WO2020258016A1 - 图像分量预测方法、装置及计算机存储介质 - Google Patents

图像分量预测方法、装置及计算机存储介质 Download PDF

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Publication number
WO2020258016A1
WO2020258016A1 PCT/CN2019/092711 CN2019092711W WO2020258016A1 WO 2020258016 A1 WO2020258016 A1 WO 2020258016A1 CN 2019092711 W CN2019092711 W CN 2019092711W WO 2020258016 A1 WO2020258016 A1 WO 2020258016A1
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Prior art keywords
predicted
reference pixel
pixel set
image component
component
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PCT/CN2019/092711
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English (en)
French (fr)
Chinese (zh)
Inventor
霍俊彦
马彦卓
万帅
杨付正
李新伟
冉启宏
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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Priority to JP2021576642A priority Critical patent/JP7448568B2/ja
Priority to KR1020257031111A priority patent/KR20250139896A/ko
Priority to CN202310838522.8A priority patent/CN116962677B/zh
Priority to EP24152839.7A priority patent/EP4336839A3/en
Priority to CN202310836590.0A priority patent/CN116866560B/zh
Priority to CN202111138344.5A priority patent/CN113840142B/zh
Priority to PL19934681.8T priority patent/PL3952308T3/pl
Priority to ES19934681T priority patent/ES2975857T3/es
Priority to CN202310836765.8A priority patent/CN116708771B/zh
Priority to CN202511734167.5A priority patent/CN121547579A/zh
Priority to KR1020217043312A priority patent/KR102863211B1/ko
Priority to KR1020257031106A priority patent/KR20250139895A/ko
Priority to CN202511734113.9A priority patent/CN121418566A/zh
Priority to PCT/CN2019/092711 priority patent/WO2020258016A1/zh
Priority to CN201980091266.2A priority patent/CN113396587B/zh
Priority to KR1020257031117A priority patent/KR20250139897A/ko
Priority to KR1020257031100A priority patent/KR20250140641A/ko
Priority to EP19934681.8A priority patent/EP3952308B1/en
Application filed by Guangdong Oppo Mobile Telecommunications Corp Ltd filed Critical Guangdong Oppo Mobile Telecommunications Corp Ltd
Publication of WO2020258016A1 publication Critical patent/WO2020258016A1/zh
Priority to US17/452,682 priority patent/US11363257B2/en
Anticipated expiration legal-status Critical
Priority to US17/723,179 priority patent/US11973936B2/en
Priority to JP2024030081A priority patent/JP7583208B2/ja
Priority to US18/622,202 priority patent/US12537939B2/en
Priority to JP2024189026A priority patent/JP7714766B2/ja
Priority to US19/236,578 priority patent/US20250310518A1/en
Priority to US19/236,428 priority patent/US20250310517A1/en
Priority to JP2025119422A priority patent/JP2025148530A/ja
Priority to JP2025119427A priority patent/JP2025148531A/ja
Priority to US19/402,764 priority patent/US20260089314A1/en
Priority to US19/402,735 priority patent/US20260089313A1/en
Ceased legal-status Critical Current

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    • H04N19/593—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving spatial prediction techniques

Definitions

  • the embodiments of the present application relate to the field of video coding and decoding technologies, and in particular to an image component prediction method, device, and computer storage medium.
  • H.265/High Efficiency Video Coding has been unable to meet the needs of the rapid development of video applications.
  • JVET Joint Video Exploration Team
  • VVC VVC Reference Software Test Platform
  • VTM an image component prediction method based on a prediction model has been integrated, through which the chrominance component can be predicted from the luminance component of the current coding block (CB).
  • CB current coding block
  • the embodiments of the application provide an image component prediction method, device, and computer storage medium, which unify the derivation process of model parameters without changing the codec prediction performance, and at the same time aim at the number of effective pixels in the adjacent reference pixel set When the number is less than the preset number, since no additional processing modules are added, no additional processing is required, and the computational complexity is also reduced.
  • an embodiment of the present application provides an image component prediction method, the method includes:
  • the first reference pixel set is screened to obtain a second reference pixel set; wherein, the second reference pixel set The number of effective pixels is less than or equal to the preset number;
  • the model parameters are determined by the second reference pixel set, and the prediction model corresponding to the image component to be predicted is obtained according to the model parameters ;
  • the prediction model is used to implement the prediction processing of the image component to be predicted to obtain the predicted value corresponding to the image component to be predicted.
  • an embodiment of the present application provides an image component prediction device, the image component prediction device includes: an acquisition unit, a prediction unit, and a screening unit, wherein:
  • the acquiring unit is configured to acquire a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image;
  • the prediction unit is configured to use the preset component value as the predicted value corresponding to the image component to be predicted when the number of effective pixel points in the first reference pixel set is less than a preset number;
  • the screening unit is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of effective pixel points in the first reference pixel set is greater than or equal to a preset number; wherein, The number of effective pixels in the second reference pixel set is less than or equal to a preset number;
  • the prediction unit is further configured to use the preset component value as the predicted value corresponding to the image component to be predicted when the number of effective pixel points in the second reference pixel set is less than the preset number; and when the When the number of effective pixels in the second reference pixel set is equal to the preset number, the model parameters are determined by the second reference pixel set, and the prediction model corresponding to the image component to be predicted is obtained according to the model parameters; wherein, The prediction model is used to implement prediction processing on the image component to be predicted, so as to obtain the predicted value corresponding to the image component to be predicted.
  • an embodiment of the present application provides an image component prediction device, the image component prediction device including: a memory and a processor;
  • the memory is used to store a computer program that can run on the processor
  • the processor is configured to execute the method described in the first aspect when running the computer program.
  • an embodiment of the present application provides a computer storage medium, the computer storage medium stores an image component prediction program, and when the image component prediction program is executed by at least one processor, the method described in the first aspect is implemented. method.
  • the embodiments of the present application provide an image component prediction method, device, and computer storage medium, by acquiring a first reference pixel set corresponding to the image component to be predicted of an encoding block in a video image; when there are effective pixels in the first reference pixel set When the number is less than the preset number, the preset component value is used as the predicted value corresponding to the image component to be predicted; when the number of effective pixels in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set Screening is performed to obtain a second reference pixel set.
  • the number of effective pixels in the second reference pixel set is less than or equal to the preset number; when the number of effective pixels in the second reference pixel set is less than the preset number, the The preset component value is used as the predicted value corresponding to the image component to be predicted; when the number of effective pixels in the second reference pixel set is equal to the preset number, the model parameters are determined by the second reference pixel set, and the model parameters are obtained according to the model parameters.
  • the prediction model corresponding to the image component to be predicted and the prediction model is used to implement the prediction processing of the image component to be predicted to obtain the predicted value corresponding to the image component to be predicted; in this way, when the number of effective pixels in the first reference pixel set is When the number is less than the preset number or the number of effective pixels in the second reference pixel set is less than the preset number, the preset default value is directly used as the predicted value corresponding to the image component to be predicted; only the effective pixels in the second reference pixel set When the number of points meets the preset number, the model parameters will be determined according to the first reference pixel set to establish the prediction model of the image component to be predicted, thereby unifying the model parameter derivation process; in addition, for the first reference pixel set or In the case where the number of effective pixels in the second reference pixel set is less than the preset number, especially when the effective pixel points are 0 or 2, since no additional processing modules are added, the preset default value is directly used as the waiting The predicted value corresponding to the image component is predicted
  • FIG. 1 is a schematic diagram of the distribution of an effective adjacent area according to an embodiment of the application
  • FIG. 2 is a schematic diagram of the distribution of selected areas in three modes according to an embodiment of the application.
  • FIG. 3 is a schematic diagram of the composition of a video encoding system provided by an embodiment of the application.
  • FIG. 4 is a schematic diagram of the composition of a video decoding system provided by an embodiment of the application.
  • FIG. 5 is a schematic flowchart of an image component prediction method provided by an embodiment of the application.
  • 6A is a schematic structural diagram of adjacent reference pixel selection in INTRA_LT_CCLM mode according to an embodiment of the application;
  • 6B is a schematic structural diagram of adjacent reference pixel selection in INTRA_L_CCLM mode according to an embodiment of the application;
  • 6C is a schematic structural diagram of adjacent reference pixel selection in the INTRA_T_CCLM mode provided by an embodiment of the application;
  • FIG. 7 is a schematic flowchart of another image component prediction method provided by an embodiment of the application.
  • FIG. 8A is a schematic structural diagram of generating 0 effective pixels in the INTRA_LT_CCLM mode according to an embodiment of the application;
  • FIG. 8B is a schematic structural diagram of generating 0 effective pixels in the INTRA_L_CCLM mode according to an embodiment of the application;
  • FIG. 8C is a schematic structural diagram of generating 0 effective pixels in the INTRA_T_CCLM mode according to an embodiment of the application.
  • FIG. 9A is a schematic diagram of a structure for generating 2 effective pixels in the INTRA_LT_CCLM mode according to an embodiment of the application.
  • FIG. 9B is a schematic structural diagram of generating 2 effective pixels in the INTRA_L_CCLM mode according to an embodiment of the application.
  • FIG. 9C is a schematic structural diagram of generating 2 effective pixels in the INTRA_T_CCLM mode according to an embodiment of the application.
  • FIG. 10 is a schematic diagram of a flow chart of model parameter derivation provided by an embodiment of this application.
  • FIG. 11 is a simplified schematic diagram of a model parameter derivation process provided by an embodiment of the application.
  • FIG. 12 is a simplified flowchart of another model parameter derivation provided by an embodiment of this application.
  • FIG. 13 is a schematic diagram of the composition structure of an image component prediction apparatus provided by an embodiment of the application.
  • FIG. 14 is a schematic diagram of a specific hardware structure of an image component prediction apparatus provided by an embodiment of the application.
  • 15 is a schematic diagram of the composition structure of an encoder provided by an embodiment of the application.
  • FIG. 16 is a schematic diagram of the composition structure of a decoder provided by an embodiment of the application.
  • the first image component, the second image component, and the third image component are generally used to characterize the coding block; among them, the three image components are a luminance component, a blue chrominance component, and a red chrominance component.
  • the luminance component is usually represented by the symbol Y
  • the blue chrominance component is usually represented by the symbol Cb or U
  • the red chrominance component is usually represented by the symbol Cr or V; in this way, the video image can be represented in YCbCr format or YUV. Format representation.
  • the first image component may be a luminance component
  • the second image component may be a blue chrominance component
  • the third image component may be a red chrominance component
  • the cross-component prediction technology mainly includes the cross-component linear model prediction (CCLM) mode and the multi-directional linear model prediction (Multi-Directional Linear Model Prediction, MDLM) mode, whether it is based on the model parameters derived from the CCLM mode or the model parameters derived from the MDLM mode, its corresponding prediction model can realize the first image component to the second image component, and the second image component to the first image component , Prediction between image components such as the first image component to the third image component, the third image component to the first image component, the second image component to the third image component, or the third image component to the second image component.
  • CCLM cross-component linear model prediction
  • MDLM Multi-Directional Linear Model Prediction
  • the CCLM mode is used in VVC.
  • the first image component and the second image component For the same coding block, that is, the predicted value of the second image component is constructed according to the reconstruction value of the first image component of the same coding block, as shown in equation (1),
  • i,j represent the position coordinates of the pixel in the coding block
  • i represents the horizontal direction
  • j represents the vertical direction
  • Pred C [i,j] represents the pixel corresponding to the location coordinate [i,j] in the coding block
  • Pred L [i,j] represents the reconstructed value of the first image component corresponding to the pixel with the position coordinate [i,j] in the same coding block (downsampled)
  • ⁇ and ⁇ represent the model parameter.
  • its adjacent areas may include a left adjacent area, an upper adjacent area, a lower left adjacent area, and an upper right adjacent area.
  • three cross-component linear model prediction modes can be included, which are: the intra-CCLM mode adjacent to the left and upper side (can be represented by the INTRA_LT_CCLM mode), and the intra-CCLM mode adjacent to the left and lower left side (It can be represented by INTRA_L_CCLM mode) and the intra-frame CCLM mode adjacent to the upper side and the upper right side (can be represented by INTRA_T_CCLM mode).
  • each mode can select a preset number (such as 4) of adjacent reference pixels for the derivation of model parameters ⁇ and ⁇ , and the biggest difference between these three modes is that they are used to derive the model
  • the selected regions corresponding to the adjacent reference pixels of the parameters ⁇ and ⁇ are different.
  • the upper selection area corresponding to the adjacent reference pixel is W'
  • the left selection area corresponding to the adjacent reference pixel is H'
  • FIG. 1 shows a schematic diagram of the distribution of an effective adjacent area provided by an embodiment of the present application.
  • the left side adjacent area, the lower left side adjacent area, the upper side adjacent area, and the upper right side adjacent area are all valid.
  • the selection areas for the three modes are shown in Figure 2.
  • Figure 2 shows the selection area of INTRA_LT_CCLM mode, including the left adjacent area and upper side adjacent area;
  • (b) shows the selection area of INTRA_L_CCLM mode, including the left adjacent area And the adjacent area on the lower left side;
  • (c) shows the selection area of INTRA_T_CCLM mode, including the adjacent area on the upper side and the adjacent area on the upper right side.
  • reference points for deriving model parameters can be selected in the selection area.
  • the reference points selected in this way can be called adjacent reference pixels, and usually the number of adjacent reference pixels is at most 4; and for a W ⁇ H code block with a certain size, the positions of the adjacent reference pixels Generally certain.
  • the coding block is even divided according to tile-shaped partitions (tile) and slices (slice)
  • the adjacent area may still be invalid at this time, resulting in the number of adjacent reference pixels selected from the adjacent area being less than 4, that is, only 0 or 2 may be selected Adjacent reference pixels; the number of adjacent reference pixels used for model parameter derivation is not uniform, thereby adding additional "copy" operations and increasing computational complexity.
  • the embodiment of the present application provides an image component prediction method by obtaining the image components to be predicted of the coding block in the video image.
  • the corresponding first reference pixel set when the number of effective pixels in the first reference pixel set is less than the preset number, the preset component value is used as the predicted value corresponding to the image component to be predicted; when the first reference pixel set is valid
  • the first reference pixel set is screened to obtain a second reference pixel set, and the number of effective pixels in the second reference pixel set is less than or equal to the preset number ;
  • the preset component value is used as the predicted value corresponding to the image component to be predicted; when the number of effective pixels in the second reference pixel set is equal to the preset
  • the model parameters are determined by the first reference pixel set.
  • the video encoding system 300 includes a transform and quantization unit 301, an intra-frame estimation unit 302, and an intra-frame
  • the encoding unit 309 can implement header information encoding and context-based adaptive binary arithmetic coding (Context-based Adaptive Binary Arithmatic Coding, CABAC).
  • a video coding block can be obtained by dividing the coding tree unit (CTU), and then the residual pixel information obtained after intra-frame or inter-frame prediction is paired by the transform and quantization unit 301
  • the video coding block is transformed, including transforming the residual information from the pixel domain to the transform domain, and quantizing the resulting transform coefficients to further reduce the bit rate;
  • the intra-frame estimation unit 302 and the intra-frame prediction unit 303 are used for Perform intra prediction on the video encoding block; specifically, the intra estimation unit 302 and the intra prediction unit 303 are used to determine the intra prediction mode to be used to encode the video encoding block;
  • the motion compensation unit 304 and the motion estimation unit 305 is used to perform inter-frame prediction coding of the received video coding block with respect to one or more blocks in one or more reference frames to provide temporal prediction information;
  • the motion estimation performed by the motion estimation unit 305 is for generating a motion vector
  • the motion vector can estimate the motion of the video coding block, and then the motion compensation
  • the context content can be based on adjacent coding blocks, can be used to encode information indicating the determined intra prediction mode, and output the code stream of the video signal; and the decoded image buffer unit 310 is used to store reconstructed video coding blocks for Forecast reference. As the video image coding progresses, new reconstructed video coding blocks will be continuously generated, and these reconstructed video coding blocks will be stored in the decoded image buffer unit 310.
  • the video decoding system 400 includes a decoding unit 401, an inverse transform and inverse quantization unit 402, and an intra-frame
  • the decoding unit 401 can implement header information decoding and CABAC decoding
  • the filtering unit 405 can implement deblocking filtering and SAO filtering.
  • the code stream of the video signal is output; the code stream is input into the video decoding system 400, and first passes through the decoding unit 401 to obtain the decoded transform coefficient;
  • the inverse transform and inverse quantization unit 402 performs processing to generate a residual block in the pixel domain;
  • the intra prediction unit 403 can be used to generate data based on the determined intra prediction mode and the data from the previous decoded block of the current frame or picture The prediction data of the current video decoding block;
  • the motion compensation unit 404 determines the prediction information for the video decoding block by analyzing the motion vector and other associated syntax elements, and uses the prediction information to generate the predictability of the video decoding block being decoded Block; by summing the residual block from the inverse transform and inverse quantization unit 402 and the corresponding predictive block generated by the intra prediction unit 403 or the motion compensation unit 404 to form a decoded video block; the decoded video signal Through the filtering unit 405 in order to remove the block effect artifacts, the video quality can be
  • the image component prediction method in the embodiment of this application is mainly applied to the part of the intra prediction unit 303 shown in FIG. 3 and the part of the intra prediction unit 403 shown in FIG. 4, and is specifically applied to CCLM prediction in intra prediction section. That is to say, the image component prediction method in the embodiment of this application can be applied to a video encoding system, a video decoding system, or even a video encoding system and a video decoding system at the same time.
  • the embodiment of this application There is no specific limitation.
  • the "coding block in the video image” specifically refers to the current coding block in the intra prediction; when the method is applied to the intra prediction unit 403 part, “coding in the video image "Block” specifically refers to the current decoded block in intra prediction.
  • FIG. 5 shows a schematic flowchart of an image component prediction method provided by an embodiment of the present application.
  • the method may include:
  • S501 Obtain a first reference pixel set corresponding to a to-be-predicted image component of a coding block in a video image
  • a video image can be divided into multiple coding blocks, and each coding block can include a first image component, a second image component, and a third image component.
  • the coding block in the embodiment of the present application is a video image to be The current block for encoding.
  • the image component to be predicted is the first image component
  • the second image component needs to be predicted by the prediction model
  • the image component to be predicted is the second image component
  • the third image component is predicted by the prediction model
  • the image component to be predicted is the third image component.
  • the first reference pixel set is determined by the encoding block
  • the adjacent area on the left side and the adjacent area on the upper side are composed of adjacent reference pixels, as shown in Figure 2(a);
  • the first reference pixel set is composed of the adjacent area on the left side of the coding block It is composed of adjacent reference pixels in the adjacent area on the lower left side, as shown in Figure 2 (b);
  • the first reference pixel set is composed of the adjacent area on the upper side of the coding block and the adjacent area on the upper right side.
  • the area is composed of adjacent reference pixels, as shown in Figure 2 (c).
  • the acquiring the first reference pixel set corresponding to the to-be-predicted image component of the coding block in the video image may include:
  • S501a-1 Obtain reference pixels adjacent to at least one side of the coding block; wherein, the at least one side includes the left side of the coding block and/or the upper side of the coding block;
  • S501a-2 Based on the reference pixel points, form a first reference pixel set corresponding to the image component to be predicted.
  • At least one side of the coding block may include the left side of the coding block and/or the upper side of the coding block; that is, at least one side of the coding block may refer to the upper side of the coding block, or it may refer to the upper side of the coding block.
  • the left side of the coding block may even refer to the upper side and the left side of the coding block, which is not specifically limited in the embodiment of the present application.
  • the first reference pixel set at this time can be the sum of the reference pixels adjacent to the left side of the encoding block and the encoding
  • the upper side of the block is composed of adjacent reference pixels.
  • the first reference pixel set can be composed of the adjacent pixels on the left side of the encoding block. It is composed of reference pixels adjacent to the side; when the adjacent area on the left is an invalid area and the adjacent area on the upper side is an effective area, then the first reference pixel set can be composed of the upper side of the coding block. It is composed of adjacent reference pixels.
  • the acquiring the first reference pixel set corresponding to the to-be-predicted image component of the coding block in the video image may include:
  • S501b-1 Obtain a reference row or reference pixel in a reference column adjacent to the coding block; wherein the reference row is composed of the upper side of the coding block and the rows adjacent to the upper right side Yes, the reference column is composed of columns adjacent to the left side and the lower left side of the coding block;
  • S501b-2 Based on the reference pixels, form a first reference pixel set corresponding to the image component to be predicted.
  • the reference row adjacent to the coding block may be composed of the upper side of the coding block and the rows adjacent to the upper right side of the coding block
  • the reference column adjacent to the coding block may be composed of the coding block.
  • the left side of the block and the columns adjacent to the lower left side; the reference row or reference column adjacent to the coding block can refer to the reference row adjacent to the upper side of the coding block, or it can refer to the The reference column adjacent to the left side may even refer to the reference row or reference column adjacent to other sides of the coding block, which is not specifically limited in the embodiment of the present application.
  • the adjacent reference rows of the coding blocks will describe the reference behaviors with adjacent sides above, and the reference columns adjacent to the coding blocks will take the reference columns adjacent to the left as an example. description.
  • the reference pixels in the reference row adjacent to the coding block may include reference pixels adjacent to the upper side and the upper right side (also referred to as adjacent reference pixels corresponding to the upper side and the upper right side) Point), where the upper side represents the upper side of the coding block, and the upper right side represents the side length of the upper side of the coding block that is horizontally extended to the right and the same height as the current coding block; in the reference column adjacent to the coding block
  • the reference pixels of may also include reference pixels adjacent to the left side and the lower left side (also referred to as the adjacent reference pixels corresponding to the left side and the lower left side), where the left side represents the code
  • the left side of the block and the lower left side represent the side length that is the same width as the current decoded block, which is vertically extended downward from the left side of the encoding block; however, the embodiment of the present application does not specifically limit it.
  • the first reference pixel set at this time may be composed of reference pixels in the reference column adjacent to the coding block;
  • the first reference pixel set at this time may be composed of reference pixels in the reference row adjacent to the coding block.
  • the number of effective pixels can be determined based on the effectiveness of adjacent areas, or can be determined based on the number of effective pixels in the selected area. For some special cases, such as the boundary condition of the coding block, unpredictable conditions, and the situation where the coding sequence makes it impossible to obtain adjacent reference pixels, etc., even the case of coding block division according to tiles and slices, at this time the adjacent area on the left , The adjacent area on the lower left side, the adjacent area on the upper side, and the adjacent area on the upper right side are not all valid areas, and there may be invalid areas, resulting in the number of effective pixels in the selected area being less than the preset number, so that the first The number of effective pixels in a reference pixel set is less than the preset number.
  • the preset number is a pre-set judgment value of the number of effective pixels, which is used to measure whether the image component to be predicted performs the steps of model parameter derivation and construction of the prediction model; wherein, the preset number can be Four, but the embodiments of the present application do not specifically limit them. In this way, it is assumed that the preset number is 4, that is, when the number of effective pixel points in the first reference pixel set is 0 or 2, the preset component value can be directly used as the corresponding image component to be predicted The predicted value to reduce computational complexity.
  • the preset component value is used to indicate a preset fixed value corresponding to the image component to be predicted (may also be referred to as a default value).
  • the preset component value is mainly related to the bit information of the current video image. Therefore, in some embodiments, for S502, when the number of effective pixel points in the first reference pixel set is less than a preset number, the preset component value is used as the corresponding value of the image component to be predicted
  • the predicted value can include:
  • S502a Determine a preset component range corresponding to the image component to be predicted based on the bit information of the video image
  • S502b Determine an intermediate value of the preset component range according to the preset component range, and use the intermediate value as the predicted value corresponding to the image component to be predicted; wherein the intermediate value is expressed as a preset component value .
  • the middle value of the preset component range corresponding to the image component to be predicted may be used as the preset component value, and then it is used as the predicted value corresponding to the image component to be predicted.
  • the bit depth of the image component to be predicted is represented by BitDepthC
  • the calculation method for obtaining the intermediate value of the image component to be predicted is 1 ⁇ (BitDepthC-1); this calculation method can be specifically set according to the actual situation.
  • the embodiments are not specifically limited.
  • the chrominance component is used as an example for the image component to be predicted. Assuming that the current video image is an 8-bit video, the component range corresponding to the chrominance component is 0-255, and the intermediate value is 128 at this time. The component value is preset at this time It can be 128, that is, the default value is 128; assuming that the current video image is a 10-bit video, the component range corresponding to the chrominance component is 0 ⁇ 1023, and the intermediate value is 512 at this time. At this time, the preset component value can be 512, that is The default value is 512. In this embodiment of the present application, the bit information of the video image will be 10 bits as an example, that is, the preset component value is 512.
  • the method may further include:
  • S502c For each pixel in the coding block, use the preset component value to fill in the predicted value of the image component to be predicted for each pixel.
  • the preset component value is 512 and the image component to be predicted is a chrominance component
  • the chrominance prediction value corresponding to each pixel in the coding block 512 can be directly used to fill the chrominance prediction value.
  • the first parameter pixel set there may be some unimportant reference pixels (for example, these reference pixels have poor correlation) or some abnormal reference pixels, in order to ensure the accuracy of the prediction model , These reference pixels need to be removed to obtain the second reference pixel set, where the number of effective pixels in the second reference pixel set is less than or equal to the preset number.
  • the number of effective pixels included in the second reference pixel set is usually selected as 4 in actual applications, but the embodiment of the present application does not specifically limit it.
  • the first reference pixel set can also be filtered to obtain the second reference pixel set; After the second reference pixel set, it is still necessary to judge according to the number of effective pixels in the second reference pixel set and the preset number; among them, if the number of effective pixels in the second reference pixel set is less than the preset number, this The preset component value can be used as the predicted value corresponding to the image component to be predicted; if the number of effective pixels in the second reference pixel set is equal to the preset number, the model parameters can be derived from the second reference pixel set at this time .
  • the screening the first reference pixel set to obtain the second reference pixel set may include:
  • the effective pixel corresponding to the position of the pixel to be selected is selected from the first reference pixel set, and the selected effective pixel is formed into a second reference pixel set;
  • the number of effective pixel points in the second reference pixel set is less than or equal to the preset number.
  • the screening of the first reference pixel set can be based on the position of the reference pixel to be selected, or based on the intensity of the image component (such as brightness value, chroma value, etc.).
  • the filtered reference pixels to be selected form a second reference pixel set. The following will describe the position of the reference pixel to be selected as an example.
  • the filtering process is as follows (where availT represents the validity of adjacent rows on the current coding block, availL represents the validity of the left adjacent column of the current coding block, nTbW represents the width of the current coding block, and nTbH represents the height of the current coding block):
  • the intra prediction mode of the current block is INTRA_LT_CCLM mode
  • numTopRight represents the number of effective pixels in the upper right side nTbW range
  • numLeftBelow represents the number of effective pixels in the lower left side nTbH.
  • the number of pixels screened on each side is represented by cntN
  • the starting point position is represented by startPosN
  • the selection interval is represented by pickStepN
  • the position of the pixel to be selected is represented by pickPosN[pos].
  • variable numIs4N indicates whether to filter pixels on only one side:
  • variable startPosN represents the starting point position:
  • startPosN numSampN>>(2+numIs4N)
  • variable pickStepN represents the point selection interval:
  • N is replaced by T and L respectively, which can respectively indicate the case of filtering pixels on the upper side and filtering on the left, that is, the N side here represents the T side or the L side.
  • the validity availN of the N side is TRUE and the selected intra mode predModeIntra is INTRA_LT_CCLM mode or INTRA_N_CCLM mode
  • the number of pixels cntN and the position of the pixel to be selected pickPosN[pos] to be selected on the N side are as follows Show (It should be noted that the total number of pixels to be screened should be cntT+cntL):
  • cntN is set to 0, that is, the number of pixels to be screened is 0.
  • the second step is to obtain adjacent luminance reconstruction samples pY[x][y]:
  • the down-sampled reconstructed brightness value pSelDsY[idx]with idx 0...cntL-1 of the point selected on the side.
  • pSelComp[3] is set to pSelComp[0]
  • pSelComp[2] is set to pSelComp[1]
  • pSelComp[0] is set to pSelComp[1]
  • pSelComp[1] is set to pSelComp[ 3], where Comp is replaced by DsY and C to represent the reconstructed luminance and chrominance of the selected adjacent samples.
  • the array minGrpIdx and maxGrpIdx are derived as follows,
  • the derivation process of linear model parameters a, b and k is as follows (here, a is the slope (the difference in chromaticity than the difference in brightness), b is the intercept, and k is the shift to a. save),
  • 2 adjacent reference pixels to be selected can be filtered out in the upper selection area W', and their corresponding positions are S[ W'/4,-1] and S[3W'/4,-1]; 2 adjacent reference pixels to be selected can be screened out in the left selection area H', and their corresponding positions are respectively S[-1, H'/4] and S[-1,3H'/4]; these 4 adjacent reference pixels to be selected form a second reference pixel set, as shown in FIG. 6A.
  • the adjacent area on the left side and the adjacent area on the upper side of the coding block are both effective, and in order to maintain the same resolution of the luminance component and the chrominance component, the luminance component needs to be down-sampled, so that The down-sampled luminance component and chrominance component have the same resolution.
  • the left side adjacent area and the lower left side adjacent area of the coding block are both effective, and in order to maintain the same resolution of the luminance component and the chrominance component, the luminance component still needs to be down-sampled, so that The down-sampled luminance component and chrominance component have the same resolution.
  • the upper adjacent area and the upper right adjacent area of the coding block are both effective, and in order to maintain the same resolution of the luminance component and the chrominance component, the luminance component still needs to be down-sampled, so that The down-sampled luminance component and chrominance component have the same resolution.
  • the second reference pixel set can be obtained, and the second reference pixel set 4 effective pixels are included;
  • the second reference pixel set is obtained.
  • the number of effective pixels in the second reference pixel set can be less than the preset number, or greater than or equal to the preset number. If the number of effective pixels in the second reference pixel set is less than the preset number, then the preset component value is directly used as the predicted value corresponding to the image component to be predicted; if the number of effective pixels in the second reference pixel set is greater than When the number is equal to or equal to the preset number, the model parameters are determined by the second reference pixel set, and the prediction model corresponding to the image component to be predicted is obtained according to the model parameters.
  • the second reference pixel set obtained after such screening is either less than the preset number (the second reference pixel set is less than 4 effective pixels Points), or equal to the preset number (the second reference pixel set includes 4 effective pixel points).
  • the prediction model can be a linear model or a nonlinear model; among them, the nonlinear model can be a nonlinear form such as a quadratic curve, or a nonlinear form composed of multiple linear models, such as multiple models.
  • the cross-component prediction technology of CCLM Multiple Model CCLM, MMLM
  • CCLM Multiple Model CCLM, MMLM
  • the prediction model can be used to implement the prediction processing of the image component to be predicted, so as to obtain the predicted value corresponding to the image component to be predicted.
  • the model parameters can be determined according to the second reference pixel set.
  • the prediction model corresponding to the chroma component can also be obtained according to the model parameters, as shown in equation (1); then the prediction model is used to perform the prediction processing on the chroma component to obtain the prediction corresponding to the chroma component value.
  • the method may further include:
  • the model parameters (such as ⁇ and ⁇ ) need to be determined through the first reference pixel set, and then based on the model parameters Obtain the prediction model corresponding to the image component to be predicted to obtain the predicted value corresponding to the image component to be predicted for each pixel in the coding block.
  • the prediction model corresponding to the chrominance component shown in formula (1) can be obtained; then the prediction model shown in formula (1) is used Perform prediction processing on the chrominance component of each pixel in the coding block, so that the predicted value corresponding to the chrominance component of each pixel can be obtained.
  • FIG. 7 shows a schematic flowchart of another image component prediction method provided by an embodiment of the present application. As shown in FIG. 7, after S501, the method may further include:
  • S701 Determine the number of effective pixels in the first reference pixel set, and determine whether the number of effective pixels is less than a preset number
  • the method may further include:
  • S702 Determine whether the number of effective pixels in the second reference pixel set is less than a preset number.
  • the number of effective pixels can be determined based on the effectiveness of adjacent regions.
  • step S502 is executed;
  • step S504 is executed;
  • step S505 is executed.
  • the preset number can be four. A detailed description will be given below taking the preset number equal to 4 as an example.
  • the model parameter derivation uses generally 4 reference pixels, you can also first The first reference pixel set is screened so that the number of effective pixels in the first reference pixel set is 4; then the model parameters are derived based on these 4 effective pixels, and the image to be predicted is obtained according to the model parameters The prediction model corresponding to the component to obtain the prediction value corresponding to the image component to be predicted.
  • the image component to be predicted is a chrominance component
  • the chrominance component is predicted by the luminance component.
  • the numbers of the 4 effective pixels selected through the screening are 0, 1, 2, and 3 respectively.
  • 2 pixels with larger brightness values can be further selected (can include the pixel with the largest brightness value and the pixel with the next largest brightness value)
  • 2 pixels with smaller brightness value can include the pixel with the smallest brightness value and the pixel with the next smallest brightness value).
  • two arrays of minIdx[2] and maxIdx[2] can be set to store two sets of pixels respectively. Initially, the effective pixels numbered 0 and 2 are put into minIdx[2], and the numbers are 1 and 3. Put the effective pixels into maxIdx[2], as shown below,
  • the two pixels with the smaller brightness value can be stored in minIdx[2], and the two pixels with the larger brightness value are stored in maxIdx[2].
  • the details are as follows Show,
  • Step1 if(L[minIdx[0]]>L[minIdx[1]],swap(minIdx[0],minIdx[1])
  • Step2 if(L[maxIdx[0]]>L[maxIdx[1]],swap(maxIdx[0],maxIdx[1])
  • Step3 if(L[minIdx[0]]>L[maxIdx[1]],swap(minIdx,maxIdx)
  • Step4 if(L[minIdx[1]]>L[maxIdx[0]],swap(minIdx[1],maxIdx[0])
  • the average value is calculated for the brightness values corresponding to the two smaller pixels, and the brightness value corresponding to the first average point is expressed as luma min , and the brightness values corresponding to the two larger pixels are averaged
  • the brightness value corresponding to the second average point can be expressed as luma max ; in the same way, the chromaticity values corresponding to the two average points can also be expressed as chroma min and chroma max respectively, as shown below.
  • chroma min (chroma 0 min +chroma 1 min +1)>>1
  • chroma max (chroma 0 max +chroma 1 max +1)>>1
  • model parameters ⁇ and ⁇ can be calculated by formula (2),
  • the model parameter ⁇ is the slope in the prediction model
  • the model parameter ⁇ is the intercept in the prediction model.
  • the coding block is divided according to tiles and slices.
  • the left adjacent area, the lower left adjacent area, the upper adjacent area, and the upper right adjacent area are not all valid areas. There may be invalid areas, resulting in the first reference pixel set
  • the number of effective pixels is less than the preset number.
  • the preset component value As the predicted value corresponding to the image component to be predicted, it may include:
  • the preset component value is used as the predicted value corresponding to the image component to be predicted.
  • the preset component value is used as the predicted value corresponding to the image component to be predicted .
  • the preset component value is used as the predicted value corresponding to the image component to be predicted.
  • the preset number is 4, whether it is the case that the number of effective pixels in the first reference pixel set is less than the preset number, or the number of effective pixels in the second reference pixel set is less than the preset number In the case of the number of pixels, the number of effective pixels is 0 or 2.
  • the selection area W' 0 at this time, as shown in FIG. 8C.
  • the area filled with gray diagonal lines represents an invalid area.
  • the number of effective pixels is determined based on the effectiveness of the adjacent area; that is, the number of effective pixels in the first reference pixel set can be determined according to the effectiveness of the adjacent area.
  • the model parameter ⁇ can be set to 0 and the model parameter ⁇ can be set to the preset component value corresponding to the image component to be predicted.
  • the predicted value Pred C [i,j] corresponding to the chrominance component of all pixels in the current coding block can be filled with the preset component value, that is, the default value of the chrominance component ;
  • the default value is the middle value of the chrominance component.
  • the component range corresponding to the chrominance component is 0-255, and the intermediate value is 128 at this time.
  • the preset component value can be 128; assuming that the current video image is 10 bits For video, the component range corresponding to the chrominance component is 0-1023, and the intermediate value is 512 at this time. At this time, the preset component value can be 512.
  • the adjacent area on the side with side length 2 is valid, and the side with side length N
  • the number of effective pixels can be determined based on the effectiveness of adjacent areas, or based on the number of effective pixels in the selected area, or based on other judgment conditions.
  • the application examples are not specifically limited. In this way, the number of effective pixels in the first reference pixel set can be determined according to the effectiveness of the adjacent regions.
  • the model parameter ⁇ can also be set to 0, and the model parameter ⁇ can also be set to the preset component value corresponding to the image component to be predicted.
  • the predicted value Pred C [i,j] corresponding to the chrominance component of all pixels in the current coding block can be filled with the preset component value, that is, the default value of the chrominance component .
  • FIG. 10 shows a schematic flowchart of a model parameter derivation provided by an embodiment of the present application.
  • the image component to be predicted is a chrominance component
  • first obtain adjacent reference pixels from the selected area to form the first adjacent reference pixel set ; then determine the number of effective pixels in the first adjacent reference pixel set
  • the first reference pixel set is filtered to obtain the second reference pixel set, and then the number of effective pixels in the second adjacent reference pixel set is determined
  • the model parameter ⁇ is set to 0, and the model parameter ⁇ is set to the default value.
  • the predicted value corresponding to the chroma component is filled with the default Value; when the number of effective pixels in the first reference pixel set or the second reference pixel set is 2, the processing steps are the same as when the number of effective pixels is 0; and for the second reference pixel set
  • the number of effective pixels is 4, the two pixels with the larger value of the chroma component and the two pixels with the smaller value are obtained after 4 comparisons, and then two average points are calculated; based on the two average points
  • the model parameters ⁇ and ⁇ are derived, and the chromaticity component is predicted according to the constructed prediction model.
  • the filling method can reduce the calculation complexity when the number of reference pixels in the selected area is less than 4, and can also maintain the coding and decoding performance basically unchanged.
  • the model parameter derivation process is unified, that is, for the number of effective pixels used for model parameter derivation in the first reference pixel set, when the number of effective pixels in the first reference pixel set is greater than or equal to
  • the first reference pixel set is screened for effective pixels to obtain the second reference pixel set, and then the number of effective pixels in the second adjacent reference pixel set is determined; when the second reference pixel set is valid
  • the current coding block needs to perform the steps of deriving model parameters under CCLM and constructing a prediction model; when the number of effective pixels in the first reference pixel set or the second reference pixel set is less than the preset number
  • the current coding block can use the default value to fill in the predicted value corresponding to the image component to be predicted of the coding block. Therefore, the embodiment of the present application may also provide a simplified process for deriving model parameters, as shown in FIG. 11.
  • the model parameter derivation process shown in Figure 11 is more streamlined.
  • the image component to be predicted is a chrominance component, and the preset component value is 512.
  • the number of effective pixels in the adjacent reference pixel set when the number of effective pixels in the first reference pixel set or the second reference pixel set is less than the preset number, the model parameter ⁇ is set to 0, and the model parameter ⁇ is set At this time, the predicted value corresponding to the chrominance component is filled with 512; when the number of effective pixels in the second reference pixel set meets the preset number, the two values of the chrominance component with larger values are obtained after 4 comparisons. Pixels and two pixels with smaller values, and then two average points are calculated; model parameters ⁇ and ⁇ are derived based on the two average points, and the chroma component is predicted according to the constructed prediction model.
  • the coding block whose number of effective pixels in the second reference pixel set meets the preset number can perform the derivation of model parameters in CCLM mode; and for coding with the number of effective pixels less than the preset number Blocks are directly filled with default values, which can reduce the computational complexity when the number of reference pixels in the selected area is less than the preset number, and can also maintain the codec performance basically unchanged.
  • the preset number in the embodiment of the present application may be four.
  • the number of effective pixels in the first reference pixel set can be determined according to the number of effective pixels in the selected area. Therefore, the embodiment of the present application may also provide another simplified process for deriving model parameters, as shown in FIG. 12.
  • the image component to be predicted is a chrominance component and the preset component value is 512
  • the model parameters ⁇ and ⁇ are derived, and the chromaticity component is predicted according to the
  • the default value filling method can reduce the computational complexity when the number of reference pixels in the selected area is less than the preset number, and the codec performance can be maintained basically unchanged.
  • the preset number in the embodiment of the present application may be four.
  • VVC defines two variables, numSampL and numSampT.
  • the variable numSampL represents the total number of pixels in the selected area H'
  • the variable numSampT represents the total number of pixels in the selected area W':
  • the effectiveness of the selected area needs to be considered at the same time, that is, the variables numSampL and numSampT only represent the number of effective pixels in the above range.
  • VVC also defines that when the variables numSampL and numSampT are both 0 (this will result in the number of effective pixels that can be filtered for model parameter derivation is 0), then directly set the predicted value corresponding to the chrominance component Is the default value, otherwise you need to perform the derivation of the model parameters, as shown below,
  • This embodiment provides an image component prediction method by obtaining a first reference pixel set corresponding to the image component to be predicted of a coding block in a video image; when the number of effective pixels in the first reference pixel set is less than a preset number , Using the preset component value as the predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set is filtered to obtain the first reference pixel set Two reference pixel sets, the number of effective pixels in the second reference pixel set is less than or equal to the preset number; when the number of effective pixels in the second reference pixel set is less than the preset number, the preset component value is taken as The predicted value corresponding to the image component to be predicted; when the number of effective pixel points in the second reference pixel set is equal to the preset number, the model parameters are determined by the second reference pixel set, and the image to be predicted is obtained according to the model parameters
  • the method may further include:
  • the preset component value is used as the to-be-predicted The predicted value corresponding to the image component
  • the CCLM mode is adopted to realize the prediction processing of the image component to be predicted.
  • the CCLM mode can be disabled at this time, for example, the flag of whether the CCLM mode is used is set to "disabled" CCLM mode", at this time, directly fill the predicted value corresponding to the image component to be predicted as the default value; only when the number of effective pixels in the second reference pixel set is greater than or equal to the preset number, the CCLM mode will be used, for example, The flag of whether the CCLM mode is used is set to "enable CCLM mode". At this time, the prediction processing of the image component to be predicted can be realized through the CCLM mode.
  • the image component to be predicted is a chrominance component, and the preset number is 4, then for all situations where 2 effective pixels may be generated (wherein, for the judgment method for generating 2 effective pixels, The embodiments of this application are not specifically limited).
  • the model parameter ⁇ can also be set to 0, and the model parameter ⁇ can be set to the intermediate value (also referred to as the default value) corresponding to the chrominance component, so that all pixels in the encoding block can be set
  • the predicted values corresponding to the chrominance components of are filled with default values; in addition, for all situations where 2 effective pixels may be generated, numSampL and numSampT can also be set to 0 at this time, thereby setting the value of all pixels in the encoding block
  • the predicted values corresponding to the chrominance components are all filled with default values.
  • the predicted value corresponding to the chrominance component can be directly filled with the default value; or for all cases where 2 effective pixels may be generated, the CCLM mode can be disabled; or for all cases If 2 or 0 effective pixels may be generated, the CCLM mode may be disabled; or for all situations where 2 or 0 effective pixels may be generated, the predicted value corresponding to the chrominance component may be directly filled with the default value .
  • the image component prediction method in the embodiment of this application is based on the latest VVC reference software VTM5.0. Under All intra conditions, the test sequence required by JVET is tested according to the general test conditions, and the Y component, Cb component and Cr component are BD- The average changes in rate are 0.00%, 0.02%, and 0.02%, respectively, which shows that this application basically has no effect on the coding and decoding performance.
  • this application may have the following beneficial effects:
  • this application can unify the derivation process of model parameters in CCLM mode.
  • an additional "copy” operation is required to generate 4 usable pixels, which can perform the same as the case of 4 effective pixels , And then complete the derivation of model parameters.
  • this application can save additional "copy” operations, and at the same time align the processing when the number of effective pixels is 2 with the processing when the number of effective pixels is 0. At this time, no additional operations are needed.
  • the same processing module is directly used, so that the unity of the linear model parameter derivation process can be realized.
  • this application can also reduce the computational complexity when there are two effective pixels used for model parameter derivation in CCLM mode.
  • this application can save these operations and directly fill all the predicted values Pred C [i,j] corresponding to the chrominance components of all pixels in the current coding block as the preset component values, that is, the default values of the chrominance components, and It does not affect the codec performance.
  • This embodiment provides an image component prediction method.
  • the number of effective pixels in the first reference pixel set is compared with a preset number.
  • the preset default value is directly used as the predicted value corresponding to the image component to be predicted; when the number of effective pixels in the second reference pixel set is greater than or equal to the preset number
  • the model parameters are determined according to the first reference pixel set to construct the prediction model of the image components to be predicted, thereby unifying the derivation process of the model parameters; in addition, the number of effective pixels in the first reference pixel set is less than the predicted In the case of setting the number, since no additional processing modules are added, the computational complexity is also reduced.
  • FIG. 13 shows a schematic diagram of the composition structure of an image component prediction apparatus 130 provided by an embodiment of the present application.
  • the image component prediction device 130 may include: an acquisition unit 1301, a prediction unit 1302, and a screening unit 1303, where
  • the obtaining unit 1301 is configured to obtain a first reference pixel set corresponding to the image component to be predicted of the coding block in the video image;
  • the prediction unit 1302 is configured to use the preset component value as the predicted value corresponding to the image component to be predicted when the number of effective pixel points in the first reference pixel set is less than the preset number;
  • the screening unit 1303 is configured to screen the first reference pixel set to obtain a second reference pixel set when the number of effective pixel points in the first reference pixel set is greater than or equal to a preset number; wherein , The number of effective pixels in the second reference pixel set is less than or equal to a preset number;
  • the prediction unit 1302 is further configured to use the preset component value as the predicted value corresponding to the image component to be predicted when the number of effective pixel points in the second reference pixel set is less than the preset number; and When the number of effective pixels in the second reference pixel set is equal to the preset number, the model parameters are determined by the second reference pixel set, and the prediction model corresponding to the image component to be predicted is obtained according to the model parameters; wherein , The prediction model is used to implement prediction processing on the image component to be predicted, so as to obtain the predicted value corresponding to the image component to be predicted.
  • the acquiring unit 1301 is specifically configured to acquire reference pixels adjacent to at least one side of the encoding block; wherein, the at least one side includes the left side of the encoding block and/or the The upper side of the coding block; and based on the reference pixels, a first reference pixel set corresponding to the image component to be predicted is formed.
  • the acquiring unit 1301 is specifically configured to acquire reference pixels in a reference row or reference column adjacent to the encoding block; wherein, the reference row is defined by the upper side of the encoding block And the rows adjacent to the upper right side, the reference column is composed of the columns adjacent to the left side and the lower left side of the coding block; and based on the reference pixels, the waiting Predict the first reference pixel set corresponding to the image component.
  • the screening unit 1303 is specifically configured to determine the position of the pixel to be selected based on the pixel position and/or image component intensity corresponding to each adjacent reference pixel in the first reference pixel set; and Determine the position of the pixel to be selected, select the effective pixel corresponding to the position of the pixel to be selected from the first reference pixel set, and compose the selected effective pixel to form a second reference pixel set; wherein, the The number of effective pixels in the second reference pixel set is less than or equal to the preset number.
  • the image component prediction apparatus 130 may further include a determining unit 1304 configured to determine a preset component range corresponding to the image component to be predicted based on the bit information of the video image; and The preset component range determines an intermediate value of the preset component range, and uses the intermediate value as a predicted value corresponding to the image component to be predicted; wherein the intermediate value is expressed as a preset component value.
  • a determining unit 1304 configured to determine a preset component range corresponding to the image component to be predicted based on the bit information of the video image; and The preset component range determines an intermediate value of the preset component range, and uses the intermediate value as a predicted value corresponding to the image component to be predicted; wherein the intermediate value is expressed as a preset component value.
  • the image component prediction device 130 may further include a filling unit 1305 configured to use the preset component value for each pixel in the coding block to determine The predicted image components are filled with predicted values.
  • the prediction unit 1302 is further configured to perform prediction processing on the image component to be predicted for each pixel in the coding block based on the prediction model to obtain the image component to be predicted for each pixel. Predictive value.
  • the value of the preset number is 4; the prediction unit 1302 is further configured to set the preset component when the number of effective pixel points in the first reference pixel set is 0 or 2. Value as the predicted value corresponding to the image component to be predicted;
  • the prediction unit 1302 is further configured to use the preset component value as the predicted value corresponding to the image component to be predicted when the number of effective pixel points in the second reference pixel set is 0 or 2. .
  • the image component prediction device 130 may further include a judging unit 1306 configured to: when the number of effective pixels in the first reference pixel set is less than a preset number or the second reference pixel set When the number of effective pixels in the pixel set is less than the preset number, the preset component value is used as the predicted value corresponding to the image component to be predicted; and when the number of effective pixels in the second reference pixel set is greater than or equal to When the number is preset, the CCLM mode is adopted to realize the prediction processing of the image components to be predicted.
  • a "unit" may be a part of a circuit, a part of a processor, a part of a program, or software, etc., of course, may also be a module, or may be non-modular.
  • the various components in this embodiment may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be realized in the form of hardware or software function module.
  • the integrated unit is implemented in the form of a software function module and is not sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of this embodiment is essentially or It is said that the part that contributes to the existing technology or all or 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 and includes several instructions to enable a computer device (which can A personal computer, server, or network device, etc.) or a processor (processor) executes all or part of the steps of the method described in this embodiment.
  • the aforementioned storage media include: U disk, mobile hard disk, read only memory (Read Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program codes.
  • this embodiment provides a computer storage medium that stores an image component prediction program that, when executed by at least one processor, implements the method described in any of the foregoing embodiments step.
  • FIG. 14 shows the specific hardware structure of the image component prediction device 130 provided by the embodiment of the present application, which may include: a network interface 1401, a memory 1402, and a processor 1403;
  • the various components are coupled together through the bus system 1404.
  • the bus system 1404 is used to implement connection and communication between these components.
  • the bus system 1404 also includes a power bus, a control bus, and a status signal bus.
  • various buses are marked as the bus system 1404 in FIG. 14.
  • the network interface 1401 is used to receive and send signals in the process of sending and receiving information with other external network elements;
  • the memory 1402 is used to store a computer program that can run on the processor 1403;
  • the processor 1403 is configured to execute: when the computer program is running:
  • the first reference pixel set is screened to obtain a second reference pixel set; wherein, the second reference pixel set The number of effective pixels is less than or equal to the preset number;
  • the model parameters are determined by the second reference pixel set, and the prediction model corresponding to the image component to be predicted is obtained according to the model parameters ;
  • the prediction model is used to implement the prediction processing of the image component to be predicted to obtain the predicted value corresponding to the image component to be predicted.
  • the memory 1402 in the embodiment of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), and electrically available Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory.
  • the volatile memory may be a random access memory (Random Access Memory, RAM), which is used as an external cache.
  • RAM static random access memory
  • DRAM dynamic random access memory
  • DRAM synchronous dynamic random access memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • Enhanced SDRAM, ESDRAM Synchronous Link Dynamic Random Access Memory
  • Synchlink DRAM Synchronous Link Dynamic Random Access Memory
  • DRRAM Direct Rambus RAM
  • the processor 1403 may be an integrated circuit chip with signal processing capabilities. In the implementation process, the steps of the foregoing method can be completed by hardware integrated logic circuits in the processor 1403 or instructions in the form of software.
  • the aforementioned processor 1403 may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (ASIC), a ready-made programmable gate array (Field Programmable Gate Array, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
  • DSP Digital Signal Processor
  • ASIC application specific integrated circuit
  • FPGA ready-made programmable gate array
  • the methods, steps, and logical block diagrams disclosed in the embodiments of the present application can be implemented or executed.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • the steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor.
  • the software module can be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers.
  • the storage medium is located in the memory 1402, and the processor 1403 reads the information in the memory 1402, and completes the steps of the foregoing method in combination with its hardware.
  • the embodiments described herein can be implemented by hardware, software, firmware, middleware, microcode, or a combination thereof.
  • the processing unit can be implemented in one or more Application Specific Integrated Circuits (ASIC), Digital Signal Processing (DSP), Digital Signal Processing Equipment (DSP Device, DSPD), programmable Logic device (Programmable Logic Device, PLD), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), general-purpose processors, controllers, microcontrollers, microprocessors, and others for performing the functions described in this application Electronic unit or its combination.
  • ASIC Application Specific Integrated Circuits
  • DSP Digital Signal Processing
  • DSP Device Digital Signal Processing Equipment
  • PLD programmable Logic Device
  • PLD Field-Programmable Gate Array
  • FPGA Field-Programmable Gate Array
  • the technology described herein can be implemented through modules (such as procedures, functions, etc.) that perform the functions described herein.
  • the software codes can be stored in the memory and executed by the processor.
  • the memory can be implemented in the processor or external to the processor.
  • the processor 1403 is further configured to execute the steps of the method described in any one of the foregoing embodiments when the computer program is running.
  • FIG. 15 shows a schematic diagram of the composition structure of an encoder provided by an embodiment of the present application.
  • the encoder 150 may at least include the image component prediction device 130 described in any one of the foregoing embodiments.
  • FIG. 16 shows a schematic diagram of the composition structure of a decoder provided by an embodiment of the present application.
  • the decoder 160 may at least include the image component prediction device 130 described in any of the foregoing embodiments.
  • the first reference pixel set corresponding to the image component to be predicted of the coding block in the video image is obtained; when the number of effective pixel points in the first reference pixel set is less than the preset number, the preset component value is taken as The predicted value corresponding to the image component to be predicted; when the number of effective pixels in the first reference pixel set is greater than or equal to the preset number, the first reference pixel set is screened to obtain the second reference pixel set.
  • the number of effective pixels in the pixel set is less than or equal to the preset number; when the number of effective pixels in the second reference pixel set is less than the preset number, the preset component value is used as the predicted value corresponding to the image component to be predicted;
  • the model parameters are determined by the second reference pixel set, and the prediction model corresponding to the image component to be predicted is obtained according to the model parameters, and the prediction model is used for Realize the prediction processing of the image component to be predicted to obtain the predicted value corresponding to the image component to be predicted; in this way, when the number of effective pixels in the first reference pixel set is less than the preset number or the effective pixel points in the second reference pixel set When the number is less than the preset number, the preset default value is directly used as the predicted value corresponding to the image component to be predicted; only when the number of effective pixels in the second reference pixel set meets the preset number, the first The reference pixel set determines the model parameters to

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PL19934681.8T PL3952308T3 (pl) 2019-06-25 2019-06-25 Sposób i urządzenie do predykcji składowych obrazu oraz komputerowy nośnik danych
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US18/622,202 US12537939B2 (en) 2019-06-25 2024-03-29 Image component prediction method and device, and computer storage medium
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024528567A (ja) * 2021-07-06 2024-07-30 ノキア テクノロジーズ オサケユイチア クロス成分パラメータ計算のための装置、方法、およびコンピュータプログラム

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20250139895A (ko) * 2019-06-25 2025-09-23 광동 오포 모바일 텔레커뮤니케이션즈 코포레이션 리미티드 이미지 컴포넌트의 예측 방법, 장치 및 컴퓨터 저장 매체

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180376151A1 (en) * 2017-05-30 2018-12-27 Thomson Licensing Method and device for picture encoding and decoding
US20190068969A1 (en) * 2017-08-21 2019-02-28 Qualcomm Incorporated System and method of cross-component dynamic range adjustment (CC-DRA) in video coding
US20190149838A1 (en) * 2017-11-14 2019-05-16 Qualcomm Incorporated Affine motion vector prediction in video coding
CN109905715A (zh) * 2019-02-26 2019-06-18 北京三体云联科技有限公司 插入sei数据的码流转换方法及系统

Family Cites Families (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009044744A1 (ja) 2007-10-01 2009-04-09 Sharp Kabushiki Kaisha 画像符号化装置、画像符号化方法、画像符復号化システム
WO2012134046A2 (ko) * 2011-04-01 2012-10-04 주식회사 아이벡스피티홀딩스 동영상의 부호화 방법
CN102209243B (zh) 2011-05-27 2012-10-24 山东大学 基于线性模型的深度图帧内预测方法
JP5149427B2 (ja) 2011-06-22 2013-02-20 シャープ株式会社 符号化装置、復号化装置、符復号化システム、符号化方法及び復号化方法
GB2495941B (en) * 2011-10-25 2015-07-08 Canon Kk Method and apparatus for processing components of an image
CN103379321B (zh) 2012-04-16 2017-02-01 华为技术有限公司 视频图像分量的预测方法和装置
EP2920964B1 (en) * 2013-03-26 2018-05-09 MediaTek Inc. Method of cross color intra prediction
CN105474639B (zh) * 2013-07-10 2018-08-07 凯迪迪爱通信技术有限公司 视频编码装置、视频解码装置、视频系统、视频编码方法、视频解码方法以及程序
US10200700B2 (en) * 2014-06-20 2019-02-05 Qualcomm Incorporated Cross-component prediction in video coding
CN105704491B (zh) 2014-11-28 2020-03-13 同济大学 图像编码方法、解码方法、编码装置和解码装置
CN107211121B (zh) 2015-01-22 2020-10-23 联发科技（新加坡）私人有限公司 视频编码方法与视频解码方法
WO2016195460A1 (ko) * 2015-06-05 2016-12-08 한양대학교 산학협력단 화면 내 예측에 대한 부호화/복호화 방법 및 장치
EP3360329A4 (en) 2015-11-18 2019-04-10 MediaTek Inc. METHOD AND DEVICE FOR AN INTRAPRADICATION MODE WITH AN INTRAPREDICATION FILTER FOR VIDEO AND IMAGE COMPRESSION
US20170150156A1 (en) * 2015-11-25 2017-05-25 Qualcomm Incorporated Illumination compensation with non-square predictive blocks in video coding
CN105306944B (zh) 2015-11-30 2018-07-06 哈尔滨工业大学 混合视频编码标准中色度分量预测方法
CN106998470B (zh) * 2016-01-25 2020-03-20 华为技术有限公司 解码方法、编码方法、解码设备和编码设备
EP3449630B1 (en) 2016-05-28 2024-07-10 Mediatek Inc. Method and apparatus of current picture referencing for video coding
US10484712B2 (en) 2016-06-08 2019-11-19 Qualcomm Incorporated Implicit coding of reference line index used in intra prediction
US10652575B2 (en) 2016-09-15 2020-05-12 Qualcomm Incorporated Linear model chroma intra prediction for video coding
KR102357282B1 (ko) * 2016-10-14 2022-01-28 세종대학교산학협력단 영상의 부호화/복호화 방법 및 장치
US10477240B2 (en) 2016-12-19 2019-11-12 Qualcomm Incorporated Linear model prediction mode with sample accessing for video coding
US11025903B2 (en) 2017-01-13 2021-06-01 Qualcomm Incorporated Coding video data using derived chroma mode
JP2020120141A (ja) * 2017-05-26 2020-08-06 シャープ株式会社 動画像符号化装置及び動画像復号装置、フィルタ装置
CN107580222B (zh) * 2017-08-01 2020-02-14 北京交通大学 一种基于线性模型预测的图像或视频编码方法
WO2019059107A1 (ja) * 2017-09-20 2019-03-28 パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカ 符号化装置、復号装置、符号化方法及び復号方法
GB2567249A (en) * 2017-10-09 2019-04-10 Canon Kk New sample sets and new down-sampling schemes for linear component sample prediction
CN118413648A (zh) * 2017-11-28 2024-07-30 Lx 半导体科技有限公司 图像编码/解码方法、图像数据的传输方法和存储介质
MX2020007868A (es) * 2018-01-26 2020-09-07 Interdigital Vc Holdings Inc Metodo y aparato para codificacion y decodificacion de video basado en un modelo lineal receptivo a muestras vecinas.
GB2571311B (en) * 2018-02-23 2021-08-18 Canon Kk Methods and devices for improvement in obtaining linear component sample prediction parameters
WO2019221465A1 (ko) * 2018-05-14 2019-11-21 인텔렉추얼디스커버리 주식회사 영상 복호화 방법/장치, 영상 부호화 방법/장치 및 비트스트림을 저장한 기록 매체
WO2020015433A1 (en) * 2018-07-15 2020-01-23 Huawei Technologies Co., Ltd. Method and apparatus for intra prediction using cross-component linear model
CN109005408B (zh) * 2018-08-01 2020-05-29 北京奇艺世纪科技有限公司 一种帧内预测方法、装置及电子设备
KR20250139895A (ko) * 2019-06-25 2025-09-23 광동 오포 모바일 텔레커뮤니케이션즈 코포레이션 리미티드 이미지 컴포넌트의 예측 방법, 장치 및 컴퓨터 저장 매체

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180376151A1 (en) * 2017-05-30 2018-12-27 Thomson Licensing Method and device for picture encoding and decoding
US20190068969A1 (en) * 2017-08-21 2019-02-28 Qualcomm Incorporated System and method of cross-component dynamic range adjustment (CC-DRA) in video coding
US20190149838A1 (en) * 2017-11-14 2019-05-16 Qualcomm Incorporated Affine motion vector prediction in video coding
CN109905715A (zh) * 2019-02-26 2019-06-18 北京三体云联科技有限公司 插入sei数据的码流转换方法及系统

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024528567A (ja) * 2021-07-06 2024-07-30 ノキア テクノロジーズ オサケユイチア クロス成分パラメータ計算のための装置、方法、およびコンピュータプログラム
JP7756231B2 (ja) 2021-07-06 2025-10-17 ノキア テクノロジーズ オサケユイチア クロス成分パラメータ計算のための装置、方法、およびコンピュータプログラム
US12542916B2 (en) 2021-07-06 2026-02-03 Nokia Technologies Oy Apparatus, a method and a computer program for cross-component parameter calculation

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