用于静止图像处理或编解码，即视频编解码中独立于任何先前或连续图像的单个图像的处理或编解码。一般情况下，如果图像处理仅限于单个图像17，帧间预测单元244(编码器)和帧间预测单元344(解码器)可能不可用。视频编码器20和视频解码器30的所有其他功能(也称为工具或技术)同样可用于静态图像处理，例如残差计算204/304、变换206、量化208、反量化210/310、(逆)变换212/312、分割262/362、帧内预测254/354和/或环路滤波220/320、熵编码270和熵解码304。
请参考图5，图5为本申请实施例提供的视频译码设备500的一种示例性框图。视频译码设备500适用于实现本文描述的公开实施例。在一个实施例中，视频译码设备500可以是解码器，例如图1a中的视频解码器30，也可以是编码器，例如图1a中的视频编码器20。
视频译码设备500包括：用于接收数据的入端口510(或输入端口510)和接收单元(receiver unit，Rx)520；用于处理数据的处理器、逻辑单元或中央处理器(central processing unit，CPU)530；例如，这里的处理器530可以是神经网络处理器530；用于传输数据的发送单元(transmitter unit，Tx)540和出端口550(或输出端口550)；用于存储数据的存储器560。视频译码设备500还可包括耦合到入端口510、接收单元520、发送单元540和出端口550的光电(optical-to-electrical，OE)组件和电光(electrical-to-optical，EO)组件，用于光信号或电信号的出口或入口。
处理器530通过硬件和软件实现。处理器530可实现为一个或多个处理器芯片、核(例如，多核处理器)、FPGA、ASIC和DSP。处理器530与入端口510、接收单元520、发送单元540、出端口550和存储器560通信。处理器530包括译码模块570(例如，基于神经网络的译码模块570)。译码模块570实施上文所公开的实施例。例如，译码模块570执行、处理、准备或提供各种编码操作。因此，通过译码模块570为视频译码设备500的功能提供了实质性的改进，并且影响了视频译码设备500到不同状态的切换。 或者，以存储在存储器560中并由处理器530执行的指令来实现译码模块570。
存储器560包括一个或多个磁盘、磁带机和固态硬盘，可以用作溢出数据存储设备，用于在选择执行程序时存储此类程序，并且存储在程序执行过程中读取的指令和数据。存储器560可以是易失性和/或非易失性的，可以是只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、三态内容寻址存储器(ternary content-addressable memory，TCAM)和/或静态随机存取存储器(static random-access memory，SRAM)。
请参考图6，图6为本申请实施例提供的装置600的一种示例性框图，装置600可用作图1a中的源设备12和目的设备14中的任一个或两个。
装置600中的处理器602可以是中央处理器。或者，处理器602可以是现有的或今后将研发出的能够操控或处理信息的任何其他类型设备或多个设备。虽然可以使用如图所示的处理器602等单个处理器来实施已公开的实现方式，但使用一个以上的处理器速度更快和效率更高。
在一种实现方式中，装置600中的存储器604可以是只读存储器(ROM)设备或随机存取存储器(RAM)设备。任何其他合适类型的存储设备都可以用作存储器604。存储器604可以包括处理器602通过总线612访问的代码和数据606。存储器604还可包括操作系统608和应用程序610，应用程序610包括允许处理器602执行本文所述方法的至少一个程序。例如，应用程序610可以包括应用1至N，还包括执行本文所述方法的视频译码应用。
装置600还可以包括一个或多个输出设备，例如显示器618。在一个示例中，显示器618可以是将显示器与可用于感测触摸输入的触敏元件组合的触敏显示器。显示器618可以通过总线612耦合到处理器602。
虽然装置600中的总线612在本文中描述为单个总线，但是总线612可以包括多个总线。此外，辅助储存器可以直接耦合到装置600的其他组件或通过网络访问，并且可以包括存储卡等单个集成单元或多个存储卡等多个单元。因此，装置600可以具有各种各样的配置。
请参考图7，图7为本申请实施例提供的一种编码方法。如图7所示，该编码方法可以包括：
S701、获取待编码图像块。
示例性地，可以将待编码图像划分为多个连续的图像块(编码块)，上述待编码图像块可以为上述多个图像块中的任意图像块。
S702、根据多个预测模式确定待编码图像块的编码复杂度。
其中，上述多个预测模式包括块级预测、点级预测和帧内块复制(IBC)预测中的至少一项。上述编码复杂度用于表征上述待编码图像块编码难度
在一种可能的实现方式中，可以根据上述多个预测模式对上述待编码图像块进行预测操作得到上述待编码图像块与每一预测模式对应的预测残差。然后根据上述预测残差确定上述待编码图像块与每一预测模式对应的目标参数。之后根据上述目标参数确定上述待编码图像块的编码复杂度。
其中，上述目标参数包括绝对误差和(Sum of Absolute Difference，SAD)、绝对变换差之和((Sum of Absolute Transformed Difference，SATD)或无损编码比特数中的至少一项。上述预测操作可以是基于原始或重建像素进行预测。
示例性地，如图8所示，可以通过块级预测、点级预测和帧内块复制预测分别对待编码图像块进行预测操作得到上述待编码图像块与块级预测对应的预测块，上述待编码图像块与块级预测对应的预测块和上述待编码图像块与帧内块复制对应的预测块。
然后计算上述待编码图像块预测块与待编码图像块的原始块的差值得到上述待编码图像块与块级预测对应的预测残差(预测残差1)、上述待编码图像块与块级预测对应的预测残差(预测残差2)和上述待编码图像块与帧内块复制对应的预测残差(预测残差3)。
再然后根据预测残差确定上述待编码图像块与每一预测模式对应的目标参数(绝对误差和、绝对变换差之和或无损编码比特数)。即根据预测残差1确定目标参数1、根据预测残差2确定目标参数2和根据预测残差3确定目标参数3。
之后根据上述待编码图像块与每一预测模式对应的目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，可以根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定上述待编码图像块的编码复杂度。
其中，上述目标绝对误差为上述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，上述绝对变换差之和为上述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和， 上述目标无损编码比特数为上述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
示例性地，对待编码图像块分别进行块级预测、点级预测和帧内块复制预测得到待编码图像块与块级预测对应的绝对误差、待编码图像块与块点级预测对应的绝对误差和待编码图像块与帧内块复制预测对应的绝对误差。然后将块级预测对应的绝对误差、待编码图像块与块点级预测对应的绝对误差和待编码图像块与帧内块复制预测对应的绝对误差中最小的绝对误差作为目标绝对误差。之后通过目标绝对误差和预设绝对误差数值范围进行比较确定待编码图像块的编码复杂度。其中，预设绝对误差数值范围包括多个数值范围，多个数值范围与多个编码复杂度(即编码复杂度等级)一一对应。
在一种可能的实现方式中，可以根据上述待编码图像块与每一预测模式对应的目标参数确定上述待编码图像块与每一预测模式对应的编码复杂度，然后根据上述待编码图像块与每一预测模式对应的编码复杂度确定待编码图像块的编码复杂度。
示例性地，对待编码图像块分别进行块级预测、点级预测和帧内块复制预测得到待编码图像块与块级预测对应的绝对变换差之和、待编码图像块与块点级预测对应的绝对变换差之和以及待编码图像块与帧内块复制预测对应的绝对变换差之和。
然后分别将点级预测和帧内块复制预测得到待编码图像块与块级预测对应的绝对变换差之和、待编码图像块与块点级预测对应的绝对变换差之和以及待编码图像块与帧内块复制预测对应的绝对变换差之和与预设绝对变换差之和数值范围进行比较确定待编码图像块与块级预测对应的编码复杂度、待编码图像块与块点级预测对应的编码复杂度以及待编码图像块与帧内块复制预测对应的编码复杂度。其中，预设绝对变换差之和数值范围包括多个数值范围，多个数值范围与多个编码复杂度(即编码复杂度等级)一一对应
之后对待编码图像块与块级预测对应的编码复杂度、待编码图像块与块点级预测对应的编码复杂度以及待编码图像块与帧内块复制预测对应的编码复杂度进行处理(如选取最小编码复杂度、对编码复杂度加权求和等处理)得到待编码图像块的编码复杂度(即编码复杂度等级)。
在另一种可能的实现方式中，可以根据上述目标参数确定上述待编码图像块的第一编码复杂度。将上述待编码图像块划分为多个子块。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
示例性地，如图9所示，一方面可以通过块级预测、点级预测和帧内块复制预测分别对待编码图像块进行预测操作得到上述待编码图像块与块级预测对应的预测块，上述待编码图像块与块级预测对应的预测块和上述待编码图像块与帧内块复制对应的预测块。
然后计算上述待编码图像块预测块与待编码图像块的原始块的差值得到上述待编码图像块与块级预测对应的预测残差(预测残差1)、上述待编码图像块与块级预测对应的预测残差(预测残差2)和上述待编码图像块与帧内块复制对应的预测残差(预测残差3)。
再然后根据预测残差确定上述待编码图像块与每一预测模式对应的目标参数(绝对误差和、绝对变换差之和或无损编码比特数)。
之后根据上述待编码图像块与每一预测模式对应的目标参数确定上述待编码图像块的第一编码复杂度。
另一方面将待编码图像块划分为多个子块。假设待编码图像块尺寸为W×H，其中W为图像块的宽，H为图像块的高，在本申请实施例中，可以将待编码图像块划分为N个(W/N)×H尺寸的子块。
然后进行水平和垂直差值计算，即对于每个子块，从水平和竖直两个方向逐步计算相邻像素值的差值，得到子块的水平差值块和垂直差值块。
之后计算每个子块的第二编码复杂度。对每个子块的水平差值块和垂直差值块分别求SAD值，得到每个子块的水平复杂度值和垂直复杂度值，将水平复杂度值和垂直复杂度值分别和预设绝对误差和数值范围进行比较，得到该子块的第二编码复杂度(第二编码复杂度等级)。
然后对待编码图像的多个子块的第二编码复杂度进行处理(如选取最小编码复杂度、对编码复杂度加权求和等处理)得到待编码图像的第二编码复杂度
最后对待编码图像的第一编码复杂度和待编码图像的第二编码复杂度进行处理(如选取最小编码复杂度、对编码复杂度加权求和等处理)得到待编码图像的编码复杂度。
在另一种可能的实现方式中，可以将上述待编码图像块划分为多个子块。根据上述多个预测模式对上 述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据上述预测残差确定上述每一子块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
示例性地，如图10所示，可以将待编码图像块划分为N个子块，通过块级预测、点级预测和帧内块复制预测分别对每个子块预测操作得到每一子块与每一预测模式对应的预测残差。根据上述预测残差确定上述每一子块与每一预测模式对应的目标参数。最后根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，可以根据上述目标参数确定上述每一子块的编码复杂度。根据上述每一子块的编码复杂度确定上述待编码图像块的编码复杂度。
示例性地，可以根据上述目标参数确定待编码图像的每一子块的编码复杂度，然后对每一子块的编码复杂度进行处理(如选取最小编码复杂度、对编码复杂度加权求和等处理)得到待编码图像的编码复杂度。
在另一种可能的实现方式中，可以根据上述目标参数确定上述待编码图像块的第一编码复杂度。然后确定上述多个子块中每一子块的水平差值块和垂直差值块。之后根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度
示例性地，如图11所示，可以将待编码图像块划分为N个子块。
一方面，通过块级预测、点级预测和帧内块复制预测分别对每个子块预测操作得到每一子块与每一预测模式对应的预测残差。
然后根据上述预测残差确定上述每一子块与每一预测模式对应的目标参数。
最后根据上述目标参数确定上述待编码图像块的第一编码复杂度。
另一方面，对每个子块进行水平和垂直差值计算，即对于每个子块，从水平和竖直两个方向逐步计算相邻像素值的差值，得到子块的水平差值块和垂直差值块。
之后计算每个子块的第二编码复杂度。对每个子块的水平差值块和垂直差值块分别求SAD值，得到每个子块的水平复杂度值和垂直复杂度值，将水平复杂度值和垂直复杂度值分别和预设绝对误差和数值范围进行比较，得到该子块的第二编码复杂度(第二编码复杂度等级)。
然后对待编码图像的多个子块的第二编码复杂度进行处理(如选取最小编码复杂度、对编码复杂度加权求和等处理)得到待编码图像的第二编码复杂度
最后对待编码图像的第一编码复杂度和待编码图像的第二编码复杂度进行处理(如选取最小编码复杂度、对编码复杂度加权求和等处理)得到待编码图像的编码复杂度。
在一种可能的实现方式中，上述将待编码图像划分为多个子块具体可以为：假设当前图像块(即待编码图像)尺寸为W×H，其中W为图像块的宽，H为图像块的高，本实施例中，图像块首先划分为2个(W/2)×(H)尺寸的小块，从左往右顺序，称第一个子块为左小块，第二个子块为右小块。位于切片非首列的图像块，其左小块和右小块分别划分为N/2个(W/N)×H尺寸的子块；位于切片首列非首行的图像块，当H>1时，其左小块和右小块分别划分N/2个(2*W/N)×(H/2)尺寸的子块，当H＝1时，其左小块和右小块分别划分N/4个(2*W/N)×H尺寸的子块；位于切片首行首列的图像块，仅将其右小块划分为N/2个(W/N)×H尺寸的子块，即此情况下，子块仅由右小块划分得到。
可选地，上述IBC预测模式包括应用于切片首列非首行的图像块的IBC预测模式、应用于切片非首列和应用于切片首行首列的图像块。
上述三种IBC模式的搜索区域规定如下：
当图像块位于切片非首列时，左小块的N/2个(W/N)×H尺寸的子块的搜索区域是：当前(W/2)×(H)尺寸的左小块左侧的S×H区域，右小块的N/2个(W/N)×H尺寸的子块的搜索区域是：当前(W/2)×(H)尺寸的右小块左侧的S×H区域。
当图像块位于切片首列非首行时，当H>1时，左小块和右小块的N/2个(2*W/N)×(H/2)尺寸的子块的搜索区域都为：当前图像块上一行的L×(H/2)区域，当H＝1时，左小块和右小块的N/4个(2*W/N)×H尺寸的子块的搜索区域都为：当前图像块上一行的L×1区域；
当图像块位于切片首行首列时，右小块的N/2个(W/N)×H尺寸的子块的搜索区域是：当前(P)×(H)尺寸的右小块左侧的(W/2)×H区域。
其中，各个子块的搜索区域的宽度(即S或L或P)可以都相同，也可以都不同，或者部分相同，可 以根据当前子块的实际位置进行调整。本实施例中在搜索区域寻找最优匹配块的匹配准则为最小化SAD，即搜索区域内，与当前子块内对应位置像素的原始值的差值的绝对值之和最小的匹配块为最优匹配块，其中，匹配块可以是像素原始值与当前子块的像素原始值差值求SAD，匹配块也可以是像素重建值与当前子块的像素原始值差值求SAD。
本实施例中通过对N个子块的复杂度进行规则运算得到图像块复杂度等级一。具体过程如下：
1.计算组复杂度。将N或N/2个复杂度以固定间隔step分为GN个组，GN＝N/step或N/(2*step)，计算每组内的子块的复杂度之和，将其作为组复杂度；
2.计算图像块的第一编码复杂度(编码复杂度等级)。图像块的编码复杂度(编码复杂度等级)可分为CL种，将每组的组复杂度分别和约定好的阈值进行比较，从CL种编码复杂度(编码复杂度等级)中推导出图像块的第一编码复杂度。
可选地，本申请实施例中图像块的编码复杂度按等级可以分为5种，分别是0、1、2、3和4。
示例性地，可以按照下述规则得到图像块的编码复杂度。
当图像块位于切片首行并且也位于首列时，
如果，当GN个组复杂度都小于低复杂度阈值TL时，第一编码复杂度设为0，
否则，当GN个组复杂度都小于中复杂度阈值TM时，第一编码复杂度设为1，
否则，第一编码复杂度设为2；
否则：
如果，当GN个组复杂度都小于低复杂度阈值TL时，第一编码复杂度设为0；
否则，当GN个组复杂度中有3/4个组的组复杂度都小于低复杂度阈值TL，且其余组的组复杂度都小于中复杂度阈值TM时，第一编码复杂度设为1。
否则，当GN个组复杂度中有3/4个组的组复杂度都小于低复杂度阈值TL，且其余组的组复杂度都小于高复杂度阈值TH时，第一编码复杂度设为2。
否则，当GN个组复杂度中有3/4个组的组复杂度都小于低复杂度阈值TL，且其余组的组复杂度有大于高复杂度阈值TH的组时，第一编码复杂度设为3。
否则，当GN个组复杂度中有小于等于2/4个组的组复杂度都小于低复杂度阈值TL，且其余组的组复杂度都小于中复杂度阈值TM时，第一编码复杂度设为2。
否则，当GN个组复杂度中有小于等于2/4个组的组复杂度都小于低复杂度阈值TL，且其余组的组复杂度都小于高复杂度阈值TH时，第一编码复杂度设为3。
否则，当GN个组复杂度中有小于等于2/4个组的组复杂度都小于低复杂度阈值TL，且其余组的组复杂度有大于高复杂度阈值TH的组时，第一编码复杂度设为4。
S703、根据待编码图像的编码复杂度确定待编码图像块的量化参数。
需要说明的是，待编码图像的编码复杂度确定待编码图像块的量化参数的具体方法可以采用本领域技术人员能够想到的任何一种方法进行处理，本申请实施例对此不作具体限定。
例如，可以按照下述流程根据待编码图像的编码复杂度确定待编码图像块的量化参数。
步骤一、计算缓冲区满度。
上述缓冲区满度计算方式可以为：从物理缓冲区满度记录数组中取出指定时刻T的物理缓冲区满度PhyBufT，上述物理缓冲区满度记录数组保存了此前各个编码块编码或解码时，物理缓冲区中的数据量。计算缓冲区满度RcBufT＝PhyBufT+X0，其中X0为约定好的参数。最终，缓冲区满度F的计算过程为F＝RcBufT/RcBufMAX，其中RcBufMAX为缓冲区的最大值。
步骤二、计算块比特预期量。其中，块比特预期量Bpp代表当前编码块在不考虑图像内容的情形下，预期的编码比特。
块比特预期量的计算过程可以为：Bpp＝8*BppINI+BppADJ。其中，BppINI为预期量的初始值，由输入图像块原始比特数和目标压缩率相乘得到。BppADJ为预期量的调整值，该值与(RcBufEND-RcBufT)成正比，其中RcBufEND为编码或解码过程全部结束时预期的缓冲区满度，RcBufT为上述步骤一中得到的缓冲区满度。
在一种可能的方式中，也可以不计算块比特预期量。
步骤三、计算信息比率。其中，信息比率R代表经过量化后，编码块保留的信息和原始编码块的比率。
信息比率的计算过程如下：
1)计算比特偏移量bitsOffset，bitsOffset＝BitsOffset-X1*bpp+X2，其中BitsOffset为比特偏移量的初始值，X1和X2为约定好的参数。
2)获取T时刻的平均无损编码比特BAVG，通过查询平均无损编码比特记录数组得到。
3)计算信息比率R＝(Bpp*InvTab[X3*BAVG-bitsOffset-1]+X4)*X5。
其中，Bpp为上述步骤二中得到的块比特预期量，InvTab为约定好的参数表，X3、X4和X5为约定好的参数。
步骤四、获取无损编码比特数。其中，无损编码比特数BLL代表编码块在无量化情形下编码比特数的估计值。
具体地，可以通过对无损编码比特数记录数组RecordBLL查表得到，BLL＝RecordBLL[T][k]，其中T代表指定时刻，k代表输入的图像块的编码复杂度(即编码复杂度等级)。
步骤五、计算目标比特数。其中，目标比特数BTGT代表编码块通过码控模块应得到的比特数。
目标比特数BTGT计算方法为：BTGT＝(R*(BLL-bitsOffset)+X6)*X7。
其中，R为上述步骤三得到的信息比率，BLL为上述步骤四得到的无损编码比特数，bitsOffset为上述步骤三中计算的比特偏移量，X6和X7为约定好的参数。
步骤六、对目标比特数钳位。
示例性地，可以据块比特预期量Bpp，无损编码比特数BLL和缓冲区满度F计算最小目标比特BMIN和最大目标比特BMAX，并使用该范围对目标比特数BTGT进行钳位。其中，目标比特数BTGT可以为：BTGT＝MIN(MAX(BMIN，BTGT)，BMAX)。
在一种可能的方式中，也可以不对目标比特数钳位。
步骤七、计算量化参数。
其中，量化参数QP可以满足：QP＝(BLL-(BTGT+X8)*X9)*X10。
其中，BLL为上述步骤四得到的无损编码比特数，BTGT为上述步骤五得到的目标比特数，X8、X9和X10为约定好的参数。
S704、根据待编码图像块的量化参数对待编码图像块进行编码生成码流。
示例性地，可以先将待编码图像块输入编码器后，对编码图像块进行预测、然后通过待编码图像块的量化参数对待编码图像块进行量化，之后对待编码图像块进行熵编码以得到待编码图像块对应的比特流。之后可以串联待编码图像切分的所有编码图像块对应的比特流以得到待编码图像对应的比特流。其中，编码图像块是待编码图像块切分得到的多个图像块中的任意图像块。
需要说明的是，编码过程中使用的量化参数会直接影响解码得到的图像的图像质量。通过图像的编码复杂度调整量化参数可以提高解码得到的图像的图像质量。但相关技术采用图像水平和垂直梯度计算图像编码复杂度，对于弱方向性的预测模式，梯度计算的结果与弱方向性预测模式的预测误差相差较远，此时会导致梯度计算出的编码复杂度和实际当前编码块(图像块)在最佳预测模式下的实际编码复杂度相差较远，进而导致推导出的量化参数不准，影响图像质量。而本申请实施例通过多个预测模式确定待编码图像块的编码复杂度，无论当前图像块的最佳预测模式是强方向性预测模式，还是弱方向性预测模式，都可以基于多种预测模式的预测效果得到准确得到图像块的编码复杂度，由此提高图像块的编码复杂度的准确性，通过提高编码复杂度的准确性可以使根据编码复杂度得到量化参数更为准确，由于量化参数的准确性与解码得到的图像的图像质量正相关，提高后的量化参数的准确性会使得解码得到的图像的图像质量相应提高。
在一种可能的实现方式中，在根据量化参数对待编码图像块进行编码生成码流后，还可以根据待编码图像块的编码比特数更新码控参数。其中，码控参数包括平均无损编码比特数记录表、无损编码比特数记录表、物理缓冲区满度记录表或记录表位置中的至少一项。
需要说明的是，根据待编码图像块的编码比特数更新码控参数的具体方法可以采用本领域技术人员能够想到的任何一种方法进行处理，本申请实施例对此不作具体限定。
例如，可以按照下述流程根据待编码图像块的编码比特数更新码控参数。
流程一、计算无损编码比特数。
无损编码比特数BLC的计算方法可以为：BLC＝((4*BCU+8*QP+X11)+X8)*X9。
其中，BCU为当前编码块(即待编码图像块)编码或解码后得到的实际编码比特数，QP为当前块(即待编码图像块)使用的量化参数，X8、X9和X11为约定好的参数。
流程二、计算记录表位置。
记录表位置TCUR表示当前编码块时刻，记录表位置TPRE表示上一编码块时刻，TPRE＝(TCUR+N-1)％N，其中，N为码控输入中编码比特数所属编码块和图像块编码复杂度(编码复杂度等级)所属图像块的间隔值。
流程三、更新平均无损编码比特数记录表。
平均无损编码比特数记录表，RecordBAVG为长度为N的数组，RecordBAVG[t]表示第t个位置的值。RecordBAVG[TCUR]＝(RecordBAVG[TPRE]+X12*BLC)*X13，
其中，TCUR和TPRE为上述流程二中计算的记录表位置，BLC为上述流程一中计算得到的无损编码比特数，X12和X13为约定好的参数。
流程四，更新无损编码比特数记录表。
无损编码比特数记录表RecordBLL为大小是N*K的二维数组，RecordBLL[t][k]表示第t个位置、图像块编码复杂度(编码复杂度等级)为k的值。
RecordBLL[TCUR][k]＝(RecordBLL[TPRE][k]*(8-X14)+BLC*X14+4)*X15。
其中TCUR和TPRE为流程二中计算的记录表位置，BLC为流程一中计算得到的无损编码比特数，X14和X15为约定好的参数。
流程五，更新物理缓冲区满度记录表。
物理缓冲区满度记录表RecordPHY为长度为N的数组，RecordPHY[t]表示第t个位置的值。RecordPHY[TCUR]的值更新为当前物理缓冲区满度的实际值。
流程六，更新记录表位置。
更新方法可以为：TCUR＝(TCUR+1)％N。
请参考图12，图12为本申请实施例提供的一种解码方法。如图12所示，该解码方法可以包括：
S1201、获取待编码图像块的编码复杂度。
在一种可能的实现方式中，可以对码流进行熵解码以得到上述编码复杂度。其中，上述码流由上述待编码图像块编码生成。
在另一种可能的实现方式中
S1202、根据待编码图像块的编码复杂度确定待编码图像块的量化参数。
在一种可能的实现方式中，可以根据上述多个预测模式对上述待编码图像块进行预测操作得到上述待编码图像块与每一预测模式对应的预测残差。根据上述预测残差确定上述待编码图像块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据上述目标参数确定上述待编码图像块的第一编码复杂度。将上述待编码图像块划分为多个子块。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定上述待编码图像块的编码复杂度，上述目标绝对误差为上述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，上述绝对变换差之和为上述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，上述目标无损编码比特数为上述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
在一种可能的实现方式中，将上述待编码图像块划分为多个子块。根据上述多个预测模式对上述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据上述预测残差确定上述每一子块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据上述目标参数确定上述每一子块的编码复杂度。根据上述每一子块的编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，根据上述目标参数确定上述待编码图像块的第一编码复杂度。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
S1202的具体实施方式可以参照上述S702，在此就不再赘述。
S1203、根据待编码图像块的量化参数对码流进行解码以得到解码图像块。
其中，上述码流由上述待编码图像块编码生成。上述解码图像块为重建后的上述待编码图像块。
示例性地，可以对上述码流进行熵解码得到待编码图像块的量化参数，然后通过待编码图像块的量化参数对码流进行反量化、然后对码流进行解码操作，最终输出建后的上述待编码图像块。
下面将结合图13介绍用于执行上述编码方法的编码装置。
可以理解的是，编码装置为了实现上述功能，其包含了执行各个功能相应的硬件和/或软件模块。结合本文中所公开的实施例描述的各示例的算法步骤，本申请实施例能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。本领域技术人员可以结合实施例对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请实施例的范围。
本申请实施例可以根据上述方法示例对编码装置进行功能模块的划分，例如，可以对应各个功能划分各个功能模块，也可以将两个或两个以上的功能集成在一个处理模块中。上述集成的模块可以采用硬件的形式实现。需要说明的是，本实施例中对模块的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
在采用对应各个功能划分各个功能模块的情况下，图13示出了上述实施例中涉及的编码装置的一种可能的组成示意图，如图13所示，该编码装置1300可以包括：获取单元1301，第一确定单元1302、第二确定单元1303和编码单元1304。
上述获取单元1301，用于获取待编码图像块。
上述第一确定单元1302，用于根据多个预测模式确定上述待编码图像块的编码复杂度，上述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项，上述编码复杂度用于表征上述待编码图像块编码难度。
上述第二确定单元1303，用于根据上述编码复杂度确定上述待编码图像块的量化参数。
上述编码单元1304，用于根据上述量化参数对上述待编码图像块进行编码生成码流。
在一种可能的实现方式中，上述第一确定单元1302具体用于：根据上述多个预测模式对上述待编码图像块进行预测操作得到上述待编码图像块与每一预测模式对应的预测残差。根据上述预测残差确定上述待编码图像块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述第一确定单元1302具体用于：根据上述目标参数确定上述待编码图像块的第一编码复杂度。将上述待编码图像块划分为多个子块。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述第一确定单元1302具体用于：根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定上述待编码图像块的编码复杂度，上述目标绝对误差为上述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，上述绝对变换差之和为上述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，上述目标无损编码比特数为上述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
在一种可能的实现方式中，上述第一确定单元1302具体用于：将上述待编码图像块划分为多个子块。根据上述多个预测模式对上述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据上述预测残差确定上述每一子块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述第一确定单元1302具体用于：。＝根据上述目标参数确定上述每一子块的编码复杂度。根据上述每一子块的编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述第一确定单元1302具体用于：根据上述目标参数确定上述待编码图像块的第一编码复杂度。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述编码单元1304还用于：将上述编码复杂度编入上述码流。
下面将结合图14介绍用于执行上述解码方法的解码装置。
可以理解的是，解码装置为了实现上述功能，其包含了执行各个功能相应的硬件和/或软件模块。结合本文中所公开的实施例描述的各示例的算法步骤，本申请实施例能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。本领域技术人员可以结合实施例对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请实施例的范围。
本申请实施例可以根据上述方法示例对解码装置进行功能模块的划分，例如，可以对应各个功能划分各个功能模块，也可以将两个或两个以上的功能集成在一个处理模块中。上述集成的模块可以采用硬件的形式实现。需要说明的是，本实施例中对模块的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
在采用对应各个功能划分各个功能模块的情况下，图14示出了上述实施例中涉及的解码装置的一种可能的组成示意图，如图14所示，该解码装置1400可以包括：获取单元1401、确定单元1402和解码单元1403。
上述获取单元1401，用于获取待编码图像块的编码复杂度，上述编码复杂度用于表征待编码图像块编码难度，上述编码复杂度由多个预测模式确定，上述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项。
上述确定单元1402，用于根据上述编码复杂度确定上述待编码图像块的量化参数。
上述解码单元1403，用于根据上述量化参数对码流进行解码以得到解码图像块，上述码流由上述待编码图像块编码生成，上述解码图像块为重建后的上述待编码图像块。
在一种可能的实现方式中，上述获取单元1401具体用于：对上述码流进行熵解码以得到上述编码复杂度。
在一种可能的实现方式中，上述获取单元1401具体用于：根据上述多个预测模式对上述待编码图像块进行预测操作得到上述待编码图像块与每一预测模式对应的预测残差。根据上述预测残差确定上述待编码图像块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述获取单元1401具体用于：根据上述目标参数确定上述待编码图像块的第一编码复杂度。将上述待编码图像块划分为多个子块。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述获取单元1401具体用于：根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定上述待编码图像块的编码复杂度，上述目标绝对误差为上述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，上述绝对变换差之和为上述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，上述目标无损编码比特数为上述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
在一种可能的实现方式中，上述获取单元1401具体用于：将上述待编码图像块划分为多个子块。根据上述多个预测模式对上述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差。根据上述预测残差确定上述每一子块与每一预测模式对应的目标参数，上述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项。根据上述目标参数确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，在一种可能的实现方式中，上述获取单元1401具体用于：根据上述目标参数确定上述每一子块的编码复杂度。根据上述每一子块的编码复杂度确定上述待编码图像块的编码复杂度。
在一种可能的实现方式中，上述获取单元1401具体用于。根据上述目标参数确定上述待编码图像块的第一编码复杂度。确定上述多个子块中每一子块的水平差值块和垂直差值块。根据上述每一子块的水平差值块和垂直差值块确定上述待编码图像块的第二编码复杂度。根据上述第一编码复杂度和上述第二编码复杂度确定上述待编码图像块的编码复杂度。
本申请实施例还提供一种编码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述相关方法步骤实现上述实施例中的编码方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
本申请实施例还提供一种解码装置，该装置包括：至少一个处理器，当所述至少一个处理器执行程序代码或指令时，实现上述相关方法步骤实现上述实施例中的解码方法。
可选地，该装置还可以包括至少一个存储器，该至少一个存储器用于存储该程序代码或指令。
本申请实施例还提供一种计算机存储介质，该计算机存储介质中存储有计算机指令，当该计算机指令在编码装置上运行时，使得编码装置执行上述相关方法步骤实现上述实施例中的编解码方法。
本申请实施例还提供了一种计算机程序产品，当该计算机程序产品在计算机上运行时，使得计算机执行上述相关步骤，以实现上述实施例中的编解码方法。
本申请实施例还提供一种编解码装置，这个装置具体可以是芯片、集成电路、组件或模块。具体的，该装置可包括相连的处理器和用于存储指令的存储器，或者该装置包括至少一个处理器，用于从外部存储器获取指令。当装置运行时，处理器可执行指令，以使芯片执行上述各方法实施例中的编解码方法。
图15示出了一种芯片1500的结构示意图。芯片1500包括一个或多个处理器1501以及接口电路1502。可选的，上述芯片1500还可以包含总线1503。
处理器1501可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述编解码方法的各步骤可以通过处理器1501中的硬件的集成逻辑电路或者软件形式的指令完成。
可选地，上述的处理器1501可以是通用处理器、数字信号处理(digital signal processing，DSP)器、集成电路(application specific integrated circuit，ASIC)、现场可编程门阵列(field-programmable gate array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
接口电路1502可以用于数据、指令或者信息的发送或者接收，处理器1501可以利用接口电路1502接收的数据、指令或者其他信息，进行加工，可以将加工完成信息通过接口电路1502发送出去。
可选的，芯片还包括存储器，存储器可以包括只读存储器和随机存取存储器，并向处理器提供操作指令和数据。存储器的一部分还可以包括非易失性随机存取存储器(non-volatile random access memory，NVRAM)。
可选的，存储器存储了可执行软件模块或者数据结构，处理器可以通过调用存储器存储的操作指令(该操作指令可存储在操作系统中)，执行相应的操作。
可选的，芯片可以使用在本申请实施例涉及的编码装置或DOP中。可选的，接口电路1502可用于输出处理器1501的执行结果。关于本申请实施例的一个或多个实施例提供的编解码方法可参考前述各个实施例，这里不再赘述。
需要说明的，处理器1501、接口电路1502各自对应的功能既可以通过硬件设计实现，也可以通过软件设计来实现，还可以通过软硬件结合的方式来实现，这里不作限制。
其中，本实施例提供的装置、计算机存储介质、计算机程序产品或芯片均用于执行上文所提供的对应的方法，因此，其所能达到的有益效果可参考上文所提供的对应的方法中的有益效果，此处不再赘述。
应理解，在本申请实施例的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请实施例的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请实施例所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其他的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，上述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其他的形式。
上述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选 择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请实施例各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
上述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请实施例各个实施例上述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请实施例的具体实施方式，但本申请实施例的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请实施例揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请实施例的保护范围之内。因此，本申请实施例的保护范围应所述以权利要求的保护范围为准。

Claims (36)

  1. 一种编码方法，其特征在于，包括：
    获取待编码图像块；
    根据多个预测模式确定所述待编码图像块的编码复杂度，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项，所述编码复杂度用于表征所述待编码图像块编码难度；
    根据所述编码复杂度确定所述待编码图像块的量化参数；
    根据所述量化参数对所述待编码图像块进行编码生成码流。
  2. 根据权利要求1所述的方法，其特征在于，所述根据多个预测模式确定所述待编码图像块的编码复杂度，包括：
    根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    将所述待编码图像块划分为多个子块；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  4. 根据权利要求2所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
  5. 根据权利要求1所述的方法，其特征在于，所述根据多个预测模式确定所述待编码图像块的编码复杂度，包括：
    将所述待编码图像块划分为多个子块；
    根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  6. 根据权利要求5所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据所述目标参数确定所述每一子块的编码复杂度；
    根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
  7. 根据权利要求5所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  8. 根据权利要求1至7中任一项所述的方法，其特征在于，所述方法还包括：
    将所述编码复杂度编入所述码流。
  9. 一种解码方法，其特征在于，包括：
    获取待编码图像块的编码复杂度，所述编码复杂度用于表征待编码图像块编码难度，所述编码复杂度 由多个预测模式确定，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项；
    根据所述编码复杂度确定所述待编码图像块的量化参数；
    根据所述量化参数对码流进行解码以得到解码图像块，所述码流由所述待编码图像块编码生成，所述解码图像块为重建后的所述待编码图像块。
  10. 根据权利要求9所述的方法，其特征在于，所述获取编码复杂度，包括：
    对所述码流进行熵解码以得到所述编码复杂度。
  11. 根据权利要求9所述的方法，其特征在于，所述获取待编码图像块的编码复杂度，包括：
    根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  12. 根据权利要求11所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    将所述待编码图像块划分为多个子块；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  13. 根据权利要求11所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
  14. 根据权利要求9所述的方法，其特征在于，所述获取待编码图像块的编码复杂度，包括：
    将所述待编码图像块划分为多个子块；
    根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  15. 根据权利要求14所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据所述目标参数确定所述每一子块的编码复杂度；
    根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
  16. 根据权利要求14所述的方法，其特征在于，所述根据所述目标参数确定所述待编码图像块的编码复杂度，包括：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  17. 一种编码装置，其特征在于，包括：获取单元，第一确定单元、第二确定单元和编码单元；
    所述获取单元，用于获取待编码图像块；
    所述第一确定单元，用于根据多个预测模式确定所述待编码图像块的编码复杂度，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项，所述编码复杂度用于表征所述待编码图像块编码难度；
    所述第二确定单元，用于根据所述编码复杂度确定所述待编码图像块的量化参数；
    所述编码单元，用于根据所述量化参数对所述待编码图像块进行编码生成码流。
  18. 根据权利要求17所述的装置，其特征在于，所述第一确定单元具体用于：
    根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  19. 根据权利要求18所述的装置，其特征在于，所述第一确定单元具体用于：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    将所述待编码图像块划分为多个子块；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  20. 根据权利要求18所述的装置，其特征在于，所述第一确定单元具体用于：
    根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
  21. 根据权利要求17所述的装置，其特征在于，所述第一确定单元具体用于：
    将所述待编码图像块划分为多个子块；
    根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  22. 根据权利要求21所述的装置，其特征在于，所述第一确定单元具体用于：
    根据所述目标参数确定所述每一子块的编码复杂度；
    根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
  23. 根据权利要求21所述的装置，其特征在于，所述第一确定单元具体用于：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  24. 根据权利要求17至23中任一项所述的装置，其特征在于，所述编码单元还用于：
    将所述编码复杂度编入所述码流。
  25. 一种解码装置，其特征在于，包括：获取单元、确定单元和解码单元；
    所述获取单元，用于获取待编码图像块的编码复杂度，所述编码复杂度用于表征待编码图像块编码难度，所述编码复杂度由多个预测模式确定，所述多个预测模式包括块级预测、点级预测和帧内块复制预测中的至少一项；
    所述确定单元，用于根据所述编码复杂度确定所述待编码图像块的量化参数；
    所述解码单元，用于根据所述量化参数对码流进行解码以得到解码图像块，所述码流由所述待编码图像块编码生成，所述解码图像块为重建后的所述待编码图像块。
  26. 根据权利要求25所述的解码装置，其特征在于，所述获取单元具体用于：
    对所述码流进行熵解码以得到所述编码复杂度。
  27. 根据权利要求25所述的解码装置，其特征在于，所述获取单元具体用于：
    根据所述多个预测模式对所述待编码图像块进行预测操作得到所述待编码图像块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述待编码图像块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  28. 根据权利要求27所述的解码装置，其特征在于，所述获取单元具体用于：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    将所述待编码图像块划分为多个子块；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  29. 根据权利要求27所述的解码装置，其特征在于，所述获取单元具体用于：
    根据目标绝对误差、目标绝对变换差之和或目标无损编码比特数确定所述待编码图像块的编码复杂度，所述目标绝对误差为所述待编码图像块与每一预测模式对应的绝对误差中最小的绝对误差，所述绝对变换差之和为所述待编码图像块与每一预测模式对应的绝对变换差之和中最小的绝对变换差之和，所述目标无损编码比特数为所述待编码图像块与每一预测模式对应的无损编码比特数中最小的无损编码比特数。
  30. 根据权利要求25所述的解码装置，其特征在于，所述获取单元具体用于：
    将所述待编码图像块划分为多个子块；
    根据所述多个预测模式对所述多个子块进行预测操作得到每一子块与每一预测模式对应的预测残差；
    根据所述预测残差确定所述每一子块与每一预测模式对应的目标参数，所述目标参数包括绝对误差和、绝对变换差之和或无损编码比特数中的至少一项；
    根据所述目标参数确定所述待编码图像块的编码复杂度。
  31. 根据权利要求30所述的解码装置，其特征在于，所述获取单元具体用于：
    根据所述目标参数确定所述每一子块的编码复杂度；
    根据所述每一子块的编码复杂度确定所述待编码图像块的编码复杂度。
  32. 根据权利要求30所述的解码装置，其特征在于，所述获取单元具体用于：
    根据所述目标参数确定所述待编码图像块的第一编码复杂度；
    确定所述多个子块中每一子块的水平差值块和垂直差值块；
    根据所述每一子块的水平差值块和垂直差值块确定所述待编码图像块的第二编码复杂度；
    根据所述第一编码复杂度和所述第二编码复杂度确定所述待编码图像块的编码复杂度。
  33. 一种解码装置，包括至少一个处理器和存储器，其特征在于，所述至少一个处理器执行存储在存储器中的程序或指令，以使得所述解码装置实现上述权利要求1至8中任一项所述的方法。
  34. 一种编码装置，包括至少一个处理器和存储器，其特征在于，所述至少一个处理器执行存储在存储器中的程序或指令，以使得所述编码装置实现上述权利要求9至16中任一项所述的方法。
  35. 一种计算机可读存储介质，用于存储计算机程序，其特征在于，当所述计算机程序在计算机或处理器运行时，使得所述计算机或所述处理器实现上述权利要求1至8中任一项或权利要求9至16中任一项所述的方法。
  36. 一种计算机程序产品，所述计算机程序产品中包含指令，其特征在于，当所述指令在计算机或处理器上运行时，使得所述计算机或所述处理器实现上述权利要求1至8中任一项或权利要求9至16中任一项所述的方法。
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CN118972584A (zh) * 2024-10-16 2024-11-15 支付宝(杭州)信息技术有限公司 一种视频压缩方法、装置、设备及介质
CN120434391A (zh) * 2025-07-02 2025-08-05 中科南京人工智能创新研究院 码率自适应图像压缩方法及系统

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12284360B2 (en) * 2023-06-20 2025-04-22 Disney Enterprises, Inc. Performance optimization of pre-processor using video proxy codec

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103888762A (zh) * 2014-02-24 2014-06-25 西南交通大学 一种基于hevc标准的视频编码框架
JP2017152851A (ja) * 2016-02-23 2017-08-31 富士通株式会社 動画像符号化装置、動画像符号化方法および動画像符号化プログラム
CN111836046A (zh) * 2020-06-22 2020-10-27 腾讯科技（深圳）有限公司 视频编码方法及装置、电子设备和计算机可读存储介质
CN113382258A (zh) * 2021-06-10 2021-09-10 北京百度网讯科技有限公司 视频编码方法、装置、设备和介质

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101855910B (zh) * 2007-09-28 2014-10-29 杜比实验室特许公司 视频压缩和传送技术
CN101795415B (zh) * 2010-04-22 2012-02-08 杭州华三通信技术有限公司 一种视频编码中的码率控制方法及其装置
US9930346B2 (en) * 2014-04-15 2018-03-27 Qualcomm Incorporated System and method for flatness detection for display stream compression (DSC)
JP7125594B2 (ja) * 2018-04-27 2022-08-25 富士通株式会社 符号化装置、符号化方法、及び符号化プログラム

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103888762A (zh) * 2014-02-24 2014-06-25 西南交通大学 一种基于hevc标准的视频编码框架
JP2017152851A (ja) * 2016-02-23 2017-08-31 富士通株式会社 動画像符号化装置、動画像符号化方法および動画像符号化プログラム
CN111836046A (zh) * 2020-06-22 2020-10-27 腾讯科技（深圳）有限公司 视频编码方法及装置、电子设备和计算机可读存储介质
CN113382258A (zh) * 2021-06-10 2021-09-10 北京百度网讯科技有限公司 视频编码方法、装置、设备和介质

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP4583507A4

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118972584A (zh) * 2024-10-16 2024-11-15 支付宝(杭州)信息技术有限公司 一种视频压缩方法、装置、设备及介质
CN120434391A (zh) * 2025-07-02 2025-08-05 中科南京人工智能创新研究院 码率自适应图像压缩方法及系统

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