WO2020042268A1 - 一种视频帧的复杂度的确定方法及装置 - Google Patents

一种视频帧的复杂度的确定方法及装置 Download PDF

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WO2020042268A1
WO2020042268A1 PCT/CN2018/108241 CN2018108241W WO2020042268A1 WO 2020042268 A1 WO2020042268 A1 WO 2020042268A1 CN 2018108241 W CN2018108241 W CN 2018108241W WO 2020042268 A1 WO2020042268 A1 WO 2020042268A1
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picture block
complexity
value
video frame
current video
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French (fr)
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黄学辉
吕士表
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Wangsu Science and Technology Co Ltd
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Wangsu Science and Technology Co Ltd
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Priority to EP18903034.9A priority Critical patent/EP3637769B1/en
Priority to US16/465,783 priority patent/US20210099712A1/en
Publication of WO2020042268A1 publication Critical patent/WO2020042268A1/zh
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
    • H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • H04N17/004—Diagnosis, testing or measuring for television systems or their details for digital television systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/107—Selection of coding mode or of prediction mode between spatial and temporal predictive coding, e.g. picture refresh
    • H—ELECTRICITY
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    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/109—Selection of coding mode or of prediction mode among a plurality of temporal predictive coding modes
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/11—Selection of coding mode or of prediction mode among a plurality of spatial predictive coding modes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/119—Adaptive subdivision aspects, e.g. subdivision of a picture into rectangular or non-rectangular coding blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136—Incoming video signal characteristics or properties
    • H04N19/14—Coding unit complexity, e.g. amount of activity or edge presence estimation
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    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/157—Assigned coding mode, i.e. the coding mode being predefined or preselected to be further used for selection of another element or parameter
    • H04N19/159—Prediction type, e.g. intra-frame, inter-frame or bidirectional frame prediction
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    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/61—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/625—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using discrete cosine transform [DCT]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
    • H04N21/4402—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving reformatting operations of video signals for household redistribution, storage or real-time display
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/462—Content or additional data management e.g. creating a master electronic programme guide from data received from the Internet and a Head-end or controlling the complexity of a video stream by scaling the resolution or bit-rate based on the client capabilities
    • H04N21/4621—Controlling the complexity of the content stream or additional data, e.g. lowering the resolution or bit-rate of the video stream for a mobile client with a small screen

Definitions

  • the present invention relates to the field of Internet technologies, and in particular, to a method and a device for determining the complexity of a video frame.
  • the live broadcast platform brings real-time video experience to users, it also puts forward higher requirements on users' network bandwidth.
  • the network live broadcast platform usually limits the bit rate of live video, so that the limited bit rate can adapt to the bandwidth that users can provide, and then provide users with a smooth video experience.
  • the purpose of this application is to provide a method and a device for determining the complexity of a video frame, which can improve the accuracy of determining the complexity.
  • the present application provides a method for determining the complexity of a video frame.
  • the method includes: after obtaining a current video frame to be processed, and dividing the current video frame into a specified number of picture blocks, Calculating the inter prediction value and the intra prediction value of the picture block; and determining the time complexity of the picture block based on the difference between the inter prediction value of the picture block and the original pixel value in the picture block And determining the spatial complexity of the picture block based on the difference between the intra-prediction value of the picture block and the original pixel value in the picture block; dividing the time complexity and the spatial complexity into The smaller one is determined as the complexity of the picture block, and the complexity of the current video frame is determined according to the complexity of each picture block in the specified number of picture blocks.
  • another aspect of the present application further provides a device for determining the complexity of a video frame.
  • the device includes a prediction value calculation unit configured to obtain a current video frame to be processed, and After dividing into a specified number of picture blocks, calculating an inter prediction value and an intra prediction value of the picture block; a time-space complexity determining unit, configured to be based on the inter prediction value of the picture block and the picture block The difference between the original pixel values determines the time complexity of the picture block, and the picture block is determined based on the difference between the intra prediction value of the picture block and the original pixel value in the picture block.
  • another aspect of the present application further provides a device for determining the complexity of a video frame.
  • the device includes a memory and a processor.
  • the memory is used to store a computer program. When executed, implement the method described above.
  • the technical solution provided in this application can first divide the video frame into a specified number of picture blocks, thereby reducing the amount of data to be processed each time.
  • the inter prediction value and the intra prediction value of the picture block can be calculated separately.
  • the time complexity and space complexity of the picture block can be determined respectively.
  • the time complexity can reflect the degree of picture change between the current video frame and the previous video frame
  • the space complexity can reflect the complexity of the texture details in the current video frame. Then, the smaller of the time complexity and the space complexity can be taken as the complexity of the picture block.
  • the technical solution provided by this application divides the current video frame into multiple picture blocks, thereby ensuring that the amount of data processed each time will not be too large, while improving the data processing efficiency, it can also avoid the The calculation error caused by too large, thereby improving the calculation accuracy of the final complexity.
  • determining the complexity of the current frame based on the two dimensions of time complexity and space complexity can also be applied to different types of video frames, thereby further improving the calculation accuracy of the final complexity.
  • FIG. 1 is a schematic diagram of steps of a method for determining a complexity of a video frame according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram of functional modules of a device for determining a complexity of a video frame according to an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of a device for determining a complexity of a video frame according to an embodiment of the present invention.
  • This application provides a method for determining the complexity of a video frame.
  • the method may include the following steps.
  • the current video frame when analyzing the complexity of the current video frame, in order to reduce the amount of data processed each time, the current video frame may be divided into a specified number of picture blocks.
  • the divided picture blocks can have the same size.
  • the size of the divided picture block may be determined according to a video coding format corresponding to the current video frame. Specifically, the size of the divided picture block can be kept consistent with the size of the largest coding unit in the video coding format. For example, assuming that the video encoding format corresponding to the current video frame is the H.264 encoding format, the size of the picture block after the division may be 16 * 16.
  • the size of the picture block after the division can be 64 * 64.
  • the size of a picture block can use pixels as a unit, so in a 16 * 16 picture block, both horizontal and vertical can include 16 pixels.
  • the size of the divided picture blocks may not be appropriate. For example, if the resolution of the current video frame is small, after dividing the picture block in the manner described above, each picture block may appear larger; for another example, if the resolution of the current video frame is large, then divide it in the manner described above After a picture block, each picture block may appear smaller. Therefore, in actual application, after determining the size of the picture block according to the video encoding format, the size of the picture block can also be adjusted according to the actual resolution of the current video frame.
  • the size of the picture block can be appropriately reduced, so that more picture blocks are divided. Conversely, if the size of the divided picture block is too small, the size of the picture block can be appropriately increased, so that fewer picture blocks are divided.
  • the current video frame can be down-sampled in advance to reduce the resolution of the current video frame, thereby reducing the amount of data that needs to be processed subsequently. Specifically, after acquiring the current video frame to be processed, the resolution of the current video frame may be identified. If the resolution is greater than or equal to a specified resolution threshold, it indicates that the resolution of the current video frame is too large. At this time, the current video frame may be down-sampled to obtain a down-sampled video frame.
  • a current video frame with a resolution of 1280 * 720 it can be downsampled to a resolution of 640 * 360.
  • the size of its corresponding picture block can be determined according to the video encoding format.
  • the current video frame with a resolution of 1280 * 720 corresponds to a size of a picture block of 16 * 16.
  • the size of the picture block can be correspondingly reduced.
  • the down-sampled resolution can be divided by the original resolution of the current video frame to obtain the down-sampled coefficient.
  • the size of the original picture block is converted by using the down-sampling coefficient, so as to obtain the size of the picture block corresponding to the down-sampled video frame.
  • the size of the picture block can be correspondingly changed from 16 * 16 to 8 * 8.
  • the complexity of the down-sampled video frame may be used as the complexity of the current video frame.
  • the complexity of each picture block obtained by division may be calculated in advance, and then the sum of the complexity of each picture block may be used as the current The complexity of the video frame.
  • the inter prediction value and the intra prediction value of each picture block can be calculated.
  • the coordinate values of the specified vertices of the picture block may be obtained, and the width and height of the motion search range may be determined.
  • the specified vertex may be, for example, an upper left corner vertex of the picture block.
  • the coordinate value of the designated vertex can be expressed as (y, x), where x represents the abscissa value of the designated vertex, and y represents the ordinate value of the designated vertex.
  • the motion search may be directed to the picture block, and a process of searching for a picture block similar to the picture block in a previous video frame of the current video frame. In practical applications, a range of motion search is usually limited, and the range can be expressed by the width and height of the motion search range described above.
  • multiple sets of different search values may be determined according to the coordinate values of the designated vertex and the width and height of the characteristic motion search range.
  • each set of search values may include an abscissa value and an ordinate value.
  • multiple sets of search values can be determined according to the following formula:
  • x represents the abscissa value of the designated vertex
  • y represents the ordinate value of the designated vertex
  • y 0 represents the ordinate value of the search value
  • SH is the height of the motion search range
  • x 0 represents the abscissa of the search value Coordinate value
  • SW is the wide characterization of the motion search range.
  • the search results corresponding to each set of search values may be calculated separately, and the search value corresponding to the smallest search result may be used as the adaptive search value.
  • the adaptive search value may be determined according to the following formula:
  • bh represents the height of the picture block
  • bw represents the width of the picture block
  • s represents any integer from 0 to bh-1
  • t represents any integer from 0 to bw-1
  • P p (y + s , x + t) represents the pixel value of the pixel with the coordinate value (y + s, x + t) in the current frame
  • P p-1 (s + y 0 , t + x 0 ) represents the The pixel value of a pixel with a coordinate value (s + y 0 , t + x 0 ) in a previous video frame adjacent to the video frame.
  • the picture block may be determined according to a pixel value in a previous video frame adjacent to the current video frame and the adaptive search value.
  • Inter prediction value Specifically, in an application example, the inter prediction value of the picture block may be determined according to the following formula:
  • B inter (i, j) represents an inter prediction value corresponding to a pixel with a coordinate value of (i, j) in the picture block
  • P p-1 (i + y 0 , j + x 0 ) represents an A pixel value of a pixel with a coordinate value (i + y 0 , j + x 0 ) in a previous video frame adjacent to the current video frame
  • i represents any integer from 0 to bh-1
  • j represents from 0 Any integer to bw-1.
  • the determined inter prediction value of the picture block may be a matrix, and each element in the matrix may correspond to each pixel point in the picture block.
  • a plurality of candidate prediction values in a specified direction may be determined according to a current intra prediction method.
  • the current intra prediction method may be implemented by, for example, an intra prediction mode in an encoding process such as H.264, H.265, or VP9.
  • Existing intra prediction modes can obtain different candidate prediction values for different prediction directions.
  • only candidate prediction values in specified directions such as a horizontal direction, a 45-degree angle direction, a vertical direction, and a 135-degree angle direction may be selected.
  • a corresponding evaluation value can be calculated separately.
  • the evaluation value corresponding to the candidate prediction value of the target specified direction among the plurality of candidate prediction values of the specified direction may be calculated according to the following formula:
  • SAD represents the evaluation value corresponding to the candidate prediction value of the target specified direction
  • bh represents the height of the picture block
  • bw represents the width of the picture block
  • s represents any integer from 0 to bh-1
  • t represents Any integer from 0 to bw-1
  • C intra (s, t) represents a candidate prediction value corresponding to a pixel with a coordinate value of (s, t) in the specified direction of the target
  • P p (y + s, x + t) represents a pixel value of a pixel point with a coordinate value (y + s, x + t) in the current frame.
  • the corresponding evaluation value can be calculated by using the above formula. Then, the candidate prediction value corresponding to the smallest evaluation value may be used as the intra prediction value of the picture block.
  • S3 Determine the time complexity of the picture block based on the difference between the inter-prediction value of the picture block and the original pixel value in the picture block, and based on the intra-prediction value of the picture block and the The difference between the original pixel values in the picture block is determined to determine the spatial complexity of the picture block.
  • the corresponding time complexity and space complexity can be calculated.
  • the time complexity may reflect the degree of picture change between the current video frame and the previous video frame
  • the spatial complexity may reflect the complexity of the texture details within the current video frame.
  • the time complexity of the picture block may be determined based on a difference between an inter-prediction value of the picture block and an original pixel value in the picture block.
  • the inter-prediction value of the picture block is a matrix, and each element in the matrix corresponds to the pixels of the picture block on a one-to-one basis. Therefore, when calculating the difference between the inter prediction value of the picture block and the original pixel value in the picture block, the inter prediction value and the pixel value at the same position can be subtracted to obtain the position. The difference. In this way, the resulting difference is also a matrix.
  • a discrete cosine transform may be performed on the difference, and the sum of the absolute values of the coefficients after the discrete cosine transform may be used as the time of the picture block. the complexity.
  • a discrete cosine transform may be performed on the difference between the intra prediction value of the picture block and the original pixel value in the picture block, and The sum of the absolute values of the coefficients is used as the spatial complexity of the picture block.
  • S4 Use the smaller of the time complexity and the space complexity as the complexity of the picture block, and determine the complexity according to the complexity of each picture block in the specified number of picture blocks. The complexity of the current video frame.
  • the smaller of the time complexity and the space complexity may be used as the complexity of the picture block.
  • the complexity of the current video frame can be determined according to the complexity of each picture block in the specified number of picture blocks. Specifically, the sum of the complexity of each picture block can be used as the complexity of the current video frame, thereby completing the process of determining the complexity of the current video frame.
  • the process of analyzing the complexity of the current video frame may be performed before encoding the current video frame. Specifically, in practical applications, if the internal information of the encoder during the encoding process cannot be used, for the current video frame, the picture complexity of the current video frame can be analyzed first, and then the current video frame can be analyzed. Enter the encoder for encoding. If the internal information of the encoder during the encoding process can be used, the current video frame can be directly input to the encoder. After the encoder recognizes the frame type of the current video frame, the picture complexity of the current video frame is determined. Analysis process. The internal information may be a result of the type recognition of the current video frame by the encoder.
  • the frame type of the current video frame may include a B frame, an I frame, and a P frame.
  • the I frame can be called an internal picture frame or a key frame, and the I frame can be used as an independent frame, and does not depend on other adjacent video frames.
  • the P frame can be called a forward search frame
  • the B frame can be called a bidirectional search frame
  • the P and B frames need to depend on the previous video frame or two adjacent video frames.
  • the inter-prediction value and intra-prediction value of the picture block need to be calculated in the manner described above, so as to determine the time complexity that reflects the degree of picture change between the current video frame and the previous video frame.
  • the spatial complexity that can reflect the complexity of the texture details within the current video frame can be determined. If it is identified that the current video frame is an intra picture frame, it indicates that the current video frame does not depend on other video frames. Therefore, there is no need to determine the time complexity, and only the intra prediction value of the picture block can be calculated.
  • the space complexity determined based on the difference between the intra prediction value of the picture block and the original pixel value in the picture block is taken as the complexity of the picture block.
  • the technical solution provided by the present application can realize an accurate picture complexity analysis process regardless of whether the internal information of the encoder during the encoding process can be used, and thus can be independent of the internal information of the encoder.
  • the present application further provides a device for determining the complexity of a video frame.
  • the device includes:
  • a prediction value calculation unit configured to obtain a current video frame to be processed, and divide the current video frame into a specified number of picture blocks, and calculate an inter prediction value and an intra prediction value of the picture block;
  • a time-space complexity determining unit configured to determine a time complexity of the picture block based on a difference between an inter prediction value of the picture block and an original pixel value in the picture block, and based on the picture block A difference between the intra prediction value of the frame and the original pixel value in the picture block to determine the spatial complexity of the picture block;
  • a complexity determining unit configured to use the smaller of the time complexity and the space complexity as the complexity of the picture block, and according to the complexity of each picture block in the specified number of picture blocks Degree to determine the complexity of the current video frame.
  • the present application further provides a device for determining the complexity of a video frame.
  • the device includes a memory and a processor.
  • the memory is used to store a computer program.
  • a method for determining the complexity of the video frame can be implemented.
  • the technical solution provided in this application can first divide the video frame into a specified number of picture blocks, thereby reducing the amount of data to be processed each time.
  • the inter prediction value and the intra prediction value of the picture block can be calculated separately.
  • the time complexity and space complexity of the picture block can be determined respectively.
  • the time complexity can reflect the degree of picture change between the current video frame and the previous video frame
  • the space complexity can reflect the complexity of the texture details in the current video frame. Then, the smaller of the time complexity and the space complexity can be taken as the complexity of the picture block.
  • the technical solution provided by this application divides the current video frame into multiple picture blocks, thereby ensuring that the amount of data processed each time will not be too large, while improving the data processing efficiency, it can also avoid the The calculation error caused by too large, thereby improving the calculation accuracy of the final complexity.
  • determining the complexity of the current frame based on the two dimensions of time complexity and space complexity can also be applied to different types of video frames, thereby further improving the calculation accuracy of the final complexity.
  • each embodiment can be implemented by means of software plus a necessary universal hardware platform, and of course, can also be implemented by hardware.
  • the above-mentioned technical solution essentially or part that contributes to the existing technology can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic A disc, an optical disc, and the like include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments.

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Abstract

本发明公开了一种视频帧的复杂度的确定方法及装置，其中，所述方法包括：获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预测值；基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度；将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。本申请提供的技术方案，能够提高复杂度的确定精度。

Description

一种视频帧的复杂度的确定方法及装置 技术领域
本发明涉及互联网技术领域，特别涉及一种视频帧的复杂度的确定方法及装置。
背景技术
随着互联网技术的不断发展，涌现出大量的网络直播平台。网络直播平台在给用户带来实时性视频体验的同时，也对用户的网络带宽提出了更高的要求。目前，网络直播平台通常会限制直播视频的码率，从而使得限制之后的码率可以适应用户能够提供的带宽，进而给用户提供流畅的视频体验。
目前，在设置直播视频的码率时，有时需要对直播视频的画面复杂度进行分析。然而，当前还不具备精度较高的复杂度的分析方法。
发明内容
本申请的目的在于提供一种视频帧的复杂度的确定方法及装置，能够提高复杂度的确定精度。
为实现上述目的，本申请一方面提供一种视频帧的复杂度的确定方法，所述方法包括：获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预测值；基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度；将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。
为实现上述目的，本申请另一方面还提供一种视频帧的复杂度的确定装置，所述装置包括：预测值计算单元，用于获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预 测值；时空间复杂度确定单元，用于基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度；复杂度确定单元，用于将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。
为实现上述目的，本申请另一方面还提供一种视频帧的复杂度的确定装置，所述装置包括存储器和处理器，所述存储器用于存储计算机程序，所述计算机程序被所述处理器执行时，实现上述的方法。
由上可见，本申请提供的技术方案，在确定视频帧的复杂度时，可以先将视频帧划分为指定数量的画面块，从而减小每次需要处理的数据量。针对每个画面块，可以分别计算画面块的帧间预测值和帧内预测值。然后，可以基于计算出的帧间预测值和帧内预测值，分别确定该画面块的时间复杂度和空间复杂度。其中，该时间复杂度可以体现当前视频帧与前一视频帧之间的画面变化程度，而空间复杂度可以体现当前视频帧内纹理细节的复杂程度。接着，可以将时间复杂度和空间复杂度中的较小者作为画面块的复杂度。由于当前视频帧是由指定数量的画面块构成的，因此，在确定得到各个画面块的复杂度之后，便可以基于确定的这些画面块的复杂度，最终确定当前视频帧的整体复杂度。由上可见，本申请提供的技术方案，将当前视频帧划分为多个画面块，从而保证了每次处理的数据量不会过大，在提高数据处理效率的同时，也能避免由于数据量过大而引起的计算误差，从而提高了最终复杂度的计算精度。此外，基于时间复杂度和空间复杂度这两个维度来确定当前帧的复杂度，也可以适用于不同类型的视频帧，从而进一步地提高了最终复杂度的计算精度。
附图说明
为了更清楚地说明本发明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发明的一些实施例，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1是本发明实施方式中视频帧的复杂度的确定方法步骤示意图；
图2是本发明实施方式中视频帧的复杂度的确定装置的功能模块示意图；
图3是本发明实施方式中视频帧的复杂度的确定装置的结构示意图。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚，下面将结合附图对本发明实施方式作进一步地详细描述。
本申请提供一种视频帧的复杂度的确定方法，请参阅图1，所述方法可以包括以下步骤。
S1：获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预测值。
在本实施方式中，在分析当前视频帧的复杂度时，为了减少每次处理的数据量，可以将该当前视频帧划分为指定数量的画面块。其中，划分后的各个画面块可以具备相同的大小。此外，划分后的画面块的大小，可以按照该当前视频帧对应的视频编码格式来确定。具体地，可以将划分后的画面块的大小与视频编码格式中最大编码单元的大小保持一致。例如，假设该当前视频帧对应的视频编码格式为H.264编码格式，那么划分之后的画面块的大小可以是16*16。又例如，假设该当前视频帧对应的视频编码格式为H.265编码格式，那么划分之后的画面块的大小可以为64*64。其中，画面块的大小可以用像素点作为单位，那么16*16的画面块中，横向和纵向均可以包含16个像素点。
在一个实施方式中，考虑到当前视频帧的实际分辨率可大可小，如果单纯按照编码格式划分画面块，那么划分后的画面块的大小可能不太合适。例如，如果当前视频帧的分辨率较小，那么按照上述的方式划分画面块之后，各个画面块可能会显得较大；又例如，如果当前视频帧的分辨率较大，那么按照上述的方式划分画面块之后，各个画面块可能会显得较小。因此，在实际应用中，按照视频编码格式确定画面块的大小之后，还可以根据当前视频帧的实际分辨率对画面块的大小进行调节。例如，如果划分后的画面块的大小过大，则可以适当减少画面块的大小，从而划分出更多的画面块。相反地，如果划分后的画面块的大小过小，则可以适当增大画面块的大小，从而划分出更少的画面块。
在一个实施方式中，针对分辨率较大的当前视频帧而言，就算将其划分为多个画面块，每个画面块需要处理的数据量可能还比较大。在这种情况下，可 以预先对当前视频帧进行下采样，以减少该当前视频帧的分辨率，从而减少后续需要处理的数据量。具体地，在获取待处理的当前视频帧之后，可以识别所述当前视频帧的分辨率，若所述分辨率大于或者等于指定分辨率阈值，则表明该当前视频帧的分辨率过大。此时，可以对所述当前视频帧进行下采样，得到下采样后的视频帧。举例来说，对于分辨率为1280*720的当前视频帧，可以将其下采样至640*360的分辨率。针对原先的当前视频帧而言，可以按照视频编码格式确定出其对应的画面块的大小。例如，分辨率为1280*720的当前视频帧，其对应的画面块的大小为16*16，那么在对该当前视频帧进行下采样之后，可以对应减小画面块的大小。具体地，可以用下采样后的分辨率除以当前视频帧的原始分辨率，得到下采样系数。然后，利用该下采样系数对原始的画面块的大小进行换算，从而得到下采样后的视频帧对应的画面块的大小。例如，将分辨率为1280*720的当前视频帧下采样至640*360的分辨率之后，可以对应地将画面块的大小从16*16更改为8*8。在本实施方式中，在将原始的当前视频帧进行下采样，得到下采样后的视频帧时，便可以将所述下采样后的视频帧的复杂度作为所述当前视频帧的复杂度。
在本实施方式中，在确定当前视频帧或者下采样后的视频帧的复杂度时，可以预先计算划分得到的每个画面块的复杂度，然后可以将各个画面块的复杂度之和作为当前视频帧的复杂度。具体地，在计算各个画面块的复杂度时，首选可以计算各个画面块的帧间预测值和帧内预测值。
在本实施方式中，在计算画面块的帧间预测值时，可以获取所述画面块的指定顶点的坐标值，并确定用于表征运动搜索范围的宽和高。其中，所述指定顶点例如可以是所述画面块的左上角顶点。该指定顶点的坐标值可以表示为(y,x)，其中，x表示所述指定顶点的横坐标值，y表示所述指定顶点的纵坐标值。所述运动搜索可以指针对所述画面块，在所述当前视频帧的前一个视频帧中搜索与所述画面块相似的画面块的过程。在实际应用中，通常会给运动搜索限制一个范围，该范围便可以通过上述的表征运动搜索范围的宽和高来表示。
在本实施方式中，可以根据所述指定顶点的坐标值以及所述表征运动搜索范围的宽和高，确定多组不同的搜索值。其中，每组搜索值中可以包括横坐标值和纵坐标值。具体地，在一个实际示例中，可以按照以下公式确定多组搜索值：
|y-y 0|≤SH
|x-x 0|≤SW
其中，x表示所述指定顶点的横坐标值，y表示所述指定顶点的纵坐标值，y 0表示搜索值的纵坐标值，SH为表征运动搜索范围的高，x 0表示搜索值的横坐标值，SW为表征运动搜索范围的宽。这样，符合上述条件的(y 0,x 0)便可以作为一组搜索值。
在本实施方式中，可以分别计算每组搜索值对应的搜索结果，并将最小的搜索结果对应的搜索值作为适配搜索值。具体地，在一个应用示例中，可以按照以下公式确定所述适配搜索值：
Figure PCTCN2018108241-appb-000001
其中，bh表示所述画面块的高，bw表示所述画面块的宽，s表示从0至bh-1的任意整数，t表示从0至bw-1的任意整数，P p(y+s,x+t)表示所述当前帧中坐标值为(y+s,x+t)的像素点的像素值，P p-1(s+y 0,t+x 0)表示与所述当前视频帧相邻的前一视频帧中坐标值为(s+y 0,t+x 0)的像素点的像素值。
这样，通过将不同的搜索值代入上述的公式中，便可以得到最终的适配搜索值。
在本实施方式中，在确定出所述适配搜索值之后，便可以根据与所述当前视频帧相邻的前一视频帧中的像素值以及所述适配搜索值，确定所述画面块的帧间预测值。具体地，在一个应用示例中，可以按照以下公式确定所述画面块的帧间预测值：
B inter(i,j)＝P p-1(i+y 0,j+x 0)
其中，B inter(i,j)表示所述画面块中坐标值为(i,j)的像素点对应的帧间预测值，P p-1(i+y 0,j+x 0)表示与所述当前视频帧相邻的前一视频帧中坐标值为(i+y 0,j+x 0)的像素点的像素值，i表示从0至bh-1的任意整数，j表示从0至bw-1的任意整数。
这样，确定出的画面块的帧间预测值可以是一个矩阵，矩阵中的每个元素可以与画面块中的各个像素点相对应。
在本实施方式中，在计算画面块的帧内预测值时，可以按照当前的帧内预测方法，确定出多个指定方向的候选预测值。具体地，所述当前的帧内预测方法例如可以由H.264、H.265或VP9等编码格式编码过程中的帧内预测模式实现。 现有的帧内预测模式可以针对不同的预测方向，得到不同的候选预测值。在本实施方式中，可以仅选用水平方向、45度角方向、垂直方向以及135度角方向这些指定方向的候选预测值。针对每个指定方向的候选预测值，可以分别计算对应的评价值。在一个示例中，可以按照以下公式计算所述多个指定方向的候选预测值中目标指定方向的候选预测值对应的评价值：
Figure PCTCN2018108241-appb-000002
其中，SAD表示所述目标指定方向的候选预测值对应的评价值，bh表示所述画面块的高，bw表示所述画面块的宽，s表示从0至bh-1的任意整数，t表示从0至bw-1的任意整数，C intra(s,t)表示坐标值为(s,t)的像素点在所述目标指定方向对应的候选预测值，P p(y+s,x+t)表示所述当前帧中坐标值为(y+s,x+t)的像素点的像素值。
在本实施方式中，针对各个指定方向的候选预测值，均可以利用上述的公式计算其对应的评价值。然后，可以将最小的评价值对应的候选预测值作为所述画面块的帧内预测值。
S3：基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度。
在本实施方式中，在计算得到画面块的帧间预测值和帧内预测值之后，可以计算对应的时间复杂度和空间复杂度。其中，所述时间复杂度可以体现当前视频帧与前一视频帧之间的画面变化程度，而空间复杂度可以体现当前视频帧内纹理细节的复杂程度。
在本实施方式中，可以基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度。具体地，所述画面块的帧间预测值是一个矩阵，该矩阵中的各个元素与画面块的像素点一一对应。因此，在计算所述画面块的帧间预测值和所述画面块中原始像素值之间的差值时，可以将处于相同位置的帧间预测值和像素值相减，从而得到该位置上的差值。这样，最终得到的差值也是一个矩阵。在本实施方式中，在计算得到上述的矩形形式的差值之后，可以对该差值进行离散余弦变换，并可以将离散余弦变换之后的各个系数的绝对值之和作为所述画面块的时间复杂度。
按照类似的方式，在计算空间复杂度时，可以对所述画面块的帧内预测值 和所述画面块中原始像素值之间的差值进行离散余弦变换，并将离散余弦变换之后的各个系数的绝对值之和作为所述画面块的空间复杂度。
S4：将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。
在本实施方式中，得到画面块的时间复杂度和空间复杂度之后，可以将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度。这样，由于当前视频帧是由指定数量的画面块构成的，因此，可以根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。具体地，可以将各个画面块的复杂度之和作为所述当前视频帧的复杂度，从而完成当前视频帧的复杂度的确定过程。
在一个实施方式中，分析当前视频帧的复杂度的过程，可以在对当前视频帧进行编码之前进行。具体地，在实际应用中，如果无法使用编码器在编码过程中的内部信息，则对于当前视频帧而言，可以先对该当前视频帧的画面复杂度进行分析，然后再将该当前视频帧输入编码器中进行编码。而如果可以使用编码器在编码过程中的内部信息，则可以直接将该当前视频帧输入编码器，在编码器识别出当前视频帧的帧类型之后，在对该当前视频帧进行画面复杂度的分析过程。其中，所述内部信息可以是编码器对当前视频帧的类型识别结果。如果无法使用该内部信息，则表明在对当前视频帧分析画面复杂度时，无法知晓该当前视频帧的帧类型。而如果可以使用该内容信息，则表明在对当前视频帧分析画面复杂度时，已经确定了该当前视频帧的帧类型。其中，所述当前视频帧的帧类型可以包括B帧、I帧以及P帧。其中，I帧可以称为内部画面帧或者关键帧，I帧可以作为独立帧，不依赖与相邻的其它视频帧。P帧可以称为向前搜索帧，B帧可以称为双向搜索帧，P帧和B帧则需要依赖前一视频帧或者相邻的两个视频帧。
在本实施方式中，若无法识别所述当前视频帧的帧类型，或者识别出所述当前视频帧为非内部画面帧(非I帧)，表明该当前视频帧需要依赖其它的视频帧，此时，需要按照上述的方式，计算所述画面块的帧间预测值和帧内预测值，从而即可以确定出体现当前视频帧与前一视频帧之间的画面变化程度的时间复杂度，又可以确定出体现当前视频帧内纹理细节的复杂程度的空间复杂度。而 若识别出所述当前视频帧为内部画面帧，则表明该当前视频帧不依赖于其它视频帧，因此，无需确定时间复杂度，而是可以仅计算所述画面块的帧内预测值，并将基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值确定的空间复杂度作为所述画面块的复杂度。
由上可见，本申请提供的技术方案，无论是否可以使用编码器在编码过程中的内部信息，均能够实现精确的画面复杂度的分析过程，从而可以不依赖于编码器的内部信息。
请参阅图2，本申请还提供一种视频帧的复杂度的确定装置，所述装置包括：
预测值计算单元，用于获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预测值；
时空间复杂度确定单元，用于基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度；
复杂度确定单元，用于将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。
请参阅图3，本申请还提供一种视频帧的复杂度的确定装置，所述装置包括存储器和处理器，所述存储器用于存储计算机程序，所述计算机程序被所述处理器执行时，可以实现上述视频帧的复杂度的确定方法。
由上可见，本申请提供的技术方案，在确定视频帧的复杂度时，可以先将视频帧划分为指定数量的画面块，从而减小每次需要处理的数据量。针对每个画面块，可以分别计算画面块的帧间预测值和帧内预测值。然后，可以基于计算出的帧间预测值和帧内预测值，分别确定该画面块的时间复杂度和空间复杂度。其中，该时间复杂度可以体现当前视频帧与前一视频帧之间的画面变化程度，而空间复杂度可以体现当前视频帧内纹理细节的复杂程度。接着，可以将时间复杂度和空间复杂度中的较小者作为画面块的复杂度。由于当前视频帧是由指定数量的画面块构成的，因此，在确定得到各个画面块的复杂度之后，便可以基于确定的这些画面块的复杂度，最终确定当前视频帧的整体复杂度。由 上可见，本申请提供的技术方案，将当前视频帧划分为多个画面块，从而保证了每次处理的数据量不会过大，在提高数据处理效率的同时，也能避免由于数据量过大而引起的计算误差，从而提高了最终复杂度的计算精度。此外，基于时间复杂度和空间复杂度这两个维度来确定当前帧的复杂度，也可以适用于不同类型的视频帧，从而进一步地提高了最终复杂度的计算精度。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到各实施方式可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件来实现。基于这样的理解，上述技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，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)执行各个实施例或者实施例的某些部分所述的方法。
以上所述仅为本发明的较佳实施例，并不用以限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (13)

  1. 一种视频帧的复杂度的确定方法，其特征在于，所述方法包括：
    获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预测值；
    基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度；
    将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。
  2. 根据权利要求1所述的方法，其特征在于，计算所述画面块的帧间预测值包括：
    获取所述画面块的指定顶点的坐标值，并确定用于表征运动搜索范围的宽和高；
    根据所述指定顶点的坐标值以及所述表征运动搜索范围的宽和高，确定多组搜索值；其中，每组所述搜索值中包括横坐标值和纵坐标值；
    分别计算每组搜索值对应的搜索结果，并将最小的搜索结果对应的搜索值作为适配搜索值；
    根据与所述当前视频帧相邻的前一视频帧中的像素值以及所述适配搜索值，确定所述画面块的帧间预测值。
  3. 根据权利要求2所述的方法，其特征在于，按照以下公式确定多组搜索值：
    |y-y 0|≤SH
    |x-x 0|≤SW
    其中，x表示所述指定顶点的横坐标值，y表示所述指定顶点的纵坐标值，y 0表示搜索值的纵坐标值，SH为表征运动搜索范围的高，x 0表示搜索值的横坐标值，SW为表征运动搜索范围的宽。
  4. 根据权利要求3所述的方法，其特征在于，按照以下公式确定所述适配搜索值：
    Figure PCTCN2018108241-appb-100001
    其中，bh表示所述画面块的高，bw表示所述画面块的宽，s表示从0至bh-1的任意整数，t表示从0至bw-1的任意整数，P p(y+s,x+t)表示所述当前帧中坐标值为(y+s,x+t)的像素点的像素值，P p-1(s+y 0,t+x 0)表示与所述当前视频帧相邻的前一视频帧中坐标值为(s+y 0,t+x 0)的像素点的像素值。
  5. 根据权利要求4所述的方法，其特征在于，按照以下公式确定所述画面块的帧间预测值：
    B inter(i,j)＝P p-1(i+y 0,j+x 0)
    其中，B inter(i,j)表示所述画面块中坐标值为(i,j)的像素点对应的帧间预测值，P p-1(i+y 0,j+x 0)表示与所述当前视频帧相邻的前一视频帧中坐标值为(i+y 0,j+x 0)的像素点的像素值，i表示从0至bh-1的任意整数，j表示从0至bw-1的任意整数。
  6. 根据权利要求1所述的方法，其特征在于，计算所述画面块的帧内预测值包括：
    获取所述画面块在多个指定方向的候选预测值，并计算每个指定方向的候选预测值对应的评价值；
    将最小的评价值对应的候选预测值作为所述画面块的帧内预测值。
  7. 根据权利要求6所述的方法，其特征在于，按照以下公式计算所述多个指定方向的候选预测值中目标指定方向的候选预测值对应的评价值：
    Figure PCTCN2018108241-appb-100002
    其中，SAD表示所述目标指定方向的候选预测值对应的评价值，bh表示所述画面块的高，bw表示所述画面块的宽，s表示从0至bh-1的任意整数，t表示从0至bw-1的任意整数，C intra(s,t)表示坐标值为(s,t)的像素点在所述目标指定方向对应的候选预测值，P p(y+s,x+t)表示所述当前帧中坐标值为(y+s,x+t)的像素点的 像素值。
  8. 根据权利要求1所述的方法，其特征在于，按照以下方式确定所述画面块的时间复杂度和空间复杂度：
    对所述画面块的帧间预测值和所述画面块中原始像素值之间的差值进行离散余弦变换，并将离散余弦变换之后的各个系数的绝对值之和作为所述画面块的时间复杂度；
    对所述画面块的帧内预测值和所述画面块中原始像素值之间的差值进行离散余弦变换，并将离散余弦变换之后的各个系数的绝对值之和作为所述画面块的空间复杂度。
  9. 根据权利要求1所述的方法，其特征在于，确定所述当前视频帧的复杂度包括：
    将各个画面块的复杂度之和作为所述当前视频帧的复杂度。
  10. 根据权利要求1所述的方法，其特征在于，在将所述当前视频帧划分为指定数量的画面块后，所述方法还包括：
    若无法识别所述当前视频帧的帧类型，或者识别出所述当前视频帧为非内部画面帧，才计算所述画面块的帧间预测值和帧内预测值；
    若识别出所述当前视频帧为内部画面帧，仅计算所述画面块的帧内预测值，并将基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值确定的空间复杂度作为所述画面块的复杂度。
  11. 根据权利要求1所述的方法，其特征在于，在获取待处理的当前视频帧之后，所述方法还包括：
    识别所述当前视频帧的分辨率，若所述分辨率大于或者等于指定分辨率阈值，对所述当前视频帧进行下采样，得到下采样后的视频帧；其中，所述下采样后的视频帧的复杂度作为所述当前视频帧的复杂度。
  12. 一种视频帧的复杂度的确定装置，其特征在于，所述装置包括：
    预测值计算单元，用于获取待处理的当前视频帧，并将所述当前视频帧划分为指定数量的画面块后，计算所述画面块的帧间预测值和帧内预测值；
    时空间复杂度确定单元，用于基于所述画面块的帧间预测值和所述画面块中原始像素值之间的差值，确定所述画面块的时间复杂度，并基于所述画面块的帧内预测值和所述画面块中原始像素值之间的差值，确定所述画面块的空间复杂度；
    复杂度确定单元，用于将所述时间复杂度和所述空间复杂度之间的较小者，作为所述画面块的复杂度，并根据所述指定数量的画面块中各个画面块的复杂度，确定所述当前视频帧的复杂度。
  13. 一种视频帧的复杂度的确定装置，其特征在于，所述装置包括处理器和存储器，所述存储器用于存储计算机程序，所述计算机程序被所述处理器执行时，用于实现如权利要求1至11中任一权利要求所述的方法。
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101926178A (zh) * 2008-01-24 2010-12-22 Sk电信有限公司 基于时间复杂度和空间复杂度来确定编码模式的方法及装置
CN102984541A (zh) * 2012-12-07 2013-03-20 浙江大学 一种基于像素域失真度估计的视频质量评价方法
US20150319437A1 (en) * 2014-04-30 2015-11-05 Intel Corporation Constant quality video coding

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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US9071841B2 (en) * 2011-05-17 2015-06-30 Microsoft Technology Licensing, Llc Video transcoding with dynamically modifiable spatial resolution
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US10334224B2 (en) * 2016-02-19 2019-06-25 Alcacruz Inc. Systems and method for GPU based virtual reality video streaming server

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101926178A (zh) * 2008-01-24 2010-12-22 Sk电信有限公司 基于时间复杂度和空间复杂度来确定编码模式的方法及装置
CN102984541A (zh) * 2012-12-07 2013-03-20 浙江大学 一种基于像素域失真度估计的视频质量评价方法
US20150319437A1 (en) * 2014-04-30 2015-11-05 Intel Corporation Constant quality video coding

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