WO2020192109A1 - 图像分量预测方法、编码器、解码器以及存储介质 - Google Patents

图像分量预测方法、编码器、解码器以及存储介质 Download PDF

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Publication number
WO2020192109A1
WO2020192109A1 PCT/CN2019/113765 CN2019113765W WO2020192109A1 WO 2020192109 A1 WO2020192109 A1 WO 2020192109A1 CN 2019113765 W CN2019113765 W CN 2019113765W WO 2020192109 A1 WO2020192109 A1 WO 2020192109A1
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current block
candidate
pixels
reference pixel
pixel
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PCT/CN2019/113765
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English (en)
French (fr)
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马彦卓
霍俊彦
万帅
张伟
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Oppo广东移动通信有限公司
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Priority to KR1020217034571A priority Critical patent/KR20210138760A/ko
Priority to CN201980093368.8A priority patent/CN113508584A/zh
Priority to EP19921790.2A priority patent/EP3930324A4/en
Priority to JP2021556936A priority patent/JP2022528331A/ja
Priority to CN202111193882.4A priority patent/CN113992916B/zh
Publication of WO2020192109A1 publication Critical patent/WO2020192109A1/zh
Priority to US17/480,865 priority patent/US20220007011A1/en

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    • 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
    • H04N19/102—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
    • H04N19/105—Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
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    • 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
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    • 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
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    • 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
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    • H04N19/186—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 a colour or a chrominance component
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Definitions

  • the embodiments of the present application relate to the field of image processing technologies, and in particular, to an image component prediction method, an encoder, a decoder, and a storage medium.
  • the prediction model construction it is necessary to use the prediction model construction, and then the predicted value of the video image in the video codec is derived from the constructed prediction model.
  • the number of sample points currently used for model parameter derivation is relatively large, the computational complexity and memory bandwidth are high; at the same time, there may be abnormal sample points in these sample points, resulting in inaccurate prediction model construction .
  • the embodiments of the application provide an image component prediction method, encoder, decoder, and storage medium.
  • By reducing the number of pixels in the reference pixel set not only the computational complexity and memory bandwidth are reduced, but the accuracy of the prediction model is improved. Therefore, the prediction accuracy of the image components to be predicted is improved, and the prediction efficiency of the video image is improved.
  • an image component prediction method which includes:
  • the reference pixel subset is used to calculate the model parameters of the prediction model; wherein, the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • an encoder which includes a first determining unit and a first calculating unit, wherein:
  • a first determining unit configured to determine a first reference pixel set of the image component to be predicted of the current block
  • the first determining unit is further configured to determine a reference pixel subset from the first reference pixel set; wherein the reference pixel subset includes one or more candidate pixels selected from the first reference pixel set;
  • the first calculation unit is configured to use the reference pixel subset to calculate model parameters of the prediction model; wherein the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • an embodiment of the present application provides an encoder.
  • the encoder includes a first memory and a first processor, where:
  • the first memory is used to store a computer program that can run on the first processor
  • the first 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 decoder, which includes a second determining unit and a second calculating unit, where:
  • a second determining unit configured to determine the first reference pixel set of the image component to be predicted of the current block
  • the second determining unit is further configured to determine a reference pixel subset from the first reference pixel set; wherein the reference pixel subset includes one or more candidate pixels selected from the first reference pixel set;
  • the second calculation unit is configured to use the reference pixel subset to calculate model parameters of the prediction model; wherein the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • an embodiment of the present application provides a decoder, which includes a second memory and a second processor, wherein:
  • the second memory is used to store a computer program that can run on the second processor
  • the second 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 that stores an image component prediction program, and when the image component prediction program is executed by the first processor or the second processor, the implementation is as described in the first aspect. Methods.
  • the embodiments of the present application provide an image component prediction method, an encoder, a decoder, and a storage medium to determine a first reference pixel set of an image component to be predicted of a current block; from the first reference pixel set, determine a reference pixel subset Wherein, the reference pixel subset includes one or more candidate pixels selected from the first reference pixel set; the reference pixel subset is used to calculate the model parameters of the prediction model; wherein, the prediction model is used for the current block to be
  • the predicted image components are subjected to cross-component prediction processing; in this way, because the first reference pixel set is filtered, unimportant reference pixels or abnormal reference pixels can be removed, thereby reducing the number of pixels in the first reference pixel set.
  • the accuracy of the prediction model can be improved; because the prediction model is used to realize the prediction processing of the image components to be predicted through the model parameters, thereby improving The prediction accuracy of the image component to be predicted improves the prediction efficiency of the video image.
  • FIG. 1 is a schematic flowchart of an image component prediction method provided by an embodiment of this application
  • 2A is a schematic structural diagram of a reference pixel position provided by an embodiment of the application.
  • 2B is a schematic structural diagram of another reference pixel position provided by an embodiment of the application.
  • FIG. 3 is a schematic structural diagram for selecting a subset of adjacent reference pixels on the side of the current block provided by an embodiment of the application;
  • FIG. 4 is a schematic diagram of another structure for selecting a subset of adjacent reference pixels on the upper side of the current block provided by an embodiment of the application;
  • FIG. 5 is a schematic diagram of a comparison structure of a prediction model provided by an embodiment of the application.
  • FIG. 6 is a schematic flowchart of another image component prediction method provided by an embodiment of the application.
  • FIG. 7 is a schematic diagram of the composition structure of an encoder provided by an embodiment of the application.
  • FIG. 8 is a schematic diagram of a specific hardware structure of an encoder provided by an embodiment of the application.
  • FIG. 9 is a schematic diagram of the composition structure of a decoder provided by an embodiment of the application.
  • FIG. 10 is a schematic diagram of a specific hardware 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 (CB); among them, the three image components are a luminance component and a blue chrominance component. And a red chrominance component, specifically, the luminance component is usually represented by the symbol Y, the blue chrominance component is usually represented by the symbol Cb or U, and the red chrominance component is usually represented by the symbol Cr or V; in this way, the video image can be in YCbCr format It can also be expressed in YUV format.
  • 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 cross-component Linear Model Prediction (CCLM) mode and Multi-Directional Linear Model Prediction (MDLM) mode.
  • CCLM mode and MDLM The prediction model constructed by the mode can realize the first image component to the second image component, the second image component to the first image component, the first image component to the third image component, the third image component to the first image component, and the Prediction between image components such as the second image component to the third image component, or the third image component to the second image component.
  • the prediction technology within the image component it mainly includes the chrominance component compensation technology and the luminance component compensation technology, such as IC technology and LIC technology.
  • the prediction model constructed by the prediction technology within the image component can realize the first image component to the second Prediction techniques within image components such as prediction of an image component, prediction of a second image component to a second image component, or prediction of a third image component to a third image component.
  • the following description will mainly take the prediction model constructed by the prediction technology within the image component as an example.
  • the embodiment of the present application provides an image component prediction method, by determining the first reference pixel set of the image component to be predicted of the current block; determining the reference pixel subset from the first reference pixel set; wherein, the reference pixel The subset includes one or more candidate pixels selected from the first reference pixel set; the reference pixel subset is used to calculate the model parameters of the prediction model; wherein the prediction model is used to span the image components to be predicted in the current block.
  • Component prediction processing in this way, due to the screening process of the first reference pixel set, unimportant reference pixels or abnormal reference pixels can be removed, thereby reducing the number of pixels in the first reference pixel set, not only Computational complexity and memory bandwidth can also improve the accuracy of the prediction model, thereby improving the prediction accuracy of the image components to be predicted, and improving the prediction efficiency of the video image.
  • the image component prediction method of the embodiment of the present application can be applied to both a video encoding system and a video decoding system, and can even be applied to both a video encoding system and a video decoding system.
  • the “current block” specifically refers to the current coding block in intra prediction
  • the “current block” specifically refers to the frame The current decoded block in intra prediction.
  • FIG. 1 shows a schematic flowchart of an image component prediction method provided by an embodiment of the present application.
  • the method may include:
  • S101 Determine the first reference pixel set of the image component to be predicted of the current block
  • S102 Determine a reference pixel subset from the first reference pixel set; wherein the reference pixel subset includes one or more candidate pixels selected from the first reference pixel set;
  • S103 Calculate model parameters of a prediction model by using the reference pixel subset; wherein, the prediction model is used to perform cross-component prediction processing on the image components to be predicted of the current block.
  • each current block may include a first image component, a second image component, and a third image component; and the current block is the current prediction of the first image component, the second image component, or the third image component in the video image.
  • the first image component needs to be predicted by the prediction model
  • 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 needs to be predicted by the prediction model
  • the image component to be predicted is the third image component.
  • the first reference pixel set is the reference pixel set corresponding to the prediction model constructed in the current related technical solution.
  • the first reference pixel set there may be some unimportant reference pixels (for example, these reference pixels have poor correlation) or some abnormal reference pixels.
  • these The reference pixel points are eliminated, thereby obtaining a reference pixel subset; according to the reference pixel subset, the accuracy of the prediction model can be ensured, so that the prediction efficiency of the image component to be predicted is high.
  • the first reference pixel set of the image component to be predicted of the current block is first determined; then, the reference pixel subset is determined from the first reference pixel set; wherein, the reference pixel subset includes the first reference pixel set.
  • One or more candidate pixels selected in the reference pixel set then use the reference pixel subset to calculate the model parameters of the prediction model; where the prediction model is used to perform cross-component prediction processing on the image components to be predicted in the current block; Filtering the first reference pixel set can remove unimportant reference pixels or reference pixels that are abnormal, thereby reducing the number of pixels in the first reference pixel set, not only reducing computational complexity and memory bandwidth, Moreover, the accuracy of the prediction model can be improved, thereby improving the prediction accuracy of the image components to be predicted, and improving the prediction efficiency of the video image.
  • the determination of the first reference pixel set may be obtained based on the adjacent reference pixels around the current block, or may be obtained by reconstructing the adjacent reference pixels inside the block.
  • the embodiment of the present application does not specifically limit it. Describe them separately.
  • the determining the first reference pixel set of the image component to be predicted of the current block may include:
  • At least one side of the current block includes at least one of the following: upper side, left side, upper right Side and lower left side;
  • the first reference pixel set is obtained.
  • FIG. 2A shows a schematic structural diagram of a reference pixel position provided by an embodiment of the present application.
  • the reference pixels are located around the current block, that is, the reference pixels adjacent to at least one side of the current block, and at least one side of the current block can refer to the left side of the current block or the current block.
  • the upper side of the block may even refer to the left side and upper side of the current block; the embodiment of the present application does not specifically limit it.
  • the determining the first reference pixel set of the image component to be predicted of the current block may include:
  • Acquiring reference pixels adjacent to at least one side of the current block wherein the at least one side includes the left side of the current block and/or the upper side of the current block;
  • the first reference pixel set is obtained.
  • At least one side of the current block may include the left side of the current block and/or the upper side of the current block; that is, at least one side of the current block may refer to the upper side of the current block, or it may refer to the upper side of the current block.
  • the left side of the current block may even refer to the upper side and the left side of the current block, which is not specifically limited in the embodiment of the present application.
  • the first reference pixel set at this time can be composed of the reference pixels adjacent to the left side of the current block and the upper side of the current block. It is composed of adjacent reference pixels.
  • the first reference pixel set can be composed of adjacent to the left side of the current block.
  • the adjacent area on the left is an invalid area and the adjacent area on the upper side is an effective area
  • the first reference pixel set can be composed of reference pixels adjacent to the upper side of the current block. Points.
  • the first reference pixel set of the image component to be predicted of the block may include:
  • the first reference pixel set is obtained.
  • the reference row adjacent to the current block may be composed of the upper side of the current block and the row adjacent to the upper right side
  • the reference column adjacent to the current block may be composed of the current 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 current block can refer to the reference row adjacent to the upper side of the current block, or it can refer to the current block
  • the reference column adjacent to the left side may even refer to the reference row or reference column adjacent to the other side of the current block, which is not specifically limited in the embodiment of the present application.
  • the reference row adjacent to the current block will be described as an example of the reference behavior with adjacent sides above, and the reference column adjacent to the current block will be taken as an example of the reference column adjacent to the left side. description.
  • the reference pixels in the reference row adjacent to the current 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) Dot), where the upper side represents the upper side of the current block, and the upper right side represents the side length of the current block’s upper side horizontally extending to the right and the same height as the current block; in the reference column adjacent to the current block
  • the reference pixels 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 current block
  • the left side 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 current block; however, the embodiment of the present application does not specifically limit it.
  • the first reference pixel set at this time can be composed of reference pixels in the reference column adjacent to the current block; when the upper side is adjacent When the area and the upper-right adjacent area are valid areas, the first reference pixel set at this time may be composed of reference pixels in a reference row adjacent to the current block.
  • the determining the first reference pixel set of the image component to be predicted of the current block may include:
  • the reconstruction block obtain reference pixels adjacent to at least one side of the reconstruction block; wherein, the reconstruction block is an image block that is adjacent to the current block and has been coded and reconstructed. At least one side includes: lower side, right side, or lower side and right side;
  • the first reference pixel set is obtained.
  • FIG. 2B shows a schematic structural diagram of a reference pixel position provided in an embodiment of the present application.
  • the reference pixel is located inside the reconstruction block, that is, the reference pixel adjacent to at least one side of the reconstruction block, and at least one side of the reconstruction block can refer to the right side of the reconstruction block, or it can refer to the reconstruction block.
  • the lower side of the block may even refer to the right side and the lower side of the reconstructed block, which is not specifically limited in the embodiment of the present application.
  • the reference pixels can be called "pixels used to build the prediction model".
  • the current block is already in the coding and reconstruction stage. At this time, a prediction model is constructed.
  • the prediction model can be It is convenient for other coding blocks in subsequent images to use.
  • the adjacent reference pixels in the reconstruction block can be used to obtain the first reference pixel set, which is convenient for subsequent construction of the prediction model of the current block; on the other hand, the prediction model corresponding to the reconstruction block can also be directly borrowed , Regard it as the prediction model of the current block; that is to say, for the current block being coded, the use of the relevant information of the reconstructed block in the adjacent area can be directly used by the corresponding prediction model, without the need to use the reconstructed block
  • the adjacent reference pixels are used to construct the prediction model.
  • the first reference pixel set After the first reference pixel set is obtained, there may be some unimportant reference pixels (for example, these reference pixels have poor correlation) or some abnormal reference pixels in the first reference pixel set. To ensure the accuracy of model parameter derivation, these reference pixels need to be eliminated to obtain a reference pixel subset; in this way, based on the reference pixel subset, the accuracy of the prediction model can be guaranteed, and the prediction efficiency of the image components to be processed is high .
  • the determining a reference pixel subset according to the first reference pixel set may include:
  • a reference pixel corresponding to the candidate position is selected from the first reference pixel set, and the selected parameter pixels are formed into the reference pixel subset.
  • the determining the candidate position of the candidate pixel based on at least one side of the current block or the reconstructed block may include:
  • the candidate position is determined based on the pixel position corresponding to the reference pixel adjacent to the at least one side.
  • the determining the candidate position of the candidate pixel based on at least one side of the current block or the reconstructed block may include:
  • the candidate position is determined based on the image component intensity value corresponding to the reference pixel adjacent to the at least one side.
  • the determining the candidate position of the candidate pixel based on at least one side of the current block or the reconstructed block may include:
  • the candidate position is determined based on the pixel position and the image component intensity value corresponding to the reference pixel adjacent to the at least one side.
  • the image component intensity can be represented by image component values, such as brightness value, chroma value, etc.; here, the larger the image component value, the higher the image component intensity.
  • the reference pixels selected in the embodiments of the present application may be selected by the candidate positions of the candidate pixels; wherein, the candidate positions may be determined according to the pixel position, or may be determined according to the intensity value of the image component (such as luminance value, chrominance value) Etc.) It is determined that the embodiments of this application do not make specific limitations.
  • the reference pixel subset is formed by filtering the first reference pixel set and then selecting some reference pixels; while the model parameters are calculated based on the reference pixel subset; in this way, due to the reference
  • the reduction of the number of samples in the pixel subset also reduces the number of samples required to calculate the model parameters, thereby achieving the goal of reducing computational complexity and memory bandwidth (or called memory bandwidth).
  • the reference pixels selected in the embodiment of the present application can be selected by referring to the pixel position corresponding to the pixel, or can be selected based on the intensity value of the image component corresponding to the reference pixel (such as luminance value, chrominance value, etc.)
  • the embodiments of this application do not make specific limitations.
  • the first reference pixel set is screened either by the pixel position corresponding to the reference pixel or the image component intensity value corresponding to the reference pixel to select the appropriate reference pixel, and then form the reference pixel subset; in this way, according to the reference
  • the model parameters derived from the pixel subset are more accurate, so that the prediction model constructed based on the model parameters can also be more accurate.
  • the determining the candidate position of the candidate pixel based on at least one edge of the current block or the reconstructed block may include:
  • the candidate position is determined according to the preset number of candidate pixels and the length of the at least one side; wherein the length of the at least one side is equal to the number of pixels included in the at least one side.
  • the corresponding prediction model can be used directly, without the need to construct the prediction model through the adjacent reference pixels of the reconstructed block; therefore, the embodiments of this application will mainly use At least one edge of the current block is taken as an example to describe how to determine the candidate position of the candidate pixel.
  • the preset number of candidate pixels represents a preset number of pixels to be sampled, that is, the number of pixels included in the reference pixel subset.
  • the candidate position of the candidate pixel can be calculated according to the side length of at least one side and the preset number of candidate pixels; then according to the candidate position, the first reference pixel set Select appropriate reference pixels to form a subset of reference pixels.
  • the model parameters calculated based on the reference pixel subset are more accurate, and the constructed prediction model can also be more accurate, thereby improving the prediction accuracy of the image components to be predicted and improving the prediction efficiency of the video image.
  • the first sampling interval may be calculated first, and then the at least one edge is sampled according to the first sampling interval to determine the candidate pixel position of the candidate pixel corresponding to the at least one edge. Therefore, in some embodiments, the determining the candidate position of the candidate pixel based on at least one edge of the current block or the reconstructed block may include:
  • a reference point is determined from the at least one edge, and the candidate position is determined according to the first sampling interval.
  • the reference point may be the midpoint of the at least one side, or the first reference pixel position to the left of the midpoint of the at least one side, or the midpoint of the at least one side.
  • the position of the first reference pixel point to the right of the point may even be the position of other reference pixel points on the at least one side, which is not specifically limited in the embodiment of the present application.
  • the midpoint of the at least one side may be determined according to the length of the at least one side, and then the midpoint of the at least one side is used as the reference point.
  • the reference point may be the midpoint of the at least one side, or the first reference pixel position where the midpoint of the at least one side is leftward, or the midpoint of the at least one side rightward
  • the first reference pixel position of may even be another reference pixel position of the at least one side, which is not specifically limited in the embodiment of the present application.
  • the first reference pixel position of the middle position to the right or left can be used as the reference point of the side; if the current block’s The left side is taken as an example for description, then the position of the first reference pixel point lower or upper than the middle position can be used as the reference point of the side.
  • the preset number of reference pixels for the edge, or the initial offset for the edge from the starting position according to the preset offset, and the offset reference pixel position as the starting point to obtain a new edge, and then The middle position corresponding to the new edge is used as the reference point.
  • the middle position of the left side or the upper side of the current block is between two points.
  • the first pixel to the left of the middle position is used as the midpoint of the side; however, in the embodiment of the present application, the first pixel to the right of the middle position may also be used as the midpoint of the side.
  • Figure 4 the first pixel to the left of the middle position (3 in Figure 3) is taken as the midpoint of the side. Since the preset number of samples is 2, then the reference pixel to be selected can be determined
  • the positions (for example, the gray points in Fig. 3) are 1 and 5.
  • the corresponding reference pixels can also be selected to form a reference pixel subset. Therefore, in this embodiment of the application, for the upper side of the current block, either the first pixel to the right of the middle position can be used as the midpoint of the side, or the first pixel to the left of the middle position As the midpoint of the side, the embodiment of the present application does not specifically limit it; in addition, for the left side of the current block, either the first pixel point lower than the middle position can be used as the midpoint of the side, or the middle position The first pixel on the upper side is taken as the midpoint of the side, which is not specifically limited in the embodiment of the present application.
  • the following will take the upper side of the current block as an example, but the image component prediction method in the embodiment of the present application is also applicable to the left side of the current block, or even the right side of the reconstructed block or reconstruction
  • the lower side of the block is not specifically limited in the embodiment of the present application.
  • the second reference pixel set can also be constructed according to equations (1) and (2),
  • ⁇ represents the sampling interval
  • length represents the number of reference pixels in a row adjacent to the upper side of the current block, or the number of reference pixels in a column adjacent to the left side of the current block
  • N 2 represents the current
  • the number of reference pixels in the reference pixel subset expected to constitute the block generally, the left side and the upper side are each one-half, but the embodiment of this application does not specifically limit it
  • shift represents the selection of the reference pixel Starting point position.
  • N 2 is equal to 4
  • 1 is the starting point position
  • 4 is the sampling interval
  • the position of the reference pixel to be selected can be determined, such as 1 and 5, and then the corresponding reference pixel can be selected to form a reference pixel subset.
  • the values of the preset number of samples corresponding to the left side and the preset number of samples corresponding to the upper side may be the same or different, which is not specifically limited in the embodiment of the present application.
  • the first sampling interval corresponding to the side can be calculated.
  • the middle position of the left side or the upper side of the current block is between two points, and the calculation is The midpoint value of is a non-integer, and the calculated reference pixel position is also a non-integer; however, if the length of the left side or top side of the current block is not an integer multiple of 2, then the left side or top of the current block The middle position of the side will not be between two points.
  • the calculated midpoint value is an integer
  • the calculated reference pixel position is also an integer; that is, the calculated midpoint value can be an integer, It may also be a non-integer; correspondingly, the calculated reference pixel position may also be an integer or a non-integer; the embodiment of the present application does not specifically limit it.
  • the calculated reference pixel position is also an integer.
  • the calculated reference pixel position can be directly used as a candidate position; when the calculated midpoint value is When it is a non-integer, correspondingly, the calculated reference pixel position is also a non-integer.
  • the candidate position can be determined by rounding to the larger or smaller.
  • the method may further include:
  • the candidate position is determined according to the second sampling interval.
  • the first sampling interval can be fine-tuned, for example, the first sampling interval can be increased or decreased by 1 to obtain the second sampling interval.
  • the adjusted second sampling interval can be 3 or 5.
  • a small range for example, plus 1 or minus 1 may be adjusted, but the specific setting of the adjustment range is not specifically limited in the embodiment of the present application.
  • the method may further include:
  • a candidate position corresponding to one side of the reference point is determined according to the first sampling interval, and a candidate position corresponding to the other side of the reference point is determined according to the second sampling interval.
  • uniform sampling can be performed according to the first sampling interval or the second sampling interval; non-uniform sampling can also be performed according to the first sampling interval and the second sampling interval, and
  • the candidate positions determined after sampling may be symmetrically distributed on both sides of the reference point, or may be asymmetrically distributed on both sides of the reference point; the embodiment of the present application does not specifically limit it.
  • the reference pixel of the preset number of consecutive samples near the middle position The pixel position is used as the reference pixel position to be selected.
  • This method can be referred to as the solution of continuously taking points from the intermediate position. Specifically, assuming that the reference pixel positions on the row/column adjacent to the upper side or the left side of the current block are numbered starting from 0, then the number of adjacent reference pixels in the reference pixel subset composed in this embodiment is The numbers and the corresponding reference pixel positions to be selected are shown in Table 1. At this time, the consecutive preset number of sampled reference pixel positions near the middle position can be used as candidate positions to form a reference pixel subset.
  • the side length of at least one side of the current block Preset number of candidate pixels 2 0,1 2 4 1,2 2 8 2, 3, 4 (or 3, 4, 5) 3 16 6,7,8,9 4 32 13,14,15,16,17,18,19,20 8
  • the reference pixel points of at least one side may also be skipped, that is, the unimportant reference pixels or the abnormal reference pixels are skipped (also can be regarded as Delete processing) to obtain a reference pixel subset; on this basis, that is, after partial reference pixels of at least one side are skipped, a second reference pixel set is obtained, and the second reference pixel set is filtered, To get a subset of reference pixels. Therefore, in some embodiments, the determining the candidate position of the candidate pixel based on at least one edge of the current block or the reconstructed block may include:
  • K is a positive integer greater than or equal to 1
  • the preset number of skipped pixels represents a preset number of pixels to be deleted or to be skipped.
  • the starting position of at least one side represents the leftmost edge position of the upper side of the current block or the uppermost edge position of the left side of the current block, and the end position of at least one side represents the rightmost edge of the upper side of the current block. The position or the bottom edge position of the left side of the current block.
  • the value of K can be a preset number of reference pixels, such as 1, 2, or 4; it can also be calculated according to the side length of the current block and the corresponding preset ratio; However, in actual applications, it is still set according to actual conditions, and the embodiments of the present application do not make specific limitations.
  • the preset ratio corresponding to the upper side of the current block can be represented by a first preset ratio
  • the preset ratio corresponding to the left side of the current block can be represented by a second preset ratio
  • the first preset ratio is equal to
  • the value of the second preset ratio may be the same or different, and the embodiment of the present application does not specifically limit it.
  • the leftmost edge position of the upper side can be started At the beginning, determine the position corresponding to the continuous K pixels to be skipped to the right, and then continuously skip the K pixels to be skipped to obtain the new upper side; this time, you can use the new upper side
  • the side length and the preset number of candidate pixels are used to determine the candidate position corresponding to the new upper side, so that the selected candidate pixels form a reference pixel subset; if at least one side is the left side of the current block, you can Starting from the top edge position of the left side, determine the position corresponding to the continuous K pixels to be skipped downward, and then continuously skip the K pixels to be skipped to obtain the new left side; this time
  • the candidate position corresponding to the new left side can be determined according to the side length of the new left side and the preset number of candidate pixels, so that the selected candidate pixels form a reference
  • K continuous pixels to be skipped can be determined to the left Point corresponding to the position, and then continuously skip the K pixels to be skipped to obtain the new upper side; at this time, the new upper side can be determined according to the side length of the new upper side and the preset number of candidate pixels Candidate positions corresponding to the upper side, so that the selected candidate pixels form a reference pixel subset; if at least one side is the left side of the current block, then it can start from the bottom edge position of the left side and determine upwards The positions corresponding to the continuous K pixels to be skipped, and then the K pixels to be skipped are continuously skipped to obtain the new left side; at this time, the side length of the new left side and the preset candidate The number of pixels, the candidate position corresponding to the new left side is determined, and the selected candidate pixels are formed into a reference pixel subset.
  • the embodiment of the present application uses part of the pixels in the first reference pixel set obtained by the reference pixels adjacent to the current block (ie, a subset of reference pixels) to derive the model corresponding to a complex model (such as a nonlinear model or a multi-model) parameter. Since unimportant reference pixels or abnormal reference pixels have been eliminated from the obtained subset (ie reference pixel subset), it has fewer reference pixels, which not only reduces the computational complexity It also improves the accuracy of complex models and improves the accuracy of the image components to be processed and the prediction efficiency of video images.
  • a complex model such as a nonlinear model or a multi-model
  • the model parameters of the prediction model can be calculated based on the reference pixel subset, so as to facilitate the construction of the prediction model. Therefore, in some embodiments, for S103, using the reference pixel subset to calculate the model parameters of the prediction model may include:
  • the adjacent pixel reconstruction value of the image component to be predicted corresponding to the current block and the adjacent pixel reconstruction value of the image component to be predicted corresponding to the reference block are obtained; wherein the current block is located at the Nth Frames of video images, the reference block is located in the N-1th frame of video images;
  • the model parameters are calculated.
  • the reference block and the current block are not located in the same frame, and the relationship between the two is an inter-frame relationship.
  • the reference block and the current block are located in different frames of video images, and the frame where the reference block is located is the frame before the frame where the current block is located, that is, the current block is in the Nth frame of video image, and the reference block is in the Nth frame.
  • -1 frame of video image in addition, the position of the current block in the Nth frame of video image and the position of the reference block in the N-1th frame of video image will have a motion vector (MV) offset.
  • MV motion vector
  • model parameters include a first model parameter ⁇ and a second model parameter ⁇ .
  • ⁇ and ⁇ There are many ways to calculate ⁇ and ⁇ . It can be a preset factor calculation model constructed by the least squares method, or a preset factor calculation model constructed by the maximum and minimum values, or even other ways.
  • the preset factor calculation model is not specifically limited in the embodiment of this application.
  • the prediction model is mainly used for the prediction processing of the brightness component, such as IC technology or LIC technology; at this time, ⁇ and ⁇ can be compared with the brightness component corresponding to the current block.
  • the adjacent pixel reconstruction value and the luminance component adjacent pixel reconstruction value corresponding to the reference block are derived by minimizing the regression error.
  • L(n) represents the reconstruction value of the adjacent pixels of the luminance component corresponding to the reference block
  • C(n) represents the reconstruction value of the adjacent pixels of the luminance component corresponding to the current block
  • N is the number of adjacent pixels of the luminance component corresponding to the current block.
  • the preset factor calculation model constructed by the maximum and minimum values provides a simplified version of the model parameter derivation method. Specifically, the maximum value can be searched for in the reconstructed values of the adjacent pixels of the luminance component corresponding to the reference block. And the minimum value, according to the principle of "two points determine a line" to derive ⁇ and ⁇ , as the preset factor calculation model shown in formula (4):
  • L max and L min represent the maximum and minimum values found in the reconstruction values of the adjacent pixels of the luminance component corresponding to the reference block
  • C max and C min represent that the reference pixel at the corresponding position of L max and L min is in the current block.
  • the first model parameter ⁇ and the second model parameter ⁇ can also be obtained through the calculation of formula (4).
  • a predictive model can be constructed. Specifically, based on ⁇ and ⁇ , assuming that the predicted value of the brightness component corresponding to the current block is predicted based on the predicted value of the brightness component corresponding to the reference block, the constructed prediction model is shown in equation (5),
  • i, j represent the position coordinates of the pixel in the current block
  • i represents the horizontal direction
  • j represents the vertical direction
  • Pred 1 [i,j] represents the pixel corresponding to the location coordinate [i,j] in the current block
  • the predicted value of the brightness component, Pred[i,j] represents the predicted value of the brightness component corresponding to the pixel with the position coordinate of [i,j] in the reference block.
  • the prediction model in the embodiment of the present application may be a linear model or a nonlinear model.
  • the non-linear model can be a non-linear form such as a quadratic curve, or a non-linear form composed of multiple linear models.
  • the multi-model CCLM Multiple Model CCLM, MMLM
  • FIG. 5 shows a schematic diagram of a comparative structure of a prediction model provided by an embodiment of the present application.
  • the prediction model in the embodiment of the present application can be used not only for the prediction processing of the luminance component, but also for the prediction processing of the chrominance component.
  • the predicted value of the image component to be predicted (such as the luminance component or the chrominance component) can be updated, so that the prediction of the image component is more accurate, and the prediction accuracy and video of the image component to be predicted can be improved.
  • the purpose of image prediction efficiency can be used not only for the prediction processing of the luminance component, but also for the prediction processing of the chrominance component.
  • the method may further include:
  • the image components to be predicted can be predicted based on the prediction model.
  • the first image component of the reference block can be used to predict the first image component of the current block
  • the brightness component of the reference block can be used to predict the brightness component of the current block to update the predicted value of the brightness component
  • the second image component of the reference block can be used to predict the second image component of the current block.
  • the blue chrominance component of the reference block can be used to predict the blue chrominance component of the current block to update the predicted value of the blue chrominance component
  • the third image component of the reference block can also be used to predict the third image component of the current block.
  • the red chrominance component of the reference block can be used to predict the red chrominance component of the current block to update the predicted value of the red chrominance component. ;
  • the embodiments of this application do not make specific limitations.
  • This embodiment provides an image component prediction method, by determining the first reference pixel set of the image component to be predicted of the current block; determining the reference pixel subset from the first reference pixel set; wherein the reference pixel subset includes One or more candidate pixels selected from the first reference pixel set; use a subset of reference pixels to calculate model parameters of a prediction model; wherein the prediction model is used to perform cross-component prediction processing on the image component to be predicted in the current block;
  • the prediction model is used to perform cross-component prediction processing on the image component to be predicted in the current block;
  • FIG. 6 shows a schematic flowchart of another image component prediction method provided by an embodiment of the present application. As shown in Figure 6, the method may include:
  • S601 Select a part of reference pixels from the first reference pixel set to form a reference pixel subset
  • the reference pixel subset is obtained by selecting some reference pixels from the first reference pixel set; and the model parameters are calculated based on the reference pixel subset; in this way, due to the number of samples in the reference pixel subset The reduction also reduces the number of samples required to calculate the model parameters, thereby achieving the goal of reducing computational complexity and memory bandwidth (or called memory bandwidth).
  • the determining the first reference pixel set of the image component to be predicted of the current block may include:
  • first neighboring pixels of the current block as the first reference pixel set; wherein, the first neighboring pixels are located on the vertical side of the current block and horizontally to the current block. Edges, or pixels adjacent to the vertical and horizontal edges of the current block.
  • the method may further include:
  • the first adjacent pixel is located outside the current block, it is determined that the vertical edge of the current block is the left adjacent column outside the current block, and the horizontal edge of the current block is the upper adjacent column outside the current block. Row.
  • the method may further include:
  • the first neighboring pixel is located in the current block, it is determined that the vertical side of the current block is the right side column in the current block, and the horizontal side of the current block is the lower side of the current block Row.
  • the vertical edge of the current block can be regarded as the left side of the current block, and the horizontal edge of the current block can be regarded as the upper side of the current block;
  • the vertical edge of the current block can be regarded as the right side of the current block, and the horizontal edge of the current block can be regarded as the lower side of the current block.
  • the first reference pixel set can be formed. Since there may be some unimportant reference pixels (for example, these reference pixels have poor correlation) or some abnormal reference pixels in the first reference pixel set, in order to ensure the accuracy of model parameter derivation, these need to be The reference pixels are eliminated, so that a subset of reference pixels can be obtained. Therefore, in some embodiments, the determining a subset of reference pixels may include:
  • the determining the candidate position of the candidate pixel may include:
  • the determining the candidate position of the candidate pixel may include:
  • the determining the candidate position of the candidate pixel may include:
  • the candidate position of the candidate pixel is determined according to the position of the pixel in the first reference pixel set and the image component intensity.
  • the image component intensity can be represented by image component values, such as brightness value, chroma value, etc.; here, the larger the image component value, the higher the image component intensity.
  • the reference pixels selected in the embodiments of the present application may be selected by the candidate positions of the candidate pixels; wherein, the candidate positions may be determined according to the pixel position, or may be determined according to the intensity value of the image component (such as luminance value, chrominance value) Etc.) It is determined that the embodiments of this application do not make specific limitations.
  • the reference pixel subset is formed by filtering the first reference pixel set and then selecting some reference pixels; while the model parameters are calculated based on the reference pixel subset; in this way, due to the reference
  • the reduction of the number of samples in the pixel subset also reduces the number of samples required to calculate the model parameters, thereby achieving the goal of reducing computational complexity and memory bandwidth (or called memory bandwidth).
  • the reference pixels selected in the embodiment of the present application can be selected by referring to the pixel position corresponding to the pixel, or can be selected based on the intensity value of the image component corresponding to the reference pixel (such as luminance value, chrominance value, etc.)
  • the embodiments of this application do not make specific limitations.
  • the first reference pixel set is screened either by the pixel position corresponding to the reference pixel or the image component intensity value corresponding to the reference pixel to select the appropriate reference pixel, and then form the reference pixel subset; in this way, according to the reference
  • the model parameters derived from the pixel subset are more accurate, so that the prediction model constructed based on the model parameters can also be more accurate.
  • the determining the candidate position of the candidate pixel may include:
  • the preset number of candidate pixels represents a preset number of pixels to be sampled, that is, the number of pixels included in the reference pixel subset.
  • the candidate position of the candidate pixel can be calculated according to the side length of at least one side and the preset number of candidate pixels; then according to the candidate position, the first reference pixel set Select appropriate reference pixels to form a subset of reference pixels.
  • the model parameters calculated based on the reference pixel subset are more accurate, and the constructed prediction model can also be more accurate, thereby improving the prediction accuracy of the image components to be predicted and improving the prediction efficiency of the video image.
  • the first sampling interval may be calculated first, and then the at least one edge is sampled according to the first sampling interval to determine the candidate pixel position of the candidate pixel corresponding to the at least one edge. Therefore, in some embodiments, the determining the candidate position of the candidate pixel may include:
  • the first sampling interval is calculated according to the length of the side of the current block and the preset number of candidate pixels.
  • the determining the candidate position of the candidate pixel may include:
  • the first sampling interval is adjusted to obtain the second sampling interval.
  • the first sampling interval can be fine-tuned, for example, the first sampling interval can be increased or decreased by 1 to obtain the second sampling interval.
  • the adjusted second sampling interval can be 3 or 5.
  • a small range for example, plus 1 or minus 1 may be adjusted, but the specific setting of the adjustment range is not specifically limited in the embodiment of the present application.
  • the method may further include:
  • a reference point is determined on the side of the current block, and from the reference point, a candidate position on the side of the current block is determined at the first sampling interval.
  • the method may further include:
  • a reference point is determined on the side of the current block, and candidate positions on both sides of the reference point are determined at the first sampling interval.
  • the method may further include:
  • a reference point is determined on the edge of the current block, and from the reference point, a candidate position on the edge of the current block is determined at the second sampling interval.
  • the method may further include:
  • a reference point is determined on the side of the current block, and candidate positions on both sides of the reference point are determined at the second sampling interval.
  • the reference point may be the midpoint of the at least one side, or the first reference pixel position to the left of the midpoint of the at least one side, or the midpoint of the at least one side.
  • the position of the first reference pixel point to the right of the point may even be the position of other reference pixel points on the at least one side, which is not specifically limited in the embodiment of the present application.
  • the midpoint of the at least one side may be determined according to the length of the at least one side, and then the midpoint of the at least one side is used as the reference point.
  • the reference point may be the midpoint of the at least one side, or the first reference pixel position where the midpoint of the at least one side is leftward, or the midpoint of the at least one side rightward
  • the first reference pixel position of may even be another reference pixel position of the at least one side, which is not specifically limited in the embodiment of the present application.
  • the method may further include:
  • uniform sampling can be performed according to the first sampling interval or the second sampling interval; non-uniform sampling can also be performed according to the first sampling interval and the second sampling interval, and
  • the candidate positions determined after sampling may be symmetrically distributed on both sides of the reference point, or may be asymmetrically distributed on both sides of the reference point; the embodiment of the present application does not specifically limit it.
  • the reference pixel point of at least one side can also be skipped, that is, the unimportant reference pixel point or the abnormal reference pixel point is skipped (also can be regarded as Delete processing) to obtain a reference pixel subset; on this basis, that is, after partial reference pixels of at least one side are skipped, a second reference pixel set is obtained, and the second reference pixel set is filtered, To get a subset of reference pixels. Therefore, the method may also include:
  • the end position of the side of the current block is the start pixel position or the end pixel position of the side of the current block.
  • the preset number of skipped pixels represents a preset number of pixels to be deleted or to be skipped.
  • the starting position of at least one side represents the leftmost edge position of the upper side of the current block or the uppermost edge position of the left side of the current block, and the end position of at least one side represents the rightmost edge of the upper side of the current block. The position or the bottom edge position of the left side of the current block.
  • the value of K can be a preset number of reference pixels, such as 1, 2, or 4; it can also be calculated according to the side length of the current block and the corresponding preset ratio; However, in actual applications, it is still set according to actual conditions, and the embodiments of the present application do not make specific limitations.
  • the preset ratio corresponding to the upper side of the current block can be represented by a first preset ratio
  • the preset ratio corresponding to the left side of the current block can be represented by a second preset ratio
  • the first preset ratio is equal to
  • the value of the second preset ratio may be the same or different, and the embodiment of the present application does not specifically limit it.
  • the model parameters of the prediction model can also be calculated according to the reference pixel subset, so as to facilitate the construction of the prediction model. Therefore, in some embodiments, using the reference pixel subset to calculate the model parameters of the prediction model may include:
  • the pixel at the same position of the reference pixel in the reference pixel subset is the relative position between the reference pixel and the reference block in the image where the reference block is located and the reference pixel in the second reference pixel set and the current block Pixels with the same relative position between.
  • the method may further include:
  • the prediction value of the image component to be predicted of the current block is calculated.
  • the reference block may be an image block indicated by the inter prediction parameter of the current block.
  • a prediction model can be constructed, as shown in the aforementioned formula (5). According to the prediction model and the reference block of the current block, the predicted value of the image component to be predicted of the current block can be further calculated.
  • the image component prediction method when the image component prediction method is applied to the encoder side, some pixels can be selected from the first reference pixel set of the current block to construct a reference pixel subset, and then the prediction is calculated based on the reference pixel subset
  • the model parameters of the model, and the calculated model parameters are written into the code stream; the code stream is transmitted from the encoder side to the decoder side; correspondingly, when the image component prediction method is applied to the decoder side, it can be analyzed Code stream to directly obtain the model parameters of the prediction model; or on the decoder side, you can also select some pixels from the first reference pixel set of the current block to construct a reference pixel subset, and then calculate the model of the prediction model based on the reference pixel subset Parameters to construct a prediction model, and use the prediction model to perform cross-component prediction processing on at least one image component of the current block.
  • This embodiment provides an image component prediction method.
  • the specific implementation of the foregoing embodiment is described in detail. It can be seen from the technical solutions of the foregoing embodiment that because the first reference pixel set is filtered, the unimportant can be removed The number of pixels in the first reference pixel set is reduced, which not only reduces the computational complexity and memory bandwidth, but also improves the accuracy of the prediction model; due to the prediction The model is used to implement the prediction processing of the image component to be predicted through the model parameters, thereby improving the prediction accuracy of the image component to be predicted and improving the prediction efficiency of the video image.
  • FIG. 7 shows a schematic diagram of the composition structure of an encoder 70 provided by an embodiment of the present application.
  • the encoder 70 may include: a first determining unit 701 and a first calculating unit 702, where
  • the first determining unit 701 is configured to determine the first reference pixel set of the image component to be predicted of the current block
  • the first determining unit 701 is further configured to determine a reference pixel subset from the first reference pixel set; wherein, the reference pixel subset includes one or more selected from the first reference pixel set. Candidate pixels;
  • the first calculation unit 702 is configured to use the reference pixel subset to calculate model parameters of a prediction model; wherein the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • the encoder 70 may further include a first obtaining unit 703 configured to obtain, outside the current block, a reference pixel adjacent to at least one side of the current block; wherein, The at least one side of the current block includes at least one of the following: an upper side, a left side, an upper right side, and a lower left side; and the first reference pixel set is obtained according to the acquired reference pixels.
  • a first obtaining unit 703 configured to obtain, outside the current block, a reference pixel adjacent to at least one side of the current block; wherein, The at least one side of the current block includes at least one of the following: an upper side, a left side, an upper right side, and a lower left side; and the first reference pixel set is obtained according to the acquired reference pixels.
  • the first obtaining unit 703 is further configured to obtain reference pixels adjacent to at least one side of the reconstructed block within the reconstructed block; wherein, the reconstructed block is the same as the current block. Adjacent to an image block that has been reconstructed by encoding, at least one side of the reconstructed block includes: a bottom side, a right side, or a bottom side and a right side; and according to the obtained reference pixels, the first Reference pixel collection.
  • the encoder 70 may further include a first selecting unit 704, where:
  • the first determining unit 701 is further configured to determine a candidate position of a candidate pixel based on at least one edge of the current block or the reconstructed block;
  • the first selection unit 704 is configured to select reference pixels corresponding to the candidate position from the first reference pixel set, and compose the selected parameter pixels into the reference pixel subset.
  • the first determining unit 701 is further configured to determine the candidate position based on the pixel position corresponding to the reference pixel adjacent to the at least one side.
  • the first determining unit 701 is further configured to determine the candidate position based on the image component intensity value corresponding to the reference pixel adjacent to the at least one side.
  • the first determining unit 701 is further configured to determine the candidate position based on the pixel position and the image component intensity value corresponding to the reference pixel adjacent to the at least one side.
  • the first determining unit 701 is further configured to determine a preset number of candidate pixels; wherein, the preset number of candidate pixels represents the number of pixels sampled from the reference pixels adjacent to the at least one side And determining the candidate position according to the preset number of candidate pixels and the length of the at least one side; wherein the length of the at least one side is equal to the number of pixels included in the at least one side.
  • the first calculation unit 702 is further configured to calculate the first sampling interval according to the preset number of candidate pixels and the length of the at least one side;
  • the first determining unit 701 is further configured to determine a reference point from the at least one edge, and determine the candidate position according to the first sampling interval.
  • the encoder 70 may further include a first adjustment unit 705, configured as the first determining unit 701, and further configured to adjust the first sampling interval to obtain a second sampling interval;
  • the first determining unit 701 is further configured to determine the candidate position according to the second sampling interval based on the reference point.
  • the first determining unit 701 is further configured to determine, based on the reference point, a candidate position corresponding to one side of the reference point according to the first sampling interval, and determine the corresponding candidate position according to the second sampling interval. The candidate position corresponding to the other side of the reference point.
  • the first determining unit 701 is further configured to determine the preset number of skipped pixels K corresponding to the at least one side, where K is a positive integer greater than or equal to 1; and from the at least one Starting from the start position and/or end position of the edge, determine the positions corresponding to the K pixels to be skipped; and based on the positions corresponding to the K pixels to be skipped, from the start position of the at least one edge and /Or the end position continuously skips K pixels to be skipped to obtain at least one new side; and based on the at least one new side and the preset number of candidate pixels, the candidate position is determined.
  • the first selection unit 704 is further configured to obtain, based on the reference pixel subset, the neighboring pixel reconstruction value of the image component to be predicted corresponding to the current block and the image component to be predicted corresponding to the reference block Reconstruction values of adjacent pixels; wherein the current block is located in the Nth frame of video image, and the reference block is located in the N-1th frame of video image;
  • the first calculation unit 702 is further configured to calculate the reconstruction value of the neighboring pixel of the image component to be predicted corresponding to the current block and the reconstruction value of the neighboring pixel of the image component to be predicted corresponding to the reference block. Model parameters.
  • the encoder 70 may further include a first construction unit 706 and a first prediction unit 707, where
  • the first construction unit 706 is configured to construct the prediction model according to the model parameters
  • the first prediction unit 707 is configured to perform prediction processing on the image component to be predicted of the current block by using the prediction model to obtain a predicted value corresponding to the image component to be predicted.
  • the first determining unit 701 is further configured to use one or more first adjacent pixels of the current block as the first reference pixel set; wherein, the first adjacent pixels are The pixels are located adjacent to the vertical side of the current block, the horizontal side of the current block, or the vertical side and the horizontal side of the current block.
  • the first determining unit 701 is further configured to determine that the vertical edge of the current block is the left adjacent column outside the current block if the first neighboring pixel is located outside the current block , The horizontal edge of the current block is the upper adjacent line outside the current block.
  • the first determining unit 701 is further configured to determine that the vertical edge of the current block is the right edge column in the current block if the first neighboring pixel is located in the current block ,
  • the horizontal side of the current block is the lower side row in the current block.
  • the first determining unit 701 is further configured to determine the candidate position of the candidate pixel on the edge of the current block, wherein the edge of the current block is the vertical of the current block. Edge or horizontal edge; and selecting a pixel located at the candidate position from the first reference pixel set, and composing the selected pixel into the reference pixel subset.
  • the first determining unit 701 is further configured to determine the candidate position of the candidate pixel according to the position of the pixel in the first reference pixel set.
  • the first determining unit 701 is further configured to determine the candidate position of the candidate pixel according to the image component intensity of the pixel in the first reference pixel set.
  • the first determining unit 701 is further configured to determine the candidate position of the candidate pixel according to the position of the pixel in the first reference pixel set and the image component intensity.
  • the first determining unit 701 is further configured to determine a preset number of candidate pixels, where the preset number of candidate pixels indicates the number of pixels selected from the side of the current block;
  • the first calculation unit 702 is further configured to calculate the first sampling interval according to the length of the side of the current block and the preset number of candidate pixels.
  • the first adjustment unit 705 is configured to adjust the first sampling interval to obtain the second sampling interval.
  • the first determining unit 701 is further configured to determine a reference point on the edge of the current block, and from the reference point, determine the edge of the current block at the first sampling interval. Candidate positions.
  • the first determining unit 701 is further configured to determine a reference point on the edge of the current block, and determine candidate positions on both sides of the reference point at the first sampling interval.
  • the first determining unit 701 is further configured to determine a reference point on the edge of the current block, and from the reference point, determine the edge of the current block at the second sampling interval. Candidate positions.
  • the first determining unit 701 is further configured to determine a reference point on the edge of the current block, and determine candidate positions on both sides of the reference point at the second sampling interval.
  • the first determining unit 701 is further configured to determine a reference point on the side of the current block, determine a candidate position corresponding to one side of the reference point at the first sampling interval, and use the The second sampling interval determines the candidate position corresponding to the other side of the reference point.
  • the first determining unit 701 is further configured to determine the preset number of skipped pixels K of the side of the current block, where K is a non-negative integer; and from the end position of the side of the current block From the beginning, the Kth pixel position is set as the reference point; wherein the end position of the side of the current block is the start pixel position or the end pixel position of the side of the current block.
  • the first calculation unit 702 is further configured to use a reference pixel in the reference pixel subset and a pixel in the reference block of the current block that is located at the same position of the reference pixel in the reference pixel subset, Calculate the model parameters of the prediction model; wherein the pixels in the same position of the reference pixels in the reference pixel subset are located in the image where the reference block is located, and the relative position between the reference block and the second reference pixel set is A pixel with the same relative position between the reference pixel and the current block.
  • the first calculation unit 702 is further configured to calculate the predicted value of the image component to be predicted of the current block according to the prediction model and the reference block of the current block.
  • the reference block is the image block indicated by the inter prediction parameter of the current block.
  • 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 also 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.
  • an embodiment of the present application provides a computer storage medium that stores an image component prediction program that implements the steps of the method described in the foregoing embodiment when the image component prediction program is executed by at least one processor.
  • FIG. 8 shows an example of the specific hardware structure of the encoder 70 provided by the embodiment of the present application, which may include: a first communication interface 801, a first memory 802, and a first communication interface 801; A processor 803; various components are coupled together through a first bus system 804.
  • the first bus system 804 is used to implement connection and communication between these components.
  • the first bus system 804 also includes a power bus, a control bus, and a status signal bus.
  • various buses are marked as the first bus system 804 in FIG. 8. among them,
  • the first communication interface 801 is used for receiving and sending signals in the process of sending and receiving information with other external network elements;
  • the first memory 802 is configured to store a computer program that can run on the first processor 803;
  • the first processor 803 is configured to execute: when the computer program is running:
  • the reference pixel subset is used to calculate the model parameters of the prediction model; wherein, the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • the first memory 802 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 first processor 803 may be an integrated circuit chip with signal processing capability. In the implementation process, the steps of the foregoing method can be completed by an integrated logic circuit of hardware in the first processor 803 or instructions in the form of software.
  • the above-mentioned first processor 803 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 gates 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 first memory 802, and the first processor 803 reads the information in the first memory 802, and completes the steps of the foregoing method in combination with its hardware.
  • the embodiments described in this application 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 programmable Logic Device
  • Field-Programmable Gate Array Field-Programmable Gate Array
  • FPGA Field-Programmable Gate Array
  • the technology described in this application can be implemented through modules (such as procedures, functions, etc.) that perform the functions described in this application.
  • the first processor 803 is further configured to execute the method described in any one of the foregoing embodiments when the computer program is running.
  • This embodiment provides an encoder, which may include a first determining unit and a first calculating unit, wherein the first determining unit is configured to determine a first reference pixel set of the image component to be predicted of the current block; To determine a reference pixel subset from the first reference pixel set; wherein the reference pixel subset includes one or more candidate pixels selected from the first reference pixel set; the first calculation unit is configured to use the reference pixel subset Set, calculate the model parameters of the prediction model; among them, the prediction model is used to perform cross-component prediction processing on the image components to be predicted in the current block; in this way, because the first reference pixel set is filtered, unimportant reference pixels can be removed Or there are abnormal reference pixels, thereby reducing the number of pixels in the first reference pixel set, which can not only reduce computational complexity and memory bandwidth, but also improve the accuracy of the prediction model; because the prediction model is used for The prediction processing of the image component to be predicted is realized through the model parameters, thereby improving the prediction accuracy of the image component to be predicted and improving the prediction
  • FIG. 9 shows a schematic diagram of the composition structure of a decoder 90 provided by an embodiment of the present application.
  • the decoder 90 may include: a second determining unit 901 and a second calculating unit 902, where
  • the second determining unit 901 is configured to determine the first reference pixel set of the image component to be predicted of the current block
  • the second determining unit 901 is further configured to determine a reference pixel subset from the first reference pixel set; wherein, the reference pixel subset includes one or more selected from the first reference pixel set. Candidate pixels;
  • the second calculation unit 902 is configured to use the reference pixel subset to calculate model parameters of a prediction model; wherein, the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • the decoder 90 may further include a second obtaining unit 903, configured to obtain, outside the current block, a reference pixel adjacent to at least one side of the current block; wherein, The at least one side of the current block includes at least one of the following: an upper side, a left side, an upper right side, and a lower left side; and the first reference pixel set is obtained according to the acquired reference pixels.
  • the second acquiring unit 903 is further configured to acquire reference pixels adjacent to at least one side of the reconstruction block within the reconstruction block; wherein, the reconstruction block is the same as the current block. Adjacent to an image block that has been reconstructed by encoding, at least one side of the reconstructed block includes: a bottom side, a right side, or a bottom side and a right side; and according to the obtained reference pixels, the first Reference pixel collection.
  • the decoder 90 may further include a second selecting unit 904, where:
  • the second determining unit 901 is further configured to determine a candidate position of a candidate pixel based on at least one edge of the current block or the reconstruction block;
  • the second selecting unit 904 is configured to select reference pixels corresponding to the candidate positions from the first reference pixel set, and compose the selected parameter pixels into the reference pixel subset.
  • the second determining unit 901 is further configured to determine the candidate position based on the pixel position corresponding to the reference pixel adjacent to the at least one side.
  • the second determining unit 901 is further configured to determine the candidate position based on the image component intensity value corresponding to the reference pixel adjacent to the at least one side.
  • the second determining unit 901 is further configured to determine the candidate position based on the pixel position and the image component intensity value corresponding to the reference pixel adjacent to the at least one side.
  • the second determining unit 901 is further configured to determine a preset number of candidate pixels; wherein, the preset number of candidate pixels represents the number of pixels sampled from the reference pixels adjacent to the at least one side And determining the candidate position according to the preset number of candidate pixels and the length of the at least one side; wherein the length of the at least one side is equal to the number of pixels included in the at least one side.
  • the second calculation unit 902 is further configured to calculate the first sampling interval according to the preset number of candidate pixels and the length of the at least one side;
  • the second determining unit 901 is further configured to determine a reference point from the at least one edge, and determine the candidate position according to the first sampling interval.
  • the decoder 90 may further include a second adjustment unit 905, configured as the second determining unit 901, and further configured to adjust the first sampling interval to obtain a second sampling interval;
  • the second determining unit 901 is further configured to determine the candidate position according to the second sampling interval based on the reference point.
  • the second determining unit 901 is further configured to determine, based on the reference point, a candidate position corresponding to one side of the reference point according to the first sampling interval, and determine the candidate position corresponding to one side of the reference point according to the second sampling interval. The candidate position corresponding to the other side of the reference point.
  • the second determining unit 901 is further configured to determine the preset number of skipped pixels K corresponding to the at least one side, where K is a positive integer greater than or equal to 1; and from the at least one Starting from the start position and/or end position of the edge, determine the positions corresponding to the K pixels to be skipped; and based on the positions corresponding to the K pixels to be skipped, from the start position of the at least one edge and /Or the end position continuously skips K pixels to be skipped to obtain at least one new side; and based on the at least one new side and the preset number of candidate pixels, the candidate position is determined.
  • the second selecting unit 904 is further configured to obtain, based on the reference pixel subset, the neighboring pixel reconstruction value of the image component to be predicted corresponding to the current block and the image component to be predicted corresponding to the reference block Reconstruction values of adjacent pixels; wherein the current block is located in the Nth frame of video image, and the reference block is located in the N-1th frame of video image;
  • the second calculation unit 902 is further configured to calculate the reconstruction value of the neighboring pixel of the image component to be predicted corresponding to the current block and the reconstruction value of the neighboring pixel of the image component to be predicted corresponding to the reference block. Model parameters.
  • the decoder 90 may further include a second construction unit 906 and a second prediction unit 907, where:
  • the second construction unit 906 is configured to construct the prediction model according to the model parameters
  • the second prediction unit 907 is configured to perform prediction processing on the image component to be predicted of the current block by using the prediction model to obtain a predicted value corresponding to the image component to be predicted.
  • the second determining unit 901 is further configured to use one or more first neighboring pixels of the current block as the first reference pixel set; wherein, the first neighboring pixels are The pixels are located adjacent to the vertical side of the current block, the horizontal side of the current block, or the vertical side and the horizontal side of the current block.
  • the second determining unit 901 is further configured to determine that the vertical edge of the current block is the left adjacent column outside the current block if the first neighboring pixel is located outside the current block , The horizontal edge of the current block is the upper adjacent line outside the current block.
  • the second determining unit 901 is further configured to determine that the vertical edge of the current block is the right edge column in the current block if the first neighboring pixel is located in the current block ,
  • the horizontal side of the current block is the lower side row in the current block.
  • the second determining unit 901 is further configured to determine the candidate position of the candidate pixel on the edge of the current block, wherein the edge of the current block is the vertical direction of the current block. Edge or horizontal edge; and selecting a pixel located at the candidate position from the first reference pixel set, and composing the selected pixel into the reference pixel subset.
  • the second determining unit 901 is further configured to determine the candidate position of the candidate pixel according to the position of the pixel in the first reference pixel set.
  • the second determining unit 901 is further configured to determine the candidate position of the candidate pixel according to the image component intensity of the pixel in the first reference pixel set.
  • the second determining unit 901 is further configured to determine the candidate position of the candidate pixel according to the position of the pixel in the first reference pixel set and the image component intensity.
  • the second determining unit 901 is further configured to determine a preset number of candidate pixels, where the preset number of candidate pixels indicates the number of pixels selected from the side of the current block;
  • the second calculation unit 902 is further configured to calculate the first sampling interval according to the length of the side of the current block and the preset number of candidate pixels.
  • the second adjustment unit 905 is configured to adjust the first sampling interval to obtain a second sampling interval.
  • the second determining unit 901 is further configured to determine a reference point on the edge of the current block, and from the reference point, determine the edge of the current block at the first sampling interval. Candidate positions.
  • the second determining unit 901 is further configured to determine a reference point on the edge of the current block, and determine candidate positions on both sides of the reference point at the first sampling interval.
  • the second determining unit 901 is further configured to determine a reference point on the edge of the current block, and from the reference point, determine the edge of the current block at the second sampling interval. Candidate positions.
  • the second determining unit 901 is further configured to determine a reference point on the edge of the current block, and determine candidate positions on both sides of the reference point at the second sampling interval.
  • the second determining unit 901 is further configured to determine a reference point on the side of the current block, determine a candidate position corresponding to one side of the reference point at the first sampling interval, and use the The second sampling interval determines the candidate position corresponding to the other side of the reference point.
  • the second determining unit 901 is further configured to determine the preset number of skipped pixels K of the side of the current block, where K is a non-negative integer; and from the end position of the side of the current block From the beginning, the Kth pixel position is set as the reference point; wherein the end position of the side of the current block is the start pixel position or the end pixel position of the side of the current block.
  • the second calculation unit 902 is further configured to use the reference pixel in the reference pixel subset and the pixel in the reference block of the current block that is located at the same position of the reference pixel in the reference pixel subset, Calculate the model parameters of the prediction model; wherein the pixels in the same position of the reference pixels in the reference pixel subset are located in the image where the reference block is located, and the relative position between the reference block and the second reference pixel set is A pixel with the same relative position between the reference pixel and the current block.
  • the second calculation unit 902 is further configured to calculate the predicted value of the image component to be predicted of the current block according to the prediction model and the reference block of the current block.
  • the reference block is the image block indicated by the inter prediction parameter of the current block.
  • 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.
  • this embodiment provides a computer storage medium that stores an image component prediction program, and when the image component prediction program is executed by a second processor, the image component prediction program implements any one of the foregoing embodiments. Methods.
  • FIG. 10 shows the specific hardware structure of the decoder 90 provided by an embodiment of the present application, which may include: a second communication interface 1001, a second memory 1002, and a second Processor 1003; each component is coupled together through a second bus system 1004.
  • the second bus system 1004 is used to implement connection and communication between these components.
  • the second bus system 1004 also includes a power bus, a control bus, and a status signal bus.
  • various buses are marked as the second bus system 1004 in FIG. 10. among them,
  • the second communication interface 1001 is used for receiving and sending signals in the process of sending and receiving information with other external network elements;
  • the second memory 1002 is configured to store a computer program that can run on the second processor 1003;
  • the second processor 1003 is configured to execute: when the computer program is running:
  • the reference pixel subset is used to calculate the model parameters of the prediction model; wherein, the prediction model is used to perform cross-component prediction processing on the image component to be predicted of the current block.
  • the second processor 1003 is further configured to execute the method described in any one of the foregoing embodiments when running the computer program.
  • the hardware function of the second memory 1002 is similar to that of the first memory 802, and the hardware function of the second processor 1003 is similar to that of the first processor 803; it will not be detailed here.
  • This embodiment provides a decoder, which may include a second determining unit and a second calculating unit, wherein the second determining unit is configured to determine a first reference pixel set of the image component to be predicted of the current block; To determine a reference pixel subset from the first reference pixel set; wherein the reference pixel subset includes one or more candidate pixels selected from the first reference pixel set; the second calculation unit is configured to use the reference pixel subset Set, calculate the model parameters of the prediction model; among them, the prediction model is used to perform cross-component prediction processing on the image components to be predicted in the current block; in this way, because the first reference pixel set is filtered, unimportant reference pixels can be removed Or there are abnormal reference pixels, thereby reducing the number of pixels in the first reference pixel set, which can not only reduce computational complexity and memory bandwidth, but also improve the accuracy of the prediction model; because the prediction model is used for The prediction processing of the image component to be predicted is realized through the model parameters, thereby improving the prediction accuracy of the image component to be predicted and improving
  • the first reference pixel set of the image component to be predicted of the current block is determined; then the reference pixel subset is determined from the first reference pixel set; wherein the reference pixel subset includes the reference pixel set from the first reference pixel set.

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Abstract

一种图像分量预测方法、编码器、解码器以及存储介质，该方法包括：确定当前块的待预测图像分量的第一参考像素集合（S101）；从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素（S102）；利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理（S103）。

Description

图像分量预测方法、编码器、解码器以及存储介质 技术领域
本申请实施例涉及图像处理技术领域，尤其涉及一种图像分量预测方法、编码器、解码器以及存储介质。
背景技术
由于视频图像的色彩信息经常受到光源、采集设备的色彩偏差等因素的影响从而导致整体上色彩向某一方向移动，也是我们经常所见的偏冷、照片偏黄等现象。为了抵消这种整个视频图像中存在的色彩偏差，目前提出了光照补偿(Illumination Compensation，IC)技术或者局部光照补偿(Local Illumination Compensation，LIC)技术，以对视频图像进行色彩修正。
无论是IC技术或者LIC技术，均需要使用到预测模型构造，然后由构造的预测模型推导出视频图像在视频编解码中的预测值。然而在预测模型的构造过程中，目前用于模型参数推导的样本点数量较大，计算复杂度和内存带宽偏高；同时在这些样本点中还可能存在异常样本点，导致预测模型构造不准确。
发明内容
本申请实施例提供一种图像分量预测方法、编码器、解码器以及存储介质，通过减少参考像素集合中的像素个数，不仅降低了计算复杂度和内存带宽，而且提高了预测模型的精确度，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
本申请实施例的技术方案可以如下实现：
第一方面，本申请实施例提供了一种图像分量预测方法，该方法包括：
确定当前块的待预测图像分量的第一参考像素集合；
从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从第一参考像素集合中选择的一个或多个候选像素；
利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
第二方面，本申请实施例提供了一种编码器，该编码器包括第一确定单元和第一计算单元，其中，
第一确定单元，配置为确定当前块的待预测图像分量的第一参考像素集合；
第一确定单元，还配置为从所述第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从第一参考像素集合中选择的一个或多个候选像素；
第一计算单元，配置为利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
第三方面，本申请实施例提供了一种编码器，该编码器包括第一存储器和第一处理器，其中，
第一存储器，用于存储能够在第一处理器上运行的计算机程序；
第一处理器，用于在运行所述计算机程序时，执行如第一方面所述的方法。
第四方面，本申请实施例提供了一种解码器，该解码器包括第二确定单元和第二计算单元，其中，
第二确定单元，配置为确定当前块的待预测图像分量的第一参考像素集合；
第二确定单元，还配置为从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从第一参考像素集合中选择的一个或多个候选像素；
第二计算单元，配置为利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
第五方面，本申请实施例提供了一种解码器，该解码器包括第二存储器和第二处理器，其中，
第二存储器，用于存储能够在第二处理器上运行的计算机程序；
第二处理器，用于在运行所述计算机程序时，执行如第一方面所述的方法。
第六方面，本申请实施例提供了一种计算机存储介质，该计算机存储介质存储有图像分量预测程序，图像分量预测程序被第一处理器或第二处理器执行时实现如第一方面所述的方法。
本申请实施例提供了一种图像分量预测方法、编码器、解码器以及存储介质，确定当前块的待预测 图像分量的第一参考像素集合；从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度；由于所述预测模型是用于通过所述模型参数实现对所述待预测图像分量的预测处理，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
附图说明
图1为本申请实施例提供的一种图像分量预测方法的流程示意图；
图2A为本申请实施例提供的一种参考像素点位置的结构示意图；
图2B为本申请实施例提供的另一种参考像素点位置的结构示意图；
图3为本申请实施例提供的一种当前块上侧边相邻参考像素子集选取的结构示意图；
图4为本申请实施例提供的另一种当前块上侧边相邻参考像素子集选取的结构示意图；
图5为本申请实施例提供的一种预测模型的对比结构示意图；
图6为本申请实施例提供的另一种图像分量预测方法的流程示意图；
图7为本申请实施例提供的一种编码器的组成结构示意图；
图8为本申请实施例提供的一种编码器的具体硬件结构示意图；
图9为本申请实施例提供的一种解码器的组成结构示意图；
图10为本申请实施例提供的一种解码器的具体硬件结构示意图。
具体实施方式
为了能够更加详尽地了解本申请实施例的特点与技术内容，下面结合附图对本申请实施例的实现进行详细阐述，所附附图仅供参考说明之用，并非用来限定本申请实施例。
在视频图像中，一般采用第一图像分量、第二图像分量和第三图像分量来表征编码块(Coding Block，CB)；其中，这三个图像分量分别为一个亮度分量、一个蓝色色度分量和一个红色色度分量，具体地，亮度分量通常使用符号Y表示，蓝色色度分量通常使用符号Cb或者U表示，红色色度分量通常使用符号Cr或者V表示；这样，视频图像可以用YCbCr格式表示，也可以用YUV格式表示。
在本申请实施例中，第一图像分量可以为亮度分量，第二图像分量可以为蓝色色度分量，第三图像分量可以为红色色度分量，但是本申请实施例不作具体限定。
在当前的视频图像或者视频编解码过程中，不仅跨分量预测技术需要使用到预测模型的构建，而且图像分量内的预测技术同样需要使用到预测模型的构建。其中，对于跨分量预测技术，主要包括跨分量线性模型预测(Cross-component Linear Model Prediction，CCLM)模式和多方向线性模型预测(Multi-Directional Linear Model Prediction，MDLM)模式，这里的CCLM模式和MDLM模式所构建的预测模型，可以实现第一图像分量到第二图像分量、第二图像分量到第一图像分量、第一图像分量到第三图像分量、第三图像分量到第一图像分量、第二图像分量到第三图像分量、或者第三图像分量到第二图像分量等图像分量间的预测。而对于图像分量内的预测技术，主要包括色度分量补偿技术和亮度分量补偿技术，比如IC技术和LIC技术，利用图像分量内的预测技术所构建的预测模型，可以实现第一图像分量对第一图像分量的预测、第二图像分量对第二图像分量的预测、或者第三图像分量对第三图像分量的预测等图像分量内的预测技术。在本申请实施例中，下面将主要以图像分量内的预测技术所构建的预测模型为例进行描述。
为了保证预测模型中所使用模型参数的准确性，则用于推导模型参数所构造的参考像素集合需要更为准确。基于此，本申请实施例提供了一种图像分量预测方法，通过确定当前块的待预测图像分量的第一参考像素集合；从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度，进而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
需要说明的是，本申请实施例的图像分量预测方法，既可以应用于视频编码系统，又可以应用于视 频解码系统，甚至还可以同时应用于视频编码系统和视频解码系统，本申请实施例不作具体限定。还需要说明的是，当该方法应用于视频编码系统时，“当前块”具体是指帧内预测中的当前编码块；当该方法应用于视频解码系统时，“当前块”具体是指帧内预测中的当前解码块。
下面将结合附图对本申请各实施例进行详细描述。
参见图1，其示出了本申请实施例提供的一种图像分量预测方法的流程示意图，该方法可以包括：
S101：确定当前块的待预测图像分量的第一参考像素集合；
S102：从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
S103：利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
需要说明的是，视频图像可以划分为多个图像块，每个当前待编码的图像块可以称为当前块。其中，每个当前块可以包括第一图像分量、第二图像分量和第三图像分量；而当前块为视频图像中当前待进行第一图像分量、第二图像分量或者第三图像分量预测的当前块。其中，当需要通过预测模型对第一图像分量进行预测时，待预测图像分量为第一图像分量；当需要通过预测模型对第二图像分量进行预测时，待预测图像分量为第二图像分量；当需要通过预测模型对第三图像分量进行预测时，待预测图像分量为第三图像分量。
还需要说明的是，第一参考像素集合为当前相关技术方案中构建预测模型所对应的参考像素集合。在该第一参考像素集合中，可能会存在部分不重要的参考像素点(比如这些参考像素点的相关性较差)或者部分异常的参考像素点，为了保证预测模型的准确性，需要将这些参考像素点剔除掉，从而得到了参考像素子集；根据参考像素子集，可以保证预测模型的准确性，使得待预测图像分量的预测效率高。
在本申请实施例中，首先定当前块的待预测图像分量的第一参考像素集合；然后从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；再利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度，进而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
进一步地，针对第一参考像素集合的确定，可以是根据当前块周边相邻的参考像素得到的，也可以是重建块内部相邻的参考像素得到的，本申请实施例不作具体限定，下面将分别对其进行描述。
可选地，在一些实施例中，对于S101来说，所述确定当前块的待预测图像分量的第一参考像素集合，可以包括：
在所述当前块之外，获取与所述当前块的至少一个边相邻的参考像素；其中，所述当前块的至少一个边包括下述至少之一：上侧边、左侧边、右上侧边和左下侧边；
根据获取的参考像素，得到所述第一参考像素集合。
示例性地，参见图2A，其示出了本申请实施例提供的一种参考像素点位置的结构示意图。在图2A中，参考像素点位于当前块的周围，也即与当前块至少一个边相邻的参考像素点，而当前块至少一个边可以是指当前块的左侧边，也可以是指当前块的上侧边，甚至也可以是指当前块的左侧边和上侧边；本申请实施例不作具体限定。
可以理解，如果当前块的至少一个边为左侧边和/或上侧边，那么对于S101来说，所述确定当前块的待预测图像分量的第一参考像素集合，可以包括：
获取与所述当前块的至少一个边相邻的参考像素点；其中，所述至少一个边包括所述当前块的左侧边和/或所述当前块的上侧边；
根据获取的参考像素，得到所述第一参考像素集合。
需要说明的是，当前块的至少一个边可以包括当前块的左侧边和/或当前块的上侧边；即当前块的至少一个边可以是指当前块的上侧边，也可以是指当前块的左侧边，甚至还可以是指当前块的上侧边和左侧边，本申请实施例不作具体限定。
这样，当左侧相邻区域和上侧相邻区域全部为有效区域时，这时候第一参考像素集合可以是由与当前块的左侧边相邻的参考像素点和与当前块的上侧边相邻的参考像素点组成的，当左侧相邻区域为有效区域、而上侧相邻区域为无效区域时，这时候第一参考像素集合可以是由与当前块的左侧边相邻的参考像素点组成的；当左侧相邻区域为无效区域、而上侧相邻区域为有效区域时，这时候第一参考像素集合可以是由与当前块的上侧边相邻的参考像素点组成的。
可以理解，如果当前块的至少一个边为左侧边和左下侧边组成的相邻列、和/或上侧边和右上侧边 组成的相邻行，那么对于S101来说，所述确定当前块的待预测图像分量的第一参考像素集合，可以包括：
获取与所述当前块相邻的参考行或者参考列中的参考像素点；其中，所述参考行是由所述当前块的上侧边以及右上侧边所相邻的行组成的，所述参考列是由所述当前块的左侧边以及左下侧边所相邻是列组成的；
根据获取的参考像素，得到所述第一参考像素集合。
需要说明的是，与当前块相邻的参考行可以是由所述当前块的上侧边以及右上侧边所相邻的行组成的，与当前块相邻的参考列可以是由所述当前块的左侧边以及左下侧边所相邻的列组成的；与当前块相邻的参考行或参考列可以是指与当前块上侧边相邻的参考行，也可以是指与当前块左侧边相邻的参考列，甚至还可以是指与当前块其他边相邻的参考行或参考列，本申请实施例不作具体限定。为了方便描述，在本申请实施例中，当前块相邻的参考行将以上侧边相邻的参考行为例进行描述，当前块相邻的参考列将以左侧边相邻的参考列为例进行描述。
其中，与当前块相邻的参考行中的参考像素点可以包括与上侧边以及右上侧边相邻的参考像素点(也称之为上侧边以及右上侧边所对应的相邻参考像素点)，其中，上侧边表示当前块的上侧边，右上侧边表示当前块上侧边向右水平扩展出的与当前块高度相同的边长；与当前块相邻的参考列中的参考像素点还可以包括与左侧边以及左下侧边相邻的参考像素点(也称之为左侧边以及左下侧边所对应的相邻参考像素点)，其中，左侧边表示当前块的左侧边，左下侧边表示当前块左侧边向下垂直扩展出的与当前解码块宽度相同的边长；但是本申请实施例也不作具体限定。
这样，当左侧相邻区域和左下侧相邻区域为有效区域时，这时候第一参考像素集合可以是由与当前块相邻的参考列中的参考像素点组成的；当上侧相邻区域和右上侧相邻区域为有效区域时，这时候第一参考像素集合可以是由与当前块相邻的参考行中的参考像素点组成的。
可选地，在一些实施例中，对于S101来说，所述确定当前块的待预测图像分量的第一参考像素集合，可以包括：
在重建块之内，获取所述重建块的至少一个边相邻的参考像素；其中，所述重建块为与所述当前块相邻且已完成编码重构建的图像块，所述重建块的至少一个边包括：下侧边、右侧边、或者下侧边和右侧边；
根据获取的参考像素，得到所述第一参考像素集合。
示例性地，参见图2B，其示出了本申请实施例提供的一种参考像素点位置的结构示意图。在图2B中，参考像素点位于重建块的内部，也即与重建块至少一个边相邻的参考像素点，而重建块至少一个边可以是指重建块的右侧边，也可以是指重建块的下侧边，甚至也可以是指重建块的右侧边和下侧边，本申请实施例不作具体限定。
需要说明的是，从构建预测模型的角度，参考像素点可以称为“构建预测模型所使用的像素点”，当前块已经处于编码且重建完毕阶段，这时候构建一个预测模型，该预测模型可以方便后续图像中的其他编码块使用。另外，针对重建块来说，一方面可以利用重建块内相邻的参考像素来得到第一参考像素集合，便于后续构建当前块的预测模型；另一方面还可以直接借用重建块对应的预测模型，将其作为当前块的预测模型；也就是说，对于正在编码的当前块，相邻区域的重建块的相关信息使用，是可以通过直接利用其对应的预测模型的，而不需要通过重建块相邻的参考像素再来构建预测模型。
进一步地，在得到第一参考像素集合之后，该第一参考像素集合中可能会存在部分不重要的参考像素点(比如这些参考像素点的相关性较差)或者部分异常的参考像素点，为了保证模型参数推导的准确性，需要将这些参考像素点剔除掉，从而得到了参考像素子集；这样，根据参考像素子集，可以保证预测模型的准确性，使得待处理图像分量的预测效率高。
在一些实施例中，对于S102来说，所述根据所述第一参考像素集合，确定参考像素子集，可以包括：
基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置；
从所述第一参考像素集合中选取与所述候选位置对应的参考像素，将选取得到的参数像素组成所述参考像素子集。
进一步地，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，可以包括：
基于所述至少一个边相邻的参考像素对应的像素位置，确定所述候选位置。
进一步地，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，可以包括：
基于所述至少一个边相邻的参考像素对应的图像分量强度值，确定所述候选位置。
进一步地，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，可以包括：
基于所述至少一个边相邻的参考像素对应的像素位置和图像分量强度值，确定所述候选位置。
需要说明的是，图像分量强度可以用图像分量值来表示，比如亮度值、色度值等；这里，图像分量值越大，表明了图像分量强度越高。本申请实施例所选取的参考像素，可以是通过候选像素的候选位置来进行选取的；其中，候选位置可以是根据像素位置确定，也可以是根据图像分量强度值(比如亮度值、色度值等)确定，本申请实施例不作具体限定。
还需要说明的是，参考像素子集是通过对第一参考像素集合进行筛选处理，然后选取部分参考像素点所组成的；而模型参数是根据参考像素子集进行计算得到的；这样，由于参考像素子集中样本数量减少，也就减少了计算模型参数所需的样本数量，从而可以达到减少降低计算复杂度和内存带宽(或称为存储器带宽)的目的。
可以理解，本申请实施例所选取的部分参考像素点，可以是通过参考像素对应的像素位置来选取的，也可以是根据参考像素对应的图像分量强度值(比如亮度值、色度值等)来选取的，本申请实施例不作具体限定。其中，无论是通过参考像素对应的像素位置，还是通过参考像素对应的图像分量强度值对第一参考像素集合进行筛选以选取出合适的参考像素点，进而组成参考像素子集；这样，根据参考像素子集推导得到的模型参数更准确，使得根据该模型参数所构建的预测模型也可以更精确。
在一些实施例中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，可以包括：
确定预设候选像素数；其中，所述预设候选像素数表示从所述至少一个边相邻的参考像素中所采样的像素数量；
根据所述预设候选像素数和所述至少一个边的长度，确定所述候选位置；其中，所述至少一个边的长度等于所述至少一个边所包含的像素数量。
需要说明的是，针对重建块的相关信息使用，是可以通过直接利用其对应的预测模型的，而不需要通过重建块相邻的参考像素再来构建预测模型；因此，本申请实施例将主要以当前块的至少一个边为例进行描述如何确定候选像素的候选位置。
还需要说明的是，预设候选像素数表示预先设定的待采样的像素点个数，即参考像素子集中所包含的像素个数。以像素位置为例，可以在确定出预设候选像素数之后，根据至少一个边的边长和预设候选像素数来计算出候选像素的候选位置；然后根据候选位置，从第一参考像素集合中选取合适的参考像素点来组成参考像素子集。这样，根据参考像素子集所计算的模型参数更为准确，从而构建的预测模型也可以更精确，进而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
进一步地，对于候选位置的确定，可以先计算第一采样间隔，然后根据第一采样间隔对该至少一个边进行采样处理，以确定出该至少一个边对应的候选像素的候选位置。因此，在一些实施例中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，可以包括：
根据所述预设候选像素数和所述至少一个边的长度，计算第一采样间隔；
从所述至少一个边中确定一基准点，按照所述第一采样间隔确定所述候选位置。
需要说明的是，基准点可以是所述至少一个边的中点，也可以是所述至少一个边的中点偏左的第一个参考像素点位置，还可以是所述至少一个边的中点偏右的第一参考像素点位置，甚至还可以是所述至少一个边的其他参考像素点位置，本申请实施例不作具体限定。
具体地，可以根据所述至少一个边的长度，确定所述至少一个边的中点，然后将所述至少一个边的中点作为所述基准点。其中，基准点可以是所述至少一个边的中点，也可以是所述至少一个边的中点偏左的第一个参考像素点位置，还可以是所述至少一个边的中点偏右的第一参考像素点位置，甚至还可以是所述至少一个边的其他参考像素点位置，本申请实施例不作具体限定。
需要说明的是，考虑到与当前块的至少一个边相邻的参考像素点的重要性与其对应的位置有关，为了使得参考像素子集中的参考像素点能够代表整个相邻边的特性，需要尽可能选取处于该边中心位置的参考像素点，以将重要性比较低的点(比如该边的两侧边缘的参考像素点)进行剔除。在本申请实施例中，如果以当前块的上侧边为例进行说明，那么可以将中间位置偏右或者偏左的第一个参考像素点位置作为该边的基准点；如果以当前块的左侧边为例进行说明，那么可以将中间位置偏下或者偏上的第一个参考像素点位置作为该边的基准点。
除此之外，在确定基准点之前，还可以首先删除当前块其中一个边的末端位置对应的预设数量个参考像素点，或者针对该边从末端位置开始按照预设偏移量进行初始偏移，以偏移后的参考像素点位置作为起始点，得到新的边，然后将新的边对应的中间位置作为基准点；相应的，也可以首先删除当前块其中一个边的起始位置对应的预设数量个参考像素点，或者针对该边从起始位置开始按照预设偏移量进行初始偏移，以偏移后的参考像素点位置作为起始点，得到新的边，然后再将新的边对应的中间位置作为基准点。
在实际应用中，由于当前块的左侧边或者上侧边的边长都是2的整数倍，那么当前块的左侧边或者 上侧边的中间位置均是处于两个点之间。在图3的示例中，是以中间位置偏左的第一个像素点作为该边的中点；但是本申请实施例也可以将中间位置偏右的第一个像素点作为该边的中点，如图4所示。在图3中，以将中间位置偏左的第一个像素点(如图3中的3)作为该边的中点，由于预设采样个数为2，那么可以确定出待选择参考像素点位置(如图3中灰色点示例)为1和5，根据这些参考像素点位置也可以选取出与之对应的参考像素点，以此组成参考像素子集。因此，在本申请实施例中，针对当前块的上侧边，既可以将中间位置偏右的第一个像素点作为该边的中点，也可以将中间位置偏左的第一个像素点作为该边的中点，本申请实施例不作具体限定；另外，针对当前块的左侧边，既可以将中间位置偏下的第一个像素点作为该边的中点，也可以将中间位置偏上的第一个像素点作为该边的中点，本申请实施例也不作具体限定。
除特别说明外，下文中将以当前块的上侧边为例进行说明，但是本申请实施例的图像分量预测方法同样适用于当前块的左侧边，甚至是重建块的右侧边或者重建块的下侧边，本申请实施例不作具体限定。
可以理解地，如果不考虑与当前块的左侧边或者上侧边相邻的参考像素点的存在性，那么还可以根据式(1)和式(2)进行第二参考像素集合的构造，
△＝length/(N 2/2)                            (1)
shift＝△/2                                  (2)
其中，△表示采样间隔，length表示与当前块的上侧边相邻的一行参考像素点的个数、或者与当前块的左侧边相邻的一列参考像素点的个数，N 2表示当前块所期望的构成参考像素子集中参考像素点个数(一般来说，左侧边和上侧边各自为二分之一，但是本申请实施例不作具体限定)，shift表示选取参考像素点的起始点位置。这里，当当前块的左侧边或者上侧边的中间位置均是处于两个点之间时，此时如果以中间位置偏右的第一个像素点作为该边的中点，那么起始点位置shift＝△/2；此时如果以中间位置偏左的第一个像素点作为该边的中点，那么起始点位置shift＝△/2-1。
示例性地，以图3所示的上侧边为例，length等于8，N 2等于4，假定左侧边和上侧边各自为二分之一，即上侧边的预设采样个数为2，那么根据式(1)和式(2)分别计算得到△＝length/(N 2/2)＝4，shift＝△/2＝2，即以1为起始点位置、4为采样间隔，首先可以确定出待选择参考像素点位置，比如为1和5，进而可以选取到对应的参考像素点，以组成参考像素子集。这里，需要注意的是，左侧边对应的预设采样个数和上侧边对应的预设采样个数，两者的取值可以相同，也可以不同，本申请实施例不作具体限定。
还需要说明的是，根据预设候选像素数和当前块一个边的长度，可以计算得到该边对应的第一采样间隔。另外，由于当前块的左侧边或者上侧边的边长都是2的整数倍，那么当前块的左侧边或者上侧边的中间位置均是处于两个点之间，此时计算得到的中点值为非整数，计算得到的参考像素点位置也为非整数；然而如果当前块的左侧边或者上侧边的边长不是2的整数倍，那么当前块的左侧边或者上侧边的中间位置不会处于两个点之间，此时计算得到的中点值为整数，计算得到的参考像素点位置也为整数；也就是说，计算得到的中点值可以为整数，也可以为非整数；对应地，计算得到的参考像素点位置也可以为整数，也可以为非整数；本申请实施例不作具体限定。
这样，当计算得到的中点值为整数时，对应地，计算得到的参考像素点位置也为整数，此时可以直接将计算得到的参考像素点位置作为候选位置；当计算得到的中点值为非整数时，对应地，计算得到的参考像素点位置也为非整数，此时可以通过向大取整或者向小取整来确定出候选位置。
进一步地，在一些实施例中，在计算第一采样间隔之后，该方法还可以包括：
对所述第一采样间隔进行调整，得到第二采样间隔；
基于所述基准点，按照所述第二采样间隔确定所述候选位置。
需要说明的是，当计算得到第一采样间隔之后，还可以对第一采样间隔进行微调，比如对第一采样间隔进行加1或者减1的操作，以此得到第二采样间隔。例如，第一采样间隔为4，那么调整后的第二采样间隔可以为3或者5。在本申请实施例中，针对第一采样间隔的调整，可以进行小幅度(比如，加1或者减1)的调整，但是针对调整幅度的具体设定，本申请实施例不作具体限定。
进一步地，在一些实施例中，得到第二采样间隔之后，该方法还可以包括：
基于所述基准点，按照所述第一采样间隔确定所述基准点一侧对应的候选位置，按照所述第二采样间隔确定所述基准点另一侧对应的候选位置。
也就是说，当确定出当前块至少一条边的基准点之后，可以按照第一采样间隔或者第二采样间隔进行均匀采样；也可以按照第一采样间隔和第二采样间隔进行非均匀采样，而且采样后所确定的候选位置可以对称分布在基准点两侧，也可以非对称分布在基准点两侧；本申请实施例不作具体限定。
进一步地，由于第一参考像素集合中与当前块的待预测图像分量比较相关的是位于至少一个边的中间位置的参考像素点，那么可以将该中间位置附近连续的预设采样个数的参考像素点位置作为待选择参考像素点位置，该方法可以称之为中间位置连续取点方案。具体地，假定与当前块的上侧边或者左侧边相邻的一行/一列上的参考像素点位置从0开始编号，那么本实施例中所组成的参考像素子集中相邻参考像素点个数以及对应的待选择参考像素点位置如表1所示。这时候可以将中间位置附近连续的预设采样个数的参考像素点位置作为候选位置，以此组成参考像素子集。
表1
当前块的至少一个边的边长 候选位置 预设候选像素数
2 0,1 2
4 1,2 2
8 2,3,4(或3,4,5) 3
16 6,7,8,9 4
32 13,14,15,16,17,18,19,20 8
进一步地，对于第一参数像素集合的筛选处理，还可以对至少一个边的参考像素点进行跳点处理，即将不重要的参考像素点或存在异常的参考像素点跳过去(也可以看作是删除处理)，从而得到参考像素子集；也可以在此基础上，即至少一个边的部分参考像素点跳过之后，得到第二参考像素集合，在对第二参考像素集合在进行筛选处理，以得到参考像素子集。因此，在一些实施例中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，可以包括：
确定所述至少一个边对应的预设跳过像素数K，其中，K为大于或等于1的正整数；
从所述至少一个边的起始位置和/或末端位置开始，确定K个待跳过像素点对应的位置；
基于所述K个待跳过像素点对应的位置，从所述至少一个边的起始位置和/或末端位置开始连续跳过K个待跳过像素点，得到至少一个新边；
基于所述至少一个新边以及所述预设候选像素数，确定所述候选位置。
需要说明的是，预设跳过像素数表示预先设定的待删除或者待跳过的像素点个数。另外，至少一个边的起始位置表示当前块的上侧边的最左边缘位置或者当前块的左侧边的最上边缘位置，至少一个边的末端位置表示当前块的上侧边的最右边缘位置或者当前块的左侧边的最下边缘位置。
还需要说明的是，K的取值可以是预先设置的参考像素点个数，比如1、2或者4等；还可以是根据当前块的边长以及与之对应的预设比例进行计算得到；但是在实际应用中，仍然根据实际情况进行设定，本申请实施例不作具体限定。其中，与当前块的上侧边对应的预设比例可以用第一预设比例表示，与当前块的左侧边对应的预设比例可以用第二预设比例表示，第一预设比例与第二预设比例的取值可以相同，也可以不相同，本申请实施例也不作具体限定。
这样，假定从至少一个边的起始位置开始，如果至少一个边为当前块的上侧边(也可以称为当前块的参考行)，那么可以从至少一个边的最左边缘位置开始，确定出K个待跳过像素点对应的位置；如果至少一个边为当前块的左侧边(也可以称为当前块的参考列)，那么可以从至少一个边的最上边缘位置开始，确定出K个待跳过像素点对应的位置；假定从至少一个边的末端位置开始，如果至少一个边为当前块的上侧边，那么可以从至少一个边的最右边缘位置开始，确定出K个待跳过像素点对应的位置；如果至少一个边为当前块的左侧边，那么可以从至少一个边的最下边缘位置开始，确定出K个待跳过像素点对应的位置；在实际应用中，根据实际情况进行设定，本申请实施例不作具体限定。
在确定出K个待跳过像素点对应的位置之后，假定从至少一个边的起始位置开始，如果至少一个边为当前块的上侧边，那么可以从该上侧边的最左边缘位置开始，向右确定出连续的K个待跳过像素点所对应的位置，然后连续跳过这K个待跳过像素点，得到新的上侧边；这时候可以根据新的上侧边的边长以及预设候选像素数，确定出该新的上侧边对应的候选位置，从而将选取得到的候选像素组成参考像素子集；如果至少一个边为当前块的左侧边，那么可以从该左侧边的最上边缘位置开始，向下确定出连续的K个待跳过像素点所对应的位置，然后连续跳过这K个待跳过像素点，得到新的左侧边；这时候可以根据新的左侧边的边长以及预设候选像素数，确定出该新的左侧边对应的候选位置，从而将选取得到的候选像素组成参考像素子集。或者，假定从至少一个边的末端位置开始，如果至少一个边为当前块的上侧边，那么可以从该上侧边的最右边缘位置开始，向左确定出连续的K个待跳过像素点所对应的位置，然后连续跳过这K个待跳过像素点，得到新的上侧边；这时候可以根据新的上侧边的边长以及预设候选像素数，确定出该新的上侧边对应的候选位置，从而将选取得到的候选像素组成参考像素子集；如果至少一个边为当前块的左侧边，那么可以从该左侧边的最下边缘位置开始，向上确定出连续的K个待跳过像素点所对应的位置，然后连续跳过这K个待跳过像素点，得到新的左侧边；这时候可以根据新的左侧边的边长以及预设候选像素数，确定出该新的左侧边对应的候选位置，从而将选取得到 的候选像素组成参考像素子集。
这样，本申请实施例使用当前块相邻的参考像素点所得到的第一参考像素集合中的部分像素(即参考像素子集)来推导复杂模型(比如非线性模型或者多模型)对应的模型参数。由于所得到的子集(即参考像素子集)中已经剔除了不重要的参考像素点或者存在异常的参考像素点，从而使其具有更少的参考像素点个数，这样不仅降低了计算复杂度和内存带宽，而且还提高了复杂模型的精确度，从而可以达到提升待处理图像分量的预测准确性和视频图像的预测效率的目的。
进一步地，在确定出参考像素子集之后，可以根据该参考像素子集，计算预测模型的模型参数，便于构建预测模型。因此，在一些实施例中，对于S103来说，所述利用所述参考像素子集，计算预测模型的模型参数，可以包括：
基于所述参考像素子集，获取所述当前块对应的待预测图像分量的相邻像素重建值和参考块对应的待预测图像分量的相邻像素重建值；其中，所述当前块位于第N帧视频图像，所述参考块位于第N-1帧视频图像；
根据所述当前块对应的待预测图像分量的相邻像素重建值以及所述参考块对应的待预测图像分量的相邻像素重建值，计算得到模型参数。
需要说明的是，参考块与当前块并不是位于同一帧内，两者之间属于帧间关系。其中，参考块与当前块位于不同帧的视频图像中，且参考块所处的帧为当前块所处帧的前一帧，也即当前块处于第N帧视频图像，而参考块处于第N-1帧视频图像；另外，当前块在第N帧视频图像中的位置与参考块在第N-1帧视频图像中的位置会存在运动向量(Motion Vector，MV)的偏移。
另外，模型参数包括第一模型参数α和第二模型参数β。而针对α和β的计算具有多种方式，可以是以最小二乘法构造的预设因子计算模型，也可以是以最大值与最小值构造的预设因子计算模型，甚至还可以是其他方式构造的预设因子计算模型，本申请实施例不作具体限定。
以最小二乘法构造的预设因子计算模型为例，假定该预测模型主要是用于对亮度分量的预测处理，比如IC技术或者LIC技术；这时候α和β可以通过当前块对应的亮度分量相邻像素重建值和参考块对应的亮度分量相邻像素重建值进行最小化回归误差来推导得到，具体地，如式(3)所示的预设因子计算模型：
Figure PCTCN2019113765-appb-000001
其中，L(n)表示参考块对应的亮度分量相邻像素重建值，C(n)表示当前块对应的亮度分量相邻像素重建值，N为当前块对应的亮度分量相邻像素个数，n＝1,2,...,2N。这样，通过式(3)的计算，可以得到第一模型参数α和第二模型参数β。
以最大值与最小值构造的预设因子计算模型为例，它提供了一种简化版模型参数的推导方法，具体地，可以通过在参考块对应的亮度分量相邻像素重建值中搜索最大值和最小值，根据“两点确定一线”原则来推导出α和β，如式(4)所示的预设因子计算模型：
Figure PCTCN2019113765-appb-000002
其中，L max和L min表示在参考块对应的亮度分量相邻像素重建值中搜索得到的最大值和最小值，C max和C min表示L max和L min对应位置的参考像素点在当前块对应的亮度分量相邻像素重建值中所对应的亮度分量相邻像素重建值。根据L max和L min以及C max和C min，通过式(4)的计算，也可以得到第一模型参数α和第二模型参数β。
在得到第一模型参数α和第二模型参数β之后，可以构建预测模型。具体地，基于α和β，假设根据参考块对应的亮度分量预测值来预测当前块对应的亮度分量预测值，那么所构建的预测模型如式(5)所示，
Pred 1[i,j]＝α·Pred[i,j]+β           (5)
其中，i，j表示当前块中像素点的位置坐标，i表示水平方向，j表示竖直方向，Pred 1[i,j]表示当前块中位置坐标为[i,j]的像素点对应的亮度分量预测值，Pred[i,j]表示参考块中位置坐标为[i,j]的像素点对应的亮度分量预测值。
还需要说明的是，本申请实施例中的预测模型可以是线性模型，也可以是非线性模型。而非线性模型可以是二次曲线等非线性形式，也可以是多个线性模型构成的非线性形式；其中，多模型CCLM(Multiple Model CCLM，MMLM)的跨分量预测技术，它就是由多个线性模型所构成的非线性形式。参见图5，其示出了本申请实施例提供的一种预测模型的对比结构示意图。在图5中，(a)表示了预测模型为线性模型，它是根据第二参考像素集合中所有参考像素点推导得到的；(b)表示了预测模型仍为线性模型，它是根据第二参考像素集合中的最大值和最小值推导得到的；(c)表示了预测模型为非线性模型，它是根据两个线性模型所组成的非线性模型示例。需特别说明的是，本申请实施例将以预测模型为线性模型为例进行描述，但是本申请实施例的图像分量预测方法同样可以适用于非线性模型。
还需要说明的是，本申请实施例中的预测模型不仅可以用于对亮度分量的预测处理，还可以用于对色度分量的预测处理。而且通过该预测模型，可以实现对待预测图像分量(比如亮度分量或者色度分量)的预测值进行更新，从而使得图像分量的预测更为准确，可以达到提升待预测图像分量的预测准确性和视频图像的预测效率的目的。
进一步地，在一些实施例中，在所述利用所述参考像素子集，计算预测模型的模型参数之后，该方法还可以包括：
根据所述模型参数，构建所述预测模型；
通过所述预测模型对所述当前块的待预测图像分量进行预测处理，得到所述待预测图像分量对应的预测值。
需要说明的是，在构建出预测模型之后，可以根据该预测模型对待预测图像分量进行预测处理。一方面，可以利用参考块的第一图像分量预测当前块的第一图像分量，比如利用参考块的亮度分量来预测当前块的亮度分量，实现对亮度分量预测值的更新；另一方面，还可以利用参考块的第二图像分量预测当前块的第二图像分量，比如利用参考块的蓝色色度分量来预测当前块的蓝色色度分量，实现对蓝色色度分量预测值的更新；再一方面，也可以利用参考块的第三图像分量预测当前块的第三图像分量，比如利用参考块的红色色度分量来预测当前块的红色色度分量，实现对红色色度分量预测值的更新；本申请实施例不作具体限定。
本实施例提供了一种图像分量预测方法，通过确定当前块的待预测图像分量的第一参考像素集合；从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度；由于所述预测模型是用于通过所述模型参数实现对所述待预测图像分量的预测处理，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
参见图6，其示出了本申请实施例提供的另一种图像分量预测方法的流程示意图。如图6所示，该方法可以包括：
S601：从所述第一参考像素集合中选取部分参考像素点，组成参考像素子集；
S602：根据所述参考像素子集，计算预测模型的模型参数。
需要说明的是，参考像素子集是从第一参考像素集合中选取部分参考像素点所得到的；而模型参数是根据参考像素子集进行计算得到的；这样，由于参考像素子集中的样本数量减少，也就减少了计算模型参数所需的样本数量，从而可以达到减少降低计算复杂度和内存带宽(或称为存储器带宽)的目的。
在一些实施例中，所述确定当前块的待预测图像分量的第一参考像素集合，可以包括：
将所述当前块的一个或多个第一相邻像素作为所述第一参考像素集合；其中，所述第一相邻像素是位于与所述当前块竖直边、与所述当前块水平边、或者与所述当前块竖直边和水平边相邻的像素。
进一步地，在一些实施例中，该方法还可以包括：
若所述第一相邻像素位于所述当前块外，则确定所述当前块竖直边是所述当前块外左相邻列，所述当前块水平边是所述当前块外上相邻行。
进一步地，在一些实施例中，该方法还可以包括：
若所述第一相邻像素位于所述当前块内，则确定所述当前块竖直边是所述当前块内右侧边列，所述当前块水平边是所述当前块内下侧边行。
需要说明的是，当第一相邻像素位于当前块之外时，当前块竖直边可以看作当前块的左侧边，当前块水平边可以看作当前块的上侧边；当第一相邻像素位于当前块之内时，当前块竖直边可以看作当前块的右侧边，当前块水平边可以看作当前块的下侧边。
这样，在得到当前块的一个或多个第一相邻像素之后，可以组成第一参考像素集合。由于该第一参考像素集合中可能会存在部分不重要的参考像素点(比如这些参考像素点的相关性较差)或者部分异常的参考像素点，为了保证模型参数推导的准确性，需要将这些参考像素点剔除掉，从而可以得到参考像素子集。因此，在一些实施例中，所述确定参考像素子集，可以包括：
在所述当前块的边上，确定所述候选像素的候选位置，其中，所述当前块的边是所述当前块的竖直边或水平边；
从所述第一参考像素集合中选择位于所述候选位置的像素，将所选择的像素组成所述参考像素子集。
进一步地，所述确定候选像素的候选位置，可以包括：
根据所述第一参考像素集合中像素的位置，确定所述候选像素的候选位置。
进一步地，所述确定候选像素的候选位置，可以包括：
根据所述第一参考像素集合中像素的图像分量强度，确定所述候选像素的候选位置。
进一步地，所述确定候选像素的候选位置，可以包括：
根据所述第一参考像素集合中像素的位置和图像分量强度，确定所述候选像素的候选位置。
需要说明的是，图像分量强度可以用图像分量值来表示，比如亮度值、色度值等；这里，图像分量值越大，表明了图像分量强度越高。本申请实施例所选取的参考像素，可以是通过候选像素的候选位置来进行选取的；其中，候选位置可以是根据像素位置确定，也可以是根据图像分量强度值(比如亮度值、色度值等)确定，本申请实施例不作具体限定。
还需要说明的是，参考像素子集是通过对第一参考像素集合进行筛选处理，然后选取部分参考像素点所组成的；而模型参数是根据参考像素子集进行计算得到的；这样，由于参考像素子集中样本数量减少，也就减少了计算模型参数所需的样本数量，从而可以达到减少降低计算复杂度和内存带宽(或称为存储器带宽)的目的。
可以理解，本申请实施例所选取的部分参考像素点，可以是通过参考像素对应的像素位置来选取的，也可以是根据参考像素对应的图像分量强度值(比如亮度值、色度值等)来选取的，本申请实施例不作具体限定。其中，无论是通过参考像素对应的像素位置，还是通过参考像素对应的图像分量强度值对第一参考像素集合进行筛选以选取出合适的参考像素点，进而组成参考像素子集；这样，根据参考像素子集推导得到的模型参数更准确，使得根据该模型参数所构建的预测模型也可以更精确。
在一些实施例中，所述确定所述候选像素的候选位置，可以包括：
确定预设候选像素数，其中，所述预设候选像素数指示从所述当前块的边上选取的像素数；
根据所述第一预设像素数和所述当前块的边的长度，确定所述候选像素的候选位置；其中，所述当前块的边的长度等于所述第一参考像素集合中位于所述当前块的边上的参考像素的数量。
需要说明的是，预设候选像素数表示预先设定的待采样的像素点个数，即参考像素子集中所包含的像素个数。以像素位置为例，可以在确定出预设候选像素数之后，根据至少一个边的边长和预设候选像素数来计算出候选像素的候选位置；然后根据候选位置，从第一参考像素集合中选取合适的参考像素点来组成参考像素子集。这样，根据参考像素子集所计算的模型参数更为准确，从而构建的预测模型也可以更精确，进而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
进一步地，对于候选位置的确定，可以先计算第一采样间隔，然后根据第一采样间隔对该至少一个边进行采样处理，以确定出该至少一个边对应的候选像素的候选位置。因此，在一些实施例中，所述确定所述候选像素的候选位置，可以包括：
根据所述当前块的边的长度和所述预设候选像素数，计算第一采样间隔。
进一步地，所述确定候选像素的候选位置，可以包括：
对所述第一采样间隔进行调整，得到第二采样间隔。
需要说明的是，当计算得到第一采样间隔之后，还可以对第一采样间隔进行微调，比如对第一采样间隔进行加1或者减1的操作，以此得到第二采样间隔。例如，第一采样间隔为4，那么调整后的第二采样间隔可以为3或者5。在本申请实施例中，针对第一采样间隔的调整，可以进行小幅度(比如，加1或者减1)的调整，但是针对调整幅度的具体设定，本申请实施例不作具体限定。
在一些实施例中，可选地，在所述计算第一采样间隔之后，该方法还可以包括：
在所述当前块的边上确定基准点，从所述基准点起，以所述第一采样间隔确定所述当前块的边上的候选位置。
进一步地，在所述计算第一采样间隔之后，该方法还可以包括：
在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点两侧的候选位置。
在一些实施例中，可选地，在所述得到第二采样间隔之后，该方法还可以包括：
在所述当前块的边上确定基准点，从所述基准点起，以所述第二采样间隔确定所述当前块的边上的候选位置。
进一步地，在所述得到第二采样间隔之后，该方法还可以包括：
在所述当前块的边上确定基准点，以所述第二采样间隔确定所述基准点两侧的候选位置。
需要说明的是，基准点可以是所述至少一个边的中点，也可以是所述至少一个边的中点偏左的第一个参考像素点位置，还可以是所述至少一个边的中点偏右的第一参考像素点位置，甚至还可以是所述至少一个边的其他参考像素点位置，本申请实施例不作具体限定。
具体地，可以根据所述至少一个边的长度，确定所述至少一个边的中点，然后将所述至少一个边的中点作为所述基准点。其中，基准点可以是所述至少一个边的中点，也可以是所述至少一个边的中点偏左的第一个参考像素点位置，还可以是所述至少一个边的中点偏右的第一参考像素点位置，甚至还可以是所述至少一个边的其他参考像素点位置，本申请实施例不作具体限定。
进一步地，在一些实施例中，在所述得到第二采样间隔之后，该方法还可以包括：
在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点一侧对应的候选位置，以所述第二采样间隔确定所述基准点另一侧对应的候选位置。
也就是说，当确定出当前块至少一条边的基准点之后，可以按照第一采样间隔或者第二采样间隔进行均匀采样；也可以按照第一采样间隔和第二采样间隔进行非均匀采样，而且采样后所确定的候选位置可以对称分布在基准点两侧，也可以非对称分布在基准点两侧；本申请实施例不作具体限定。
进一步地，对于第一参数像素集合的选取处理，还可以对至少一个边的参考像素点进行跳点处理，即将不重要的参考像素点或存在异常的参考像素点跳过去(也可以看作是删除处理)，从而得到参考像素子集；也可以在此基础上，即至少一个边的部分参考像素点跳过之后，得到第二参考像素集合，在对第二参考像素集合在进行筛选处理，以得到参考像素子集。因此，该方法还可以包括：
确定所述当前块的边的预设跳过像素数K，其中，K是非负整数；
从所述当前块的边的端位置起，将第K个像素位置设置为所述基准点；
其中，所述当前块的边的端位置是所述当前块的边的起始像素位置或末端像素位置。
需要说明的是，预设跳过像素数表示预先设定的待删除或者待跳过的像素点个数。另外，至少一个边的起始位置表示当前块的上侧边的最左边缘位置或者当前块的左侧边的最上边缘位置，至少一个边的末端位置表示当前块的上侧边的最右边缘位置或者当前块的左侧边的最下边缘位置。
还需要说明的是，K的取值可以是预先设置的参考像素点个数，比如1、2或者4等；还可以是根据当前块的边长以及与之对应的预设比例进行计算得到；但是在实际应用中，仍然根据实际情况进行设定，本申请实施例不作具体限定。其中，与当前块的上侧边对应的预设比例可以用第一预设比例表示，与当前块的左侧边对应的预设比例可以用第二预设比例表示，第一预设比例与第二预设比例的取值可以相同，也可以不相同，本申请实施例也不作具体限定。
在确定出参考像素子集之后，还可以根据该参考像素子集，计算预测模型的模型参数，便于构建预测模型。因此，在一些实施例中，所述利用所述参考像素子集，计算预测模型的模型参数，可以包括：
利用所述参考像素子集中的参考像素和所述当前块的参考块的位于所述参考像素子集中参考像素的同位置的像素，计算预测模型的模型参数；
其中，所述参考像素子集中参考像素的同位置的像素是位于所述参考块所在图像中、与参考块之间的相对位置与所述第二参考像素集合中的参考像素与所述当前块之间相对位置相同的像素。
进一步地，在所述计算预测模型的模型参数之后，该方法还可以包括：
根据所述预测模型和所述当前块的参考块，计算所述当前块的待预测图像分量的预测值。
需要说明的是，参考块可以是当前块的帧间预测参数指示的图像块。这样，在计算得到模型参数(比如第一模型参数α和第二模型参数β)之后，可以构建出预测模型，如前述的式(5)所示。根据该预测模型以及当前块的参考块，可以进一步计算当前块的待预测图像分量的预测值。
另外，本申请实施例中，当该图像分量预测方法应用于编码器侧时，可以从当前块的第一参考像素集合中选取部分像素构造参考像素子集，然后根据该参考像素子集计算预测模型的模型参数，并将计算得到的模型参数写入码流中；该码流由编码器侧传输到解码器侧；对应地，当该图像分量预测方法应用于解码器侧时，可以通过解析码流来直接获得预测模型的模型参数；或者在解码器侧，也可以从当前块的第一参考像素集合中选取部分像素构造参考像素子集，然后根据该参考像素子集计算预测模型的模型参数，从而构建出预测模型，利用该预测模型对当前块的至少一个图像分量进行跨分量预测处理。
本实施例提供了一种图像分量预测方法，对前述实施例的具体实现进行了详细阐述，通过前述实施 例的技术方案可以看出，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度；由于所述预测模型是用于通过所述模型参数实现对所述待预测图像分量的预测处理，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
基于前述实施例相同的发明构思，参见图7，其示出了本申请实施例提供的一种编码器70的组成结构示意图。如图7所示，编码器70可以包括：第一确定单元701和第一计算单元702，其中，
所述第一确定单元701，配置为确定当前块的待预测图像分量的第一参考像素集合；
所述第一确定单元701，还配置为从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
所述第一计算单元702，配置为利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
在上述方案中，参见图7，编码器70还可以包括第一获取单元703，配置为在所述当前块之外，获取与所述当前块的至少一个边相邻的参考像素；其中，所述当前块的至少一个边包括下述至少之一：上侧边、左侧边、右上侧边和左下侧边；以及根据获取的参考像素，得到所述第一参考像素集合。
在上述方案中，所述第一获取单元703，还配置为在重建块之内，获取所述重建块的至少一个边相邻的参考像素；其中，所述重建块为与所述当前块相邻且已完成编码重构建的图像块，所述重建块的至少一个边包括：下侧边、右侧边、或者下侧边和右侧边；以及根据获取的参考像素，得到所述第一参考像素集合。
在上述方案中，参见图7，编码器70还可以包括第一选取单元704，其中，
所述第一确定单元701，还配置为基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置；
所述第一选取单元704，配置为从所述第一参考像素集合中选取与所述候选位置对应的参考像素，将选取得到的参数像素组成所述参考像素子集。
在上述方案中，所述第一确定单元701，还配置为基于所述至少一个边相邻的参考像素对应的像素位置，确定所述候选位置。
在上述方案中，所述第一确定单元701，还配置为基于所述至少一个边相邻的参考像素对应的图像分量强度值，确定所述候选位置。
在上述方案中，所述第一确定单元701，还配置为基于所述至少一个边相邻的参考像素对应的像素位置和图像分量强度值，确定所述候选位置。
在上述方案中，所述第一确定单元701，还配置为确定预设候选像素数；其中，所述预设候选像素数表示从所述至少一个边相邻的参考像素中所采样的像素数量；以及根据所述预设候选像素数和所述至少一个边的长度，确定所述候选位置；其中，所述至少一个边的长度等于所述至少一个边所包含的像素数量。
在上述方案中，所述第一计算单元702，还配置为根据所述预设候选像素数和所述至少一个边的长度，计算第一采样间隔；
所述第一确定单元701，还配置为从所述至少一个边中确定一基准点，按照所述第一采样间隔确定所述候选位置。
在上述方案中，参见图7，编码器70还可以包括第一调整单元705，配置为所述第一确定单元701，还配置为对所述第一采样间隔进行调整，得到第二采样间隔；
所述第一确定单元701，还配置为基于所述基准点，按照所述第二采样间隔确定所述候选位置。
在上述方案中，所述第一确定单元701，还配置为基于所述基准点，按照所述第一采样间隔确定所述基准点一侧对应的候选位置，按照所述第二采样间隔确定所述基准点另一侧对应的候选位置。
在上述方案中，所述第一确定单元701，还配置为确定所述至少一个边对应的预设跳过像素数K，其中，K为大于或等于1的正整数；以及从所述至少一个边的起始位置和/或末端位置开始，确定K个待跳过像素点对应的位置；以及基于所述K个待跳过像素点对应的位置，从所述至少一个边的起始位置和/或末端位置开始连续跳过K个待跳过像素点，得到至少一个新边；以及基于所述至少一个新边以及所述预设候选像素数，确定所述候选位置。
在上述方案中，所述第一选取单元704，还配置为基于所述参考像素子集，获取所述当前块对应的待预测图像分量的相邻像素重建值和参考块对应的待预测图像分量的相邻像素重建值；其中，所述当前块位于第N帧视频图像，所述参考块位于第N-1帧视频图像；
所述第一计算单元702，还配置为根据所述当前块对应的待预测图像分量的相邻像素重建值以及所述参考块对应的待预测图像分量的相邻像素重建值，计算得到所述模型参数。
在上述方案中，参见图7，编码器70还可以包括第一构建单元706和第一预测单元707，其中，
所述第一构建单元706，配置为根据所述模型参数，构建所述预测模型；
所述第一预测单元707，配置为通过所述预测模型对所述当前块的待预测图像分量进行预测处理，得到所述待预测图像分量对应的预测值。
在上述方案中，所述第一确定单元701，还配置为将所述当前块的一个或多个第一相邻像素作为所述第一参考像素集合；其中，所述第一相邻像素是位于与所述当前块竖直边、与所述当前块水平边、或者与所述当前块竖直边和水平边相邻的像素。
在上述方案中，所述第一确定单元701，还配置为若所述第一相邻像素位于所述当前块外，则确定所述当前块竖直边是所述当前块外左相邻列，所述当前块水平边是所述当前块外上相邻行。
在上述方案中，所述第一确定单元701，还配置为若所述第一相邻像素位于所述当前块内，则确定所述当前块竖直边是所述当前块内右侧边列，所述当前块水平边是所述当前块内下侧边行。
在上述方案中，所述第一确定单元701，还配置为在所述当前块的边上，确定所述候选像素的候选位置，其中，所述当前块的边是所述当前块的竖直边或水平边；以及从所述第一参考像素集合中选择位于所述候选位置的像素，将所选择的像素组成所述参考像素子集。
在上述方案中，所述第一确定单元701，还配置为根据所述第一参考像素集合中像素的位置，确定所述候选像素的候选位置。
在上述方案中，所述第一确定单元701，还配置为根据所述第一参考像素集合中像素的图像分量强度，确定所述候选像素的候选位置。
在上述方案中，所述第一确定单元701，还配置为根据所述第一参考像素集合中像素的位置和图像分量强度，确定所述候选像素的候选位置。
在上述方案中，所述第一确定单元701，还配置为确定预设候选像素数，其中，所述预设候选像素数指示从所述当前块的边上选取的像素数；
根据所述第一预设像素数和所述当前块的边的长度，确定所述候选像素的候选位置；其中，所述当前块的边的长度等于所述第一参考像素集合中位于所述当前块的边上的参考像素的数量。
在上述方案中，所述第一计算单元702，还配置为根据所述当前块的边的长度和所述预设候选像素数，计算第一采样间隔。
在上述方案中，所述第一调整单元705，配置为对所述第一采样间隔进行调整，得到第二采样间隔。
在上述方案中，所述第一确定单元701，还配置为在所述当前块的边上确定基准点，从所述基准点起，以所述第一采样间隔确定所述当前块的边上的候选位置。
在上述方案中，所述第一确定单元701，还配置为在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点两侧的候选位置。
在上述方案中，所述第一确定单元701，还配置为在所述当前块的边上确定基准点，从所述基准点起，以所述第二采样间隔确定所述当前块的边上的候选位置。
在上述方案中，所述第一确定单元701，还配置为在所述当前块的边上确定基准点，以所述第二采样间隔确定所述基准点两侧的候选位置。
在上述方案中，所述第一确定单元701，还配置为在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点一侧对应的候选位置，以所述第二采样间隔确定所述基准点另一侧对应的候选位置。
在上述方案中，所述第一确定单元701，还配置为确定所述当前块的边的预设跳过像素数K，其中，K是非负整数；以及从所述当前块的边的端位置起，将第K个像素位置设置为所述基准点；其中，所述当前块的边的端位置是所述当前块的边的起始像素位置或末端像素位置。
在上述方案中，所述第一计算单元702，还配置为利用所述参考像素子集中的参考像素和所述当前块的参考块的位于所述参考像素子集中参考像素的同位置的像素，计算预测模型的模型参数；其中，所述参考像素子集中参考像素的同位置的像素是位于所述参考块所在图像中、与参考块之间的相对位置与所述第二参考像素集合中的参考像素与所述当前块之间相对位置相同的像素。
在上述方案中，所述第一计算单元702，还配置为根据所述预测模型和所述当前块的参考块，计算所述当前块的待预测图像分量的预测值。
在上述方案中，所述参考块是当前块的帧间预测参数指示的图像块。
可以理解地，在本申请实施例中，“单元”可以是部分电路、部分处理器、部分程序或软件等等，当然也可以是模块，还可以是非模块化的。而且在本实施例中的各组成部分可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。
所述集成的单元如果以软件功能模块的形式实现并非作为独立的产品进行销售或使用时，可以存储在一个计算机可读取存储介质中，基于这样的理解，本实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或processor(处理器)执行本实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
因此，本申请实施例提供了一种计算机存储介质，该计算机存储介质存储有图像分量预测程序，所述图像分量预测程序被至少一个处理器执行时实现前述实施例所述方法的步骤。
基于上述编码器70的组成以及计算机存储介质，参见图8，其示出了本申请实施例提供的编码器70的具体硬件结构示例，可以包括：第一通信接口801、第一存储器802和第一处理器803；各个组件通过第一总线系统804耦合在一起。可理解，第一总线系统804用于实现这些组件之间的连接通信。第一总线系统804除包括数据总线之外，还包括电源总线、控制总线和状态信号总线。但是为了清楚说明起见，在图8中将各种总线都标为第一总线系统804。其中，
第一通信接口801，用于在与其他外部网元之间进行收发信息过程中，信号的接收和发送；
第一存储器802，用于存储能够在第一处理器803上运行的计算机程序；
第一处理器803，用于在运行所述计算机程序时，执行：
确定当前块的待预测图像分量的第一参考像素集合；
从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
可以理解，本申请实施例中的第一存储器802可以是易失性存储器或非易失性存储器，或可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(Read-Only Memory，ROM)、可编程只读存储器(Programmable ROM，PROM)、可擦除可编程只读存储器(Erasable PROM，EPROM)、电可擦除可编程只读存储器(Electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory，RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(Static RAM，SRAM)、动态随机存取存储器(Dynamic RAM，DRAM)、同步动态随机存取存储器(Synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM，DDRSDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(Synchlink DRAM，SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM，DRRAM)。本申请描述的系统和方法的第一存储器802旨在包括但不限于这些和任意其它适合类型的存储器。
而第一处理器803可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法的各步骤可以通过第一处理器803中的硬件的集成逻辑电路或者软件形式的指令完成。上述的第一处理器803可以是通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于第一存储器802，第一处理器803读取第一存储器802中的信息，结合其硬件完成上述方法的步骤。
可以理解的是，本申请描述的这些实施例可以用硬件、软件、固件、中间件、微码或其组合来实现。对于硬件实现，处理单元可以实现在一个或多个专用集成电路(Application Specific Integrated Circuits，ASIC)、数字信号处理器(Digital Signal Processing，DSP)、数字信号处理设备(DSP Device，DSPD)、可编程逻辑设备(Programmable Logic Device，PLD)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)、通用处理器、控制器、微控制器、微处理器、用于执行本申请所述功能的其它电子单元或其组合中。对于软件实现，可通过执行本申请所述功能的模块(例如过程、函数等)来实现本申请所述的技术。软件代码可存储在存储器中并通过处理器执行。存储器可以在处理器中或在处理器外部实现。
可选地，作为另一个实施例，第一处理器803还配置为在运行所述计算机程序时，执行前述实施例中任一项所述的方法。
本实施例提供了一种编码器，该编码器可以包括第一确定单元和第一计算单元，其中，第一确定单元配置为确定当前块的待预测图像分量的第一参考像素集合；还配置为从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；第一计算单元配置为利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度；由于所述预测模型是用于通过所述模型参数实现对所述待预测图像分量的预测处理，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
基于前述实施例相同的发明构思，参见图9，其示出了本申请实施例提供的一种解码器90的组成结构示意图。如图9所示，解码器90可以包括：第二确定单元901和第二计算单元902，其中，
所述第二确定单元901，配置为确定当前块的待预测图像分量的第一参考像素集合；
所述第二确定单元901，还配置为从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
所述第二计算单元902，配置为利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
在上述方案中，参见图9，解码器90还可以包括第二获取单元903，配置为在所述当前块之外，获取与所述当前块的至少一个边相邻的参考像素；其中，所述当前块的至少一个边包括下述至少之一：上侧边、左侧边、右上侧边和左下侧边；以及根据获取的参考像素，得到所述第一参考像素集合。
在上述方案中，所述第二获取单元903，还配置为在重建块之内，获取所述重建块的至少一个边相邻的参考像素；其中，所述重建块为与所述当前块相邻且已完成编码重构建的图像块，所述重建块的至少一个边包括：下侧边、右侧边、或者下侧边和右侧边；以及根据获取的参考像素，得到所述第一参考像素集合。
在上述方案中，参见图9，解码器90还可以包括第二选取单元904，其中，
所述第二确定单元901，还配置为基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置；
所述第二选取单元904，配置为从所述第一参考像素集合中选取与所述候选位置对应的参考像素，将选取得到的参数像素组成所述参考像素子集。
在上述方案中，所述第二确定单元901，还配置为基于所述至少一个边相邻的参考像素对应的像素位置，确定所述候选位置。
在上述方案中，所述第二确定单元901，还配置为基于所述至少一个边相邻的参考像素对应的图像分量强度值，确定所述候选位置。
在上述方案中，所述第二确定单元901，还配置为基于所述至少一个边相邻的参考像素对应的像素位置和图像分量强度值，确定所述候选位置。
在上述方案中，所述第二确定单元901，还配置为确定预设候选像素数；其中，所述预设候选像素数表示从所述至少一个边相邻的参考像素中所采样的像素数量；以及根据所述预设候选像素数和所述至少一个边的长度，确定所述候选位置；其中，所述至少一个边的长度等于所述至少一个边所包含的像素数量。
在上述方案中，所述第二计算单元902，还配置为根据所述预设候选像素数和所述至少一个边的长度，计算第一采样间隔；
所述第二确定单元901，还配置为从所述至少一个边中确定一基准点，按照所述第一采样间隔确定所述候选位置。
在上述方案中，参见图9，解码器90还可以包括第二调整单元905，配置为所述第二确定单元901，还配置为对所述第一采样间隔进行调整，得到第二采样间隔；
所述第二确定单元901，还配置为基于所述基准点，按照所述第二采样间隔确定所述候选位置。
在上述方案中，所述第二确定单元901，还配置为基于所述基准点，按照所述第一采样间隔确定所述基准点一侧对应的候选位置，按照所述第二采样间隔确定所述基准点另一侧对应的候选位置。
在上述方案中，所述第二确定单元901，还配置为确定所述至少一个边对应的预设跳过像素数K，其中，K为大于或等于1的正整数；以及从所述至少一个边的起始位置和/或末端位置开始，确定K个待跳过像素点对应的位置；以及基于所述K个待跳过像素点对应的位置，从所述至少一个边的起始位置和/或末端位置开始连续跳过K个待跳过像素点，得到至少一个新边；以及基于所述至少一个新边以及所述预设候选像素数，确定所述候选位置。
在上述方案中，所述第二选取单元904，还配置为基于所述参考像素子集，获取所述当前块对应的待预测图像分量的相邻像素重建值和参考块对应的待预测图像分量的相邻像素重建值；其中，所述当前块位于第N帧视频图像，所述参考块位于第N-1帧视频图像；
所述第二计算单元902，还配置为根据所述当前块对应的待预测图像分量的相邻像素重建值以及所述参考块对应的待预测图像分量的相邻像素重建值，计算得到所述模型参数。
在上述方案中，参见图9，解码器90还可以包括第二构建单元906和第二预测单元907，其中，
所述第二构建单元906，配置为根据所述模型参数，构建所述预测模型；
所述第二预测单元907，配置为通过所述预测模型对所述当前块的待预测图像分量进行预测处理，得到所述待预测图像分量对应的预测值。
在上述方案中，所述第二确定单元901，还配置为将所述当前块的一个或多个第一相邻像素作为所述第一参考像素集合；其中，所述第一相邻像素是位于与所述当前块竖直边、与所述当前块水平边、或者与所述当前块竖直边和水平边相邻的像素。
在上述方案中，所述第二确定单元901，还配置为若所述第一相邻像素位于所述当前块外，则确定所述当前块竖直边是所述当前块外左相邻列，所述当前块水平边是所述当前块外上相邻行。
在上述方案中，所述第二确定单元901，还配置为若所述第一相邻像素位于所述当前块内，则确定所述当前块竖直边是所述当前块内右侧边列，所述当前块水平边是所述当前块内下侧边行。
在上述方案中，所述第二确定单元901，还配置为在所述当前块的边上，确定所述候选像素的候选位置，其中，所述当前块的边是所述当前块的竖直边或水平边；以及从所述第一参考像素集合中选择位于所述候选位置的像素，将所选择的像素组成所述参考像素子集。
在上述方案中，所述第二确定单元901，还配置为根据所述第一参考像素集合中像素的位置，确定所述候选像素的候选位置。
在上述方案中，所述第二确定单元901，还配置为根据所述第一参考像素集合中像素的图像分量强度，确定所述候选像素的候选位置。
在上述方案中，所述第二确定单元901，还配置为根据所述第一参考像素集合中像素的位置和图像分量强度，确定所述候选像素的候选位置。
在上述方案中，所述第二确定单元901，还配置为确定预设候选像素数，其中，所述预设候选像素数指示从所述当前块的边上选取的像素数；
根据所述第一预设像素数和所述当前块的边的长度，确定所述候选像素的候选位置；其中，所述当前块的边的长度等于所述第一参考像素集合中位于所述当前块的边上的参考像素的数量。
在上述方案中，所述第二计算单元902，还配置为根据所述当前块的边的长度和所述预设候选像素数，计算第一采样间隔。
在上述方案中，所述第二调整单元905，配置为对所述第一采样间隔进行调整，得到第二采样间隔。
在上述方案中，所述第二确定单元901，还配置为在所述当前块的边上确定基准点，从所述基准点起，以所述第一采样间隔确定所述当前块的边上的候选位置。
在上述方案中，所述第二确定单元901，还配置为在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点两侧的候选位置。
在上述方案中，所述第二确定单元901，还配置为在所述当前块的边上确定基准点，从所述基准点起，以所述第二采样间隔确定所述当前块的边上的候选位置。
在上述方案中，所述第二确定单元901，还配置为在所述当前块的边上确定基准点，以所述第二采样间隔确定所述基准点两侧的候选位置。
在上述方案中，所述第二确定单元901，还配置为在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点一侧对应的候选位置，以所述第二采样间隔确定所述基准点另一侧对应的候选位置。
在上述方案中，所述第二确定单元901，还配置为确定所述当前块的边的预设跳过像素数K，其中，K是非负整数；以及从所述当前块的边的端位置起，将第K个像素位置设置为所述基准点；其中，所述当前块的边的端位置是所述当前块的边的起始像素位置或末端像素位置。
在上述方案中，所述第二计算单元902，还配置为利用所述参考像素子集中的参考像素和所述当前块的参考块的位于所述参考像素子集中参考像素的同位置的像素，计算预测模型的模型参数；其中，所述参考像素子集中参考像素的同位置的像素是位于所述参考块所在图像中、与参考块之间的相对位置与所述第二参考像素集合中的参考像素与所述当前块之间相对位置相同的像素。
在上述方案中，所述第二计算单元902，还配置为根据所述预测模型和所述当前块的参考块，计算所述当前块的待预测图像分量的预测值。
在上述方案中，所述参考块是当前块的帧间预测参数指示的图像块。
可以理解地，在本实施例中，“单元”可以是部分电路、部分处理器、部分程序或软件等等，当然也可以是模块，还可以是非模块化的。而且在本实施例中的各组成部分可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。
所述集成的单元如果以软件功能模块的形式实现并非作为独立的产品进行销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本实施例提供了一种计算机存储介质，该计算机存储介质存储有图像分量预测程序，所述图像分量预测程序被第二处理器执行时实现前述实施例中任一项所述的方法。
基于上述解码器90的组成以及计算机存储介质，参见图10，其示出了本申请实施例提供的解码器90的具体硬件结构，可以包括：第二通信接口1001、第二存储器1002和第二处理器1003；各个组件通过第二总线系统1004耦合在一起。可理解，第二总线系统1004用于实现这些组件之间的连接通信。第二总线系统1004除包括数据总线之外，还包括电源总线、控制总线和状态信号总线。但是为了清楚说明起见，在图10中将各种总线都标为第二总线系统1004。其中，
第二通信接口1001，用于在与其他外部网元之间进行收发信息过程中，信号的接收和发送；
第二存储器1002，用于存储能够在第二处理器1003上运行的计算机程序；
第二处理器1003，用于在运行所述计算机程序时，执行：
确定当前块的待预测图像分量的第一参考像素集合；
从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
可选地，作为另一个实施例，第二处理器1003还配置为在运行所述计算机程序时，执行前述实施例中任一项所述的方法。
可以理解，第二存储器1002与第一存储器802的硬件功能类似，第二处理器1003与第一处理器803的硬件功能类似；这里不再详述。
本实施例提供了一种解码器，该解码器可以包括第二确定单元和第二计算单元，其中，第二确定单元配置为确定当前块的待预测图像分量的第一参考像素集合；还配置为从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；第二计算单元配置为利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度；由于所述预测模型是用于通过所述模型参数实现对所述待预测图像分量的预测处理，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。
需要说明的是，在本申请中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
本申请所提供的几个方法实施例中所揭露的方法，在不冲突的情况下可以任意组合，得到新的方法实施例。
本申请所提供的几个产品实施例中所揭露的特征，在不冲突的情况下可以任意组合，得到新的产品实施例。
本申请所提供的几个方法或设备实施例中所揭露的特征，在不冲突的情况下可以任意组合，得到新的方法实施例或设备实施例。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。
工业实用性
本申请实施例中，首先确定当前块的待预测图像分量的第一参考像素集合；然后从第一参考像素集合中，确定参考像素子集；其中，参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；再利用参考像素子集，计算预测模型的模型参数；其中，预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理；这样，由于对第一参考像素集合进行筛选处理，可以去掉不重要的参考像素点或者存在异常的参考像素点，从而减少了第一参考像素集合中的像素个数，不仅可以降低计算复杂度和内存带宽，而且还可以提高预测模型的精确度；由于所述预测模型是用于通过所述模型参数实现对所述待预测图像分量的预测处理，从而提升了待预测图像分量的预测准确性，提高了视频图像的预测效率。

Claims (38)

  1. 一种图像分量预测方法，应用于编码器或解码器，所述方法包括：
    确定当前块的待预测图像分量的第一参考像素集合；
    从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
    利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
  2. 根据权利要求1所述的方法，其中，所述确定当前块的待预测图像分量的第一参考像素集合，包括：
    在所述当前块之外，获取与所述当前块的至少一个边相邻的参考像素；其中，所述当前块的至少一个边包括下述至少之一：上侧边、左侧边、右上侧边和左下侧边；
    根据获取的参考像素，得到所述第一参考像素集合。
  3. 根据权利要求1所述的方法，其中，所述确定当前块的待预测图像分量的第一参考像素集合，包括：
    在重建块之内，获取所述重建块的至少一个边相邻的参考像素；其中，所述重建块为与所述当前块相邻且已完成编码重构建的图像块，所述重建块的至少一个边包括：下侧边、右侧边、或者下侧边和右侧边；
    根据获取的参考像素，得到所述第一参考像素集合。
  4. 根据权利要求2或3所述的方法，其中，所述根据所述第一参考像素集合，确定参考像素子集，包括：
    基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置；
    从所述第一参考像素集合中选取与所述候选位置对应的参考像素，将选取得到的参数像素组成所述参考像素子集。
  5. 根据权利要求4所述的方法，其中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，包括：
    基于所述至少一个边相邻的参考像素对应的像素位置，确定所述候选位置。
  6. 根据权利要求4所述的方法，其中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，包括：
    基于所述至少一个边相邻的参考像素对应的图像分量强度值，确定所述候选位置。
  7. 根据权利要求4所述的方法，其中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，包括：
    基于所述至少一个边相邻的参考像素对应的像素位置和图像分量强度值，确定所述候选位置。
  8. 根据权利要求4所述的方法，其中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，包括：
    确定预设候选像素数；其中，所述预设候选像素数表示从所述至少一个边相邻的参考像素中所采样的像素数量；
    根据所述预设候选像素数和所述至少一个边的长度，确定所述候选位置；其中，所述至少一个边的长度等于所述至少一个边所包含的像素数量。
  9. 根据权利要求8所述的方法，其中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，包括：
    根据所述预设候选像素数和所述至少一个边的长度，计算第一采样间隔；
    从所述至少一个边中确定一基准点，按照所述第一采样间隔确定所述候选位置。
  10. 根据权利要求9所述的方法，其中，在所述计算第一采样间隔之后，所述方法还包括：
    对所述第一采样间隔进行调整，得到第二采样间隔；
    基于所述基准点，按照所述第二采样间隔确定所述候选位置。
  11. 根据权利要求10所述的方法，其中，所述得到第二采样间隔之后，所述方法还包括：
    基于所述基准点，按照所述第一采样间隔确定所述基准点一侧对应的候选位置，按照所述第二采样间隔确定所述基准点另一侧对应的候选位置。
  12. 根据权利要求8至11任一项所述的方法，其中，所述基于所述当前块或所述重建块的至少一个边，确定候选像素的候选位置，包括：
    确定所述至少一个边对应的预设跳过像素数K，其中，K为大于或等于1的正整数；
    从所述至少一个边的起始位置和/或末端位置开始，确定K个待跳过像素点对应的位置；
    基于所述K个待跳过像素点对应的位置，从所述至少一个边的起始位置和/或末端位置开始连续跳过K个待跳过像素点，得到至少一个新边；
    基于所述至少一个新边以及所述预设候选像素数，确定所述候选位置。
  13. 根据权利要求1至12任一项所述的方法，其中，所述利用所述参考像素子集，计算预测模型的模型参数，包括：
    基于所述参考像素子集，获取所述当前块对应的待预测图像分量的相邻像素重建值和参考块对应的待预测图像分量的相邻像素重建值；其中，所述当前块位于第N帧视频图像，所述参考块位于第N-1帧视频图像；
    根据所述当前块对应的待预测图像分量的相邻像素重建值以及所述参考块对应的待预测图像分量的相邻像素重建值，计算得到所述模型参数。
  14. 根据权利要求1所述的方法，其中，在所述利用所述参考像素子集，计算预测模型的模型参数之后，所述方法还包括：
    根据所述模型参数，构建所述预测模型；
    通过所述预测模型对所述当前块的待预测图像分量进行预测处理，得到所述待预测图像分量对应的预测值。
  15. 根据权利要求1所述的方法，其中，所述确定当前块的待预测图像分量的第一参考像素集合，包括：
    将所述当前块的一个或多个第一相邻像素作为所述第一参考像素集合；其中，所述第一相邻像素是位于与所述当前块竖直边、与所述当前块水平边、或者与所述当前块竖直边和水平边相邻的像素。
  16. 根据权利要求15所述的方法，其中，所述方法还包括：
    若所述第一相邻像素位于所述当前块外，则确定所述当前块竖直边是所述当前块外左相邻列，所述当前块水平边是所述当前块外上相邻行。
  17. 根据权利要求15所述的方法，其中，所述方法还包括：
    若所述第一相邻像素位于所述当前块内，则确定所述当前块竖直边是所述当前块内右侧边列，所述当前块水平边是所述当前块内下侧边行。
  18. 根据权利要求15所述的方法，其中，所述确定参考像素子集，包括：
    在所述当前块的边上，确定所述候选像素的候选位置，其中，所述当前块的边是所述当前块的竖直边或水平边；
    从所述第一参考像素集合中选择位于所述候选位置的像素，将所选择的像素组成所述参考像素子集。
  19. 根据权利要求18所述的方法，其中，所述确定候选像素的候选位置，包括：
    根据所述第一参考像素集合中像素的位置，确定所述候选像素的候选位置。
  20. 根据权利要求18所述的方法，其中，所述确定候选像素的候选位置，包括：
    根据所述第一参考像素集合中像素的图像分量强度，确定所述候选像素的候选位置。
  21. 根据权利要求18所述的方法，其中，所述确定候选像素的候选位置，包括：
    根据所述第一参考像素集合中像素的位置和图像分量强度，确定所述候选像素的候选位置。
  22. 根据权利要求18所述的方法，其中，所述确定所述候选像素的候选位置，包括：
    确定预设候选像素数，其中，所述预设候选像素数指示从所述当前块的边上选取的像素数；
    根据所述第一预设像素数和所述当前块的边的长度，确定所述候选像素的候选位置；其中，所述当前块的边的长度等于所述第一参考像素集合中位于所述当前块的边上的参考像素的数量。
  23. 根据权利要求22所述的方法，其中，所述确定所述候选像素的候选位置，包括：
    根据所述当前块的边的长度和所述预设候选像素数，计算第一采样间隔。
  24. 根据权利要求23所述的方法，其中，所述确定候选像素的候选位置，包括：
    对所述第一采样间隔进行调整，得到第二采样间隔。
  25. 根据权利要求23所述的方法，其中，在所述计算第一采样间隔之后，所述方法还包括：
    在所述当前块的边上确定基准点，从所述基准点起，以所述第一采样间隔确定所述当前块的边上的候选位置。
  26. 根据权利要求23所述的方法，其中，在所述计算第一采样间隔之后，所述方法还包括：
    在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点两侧的候选位置。
  27. 根据权利要求24所述的方法，其中，在所述得到第二采样间隔之后，所述方法还包括：
    在所述当前块的边上确定基准点，从所述基准点起，以所述第二采样间隔确定所述当前块的边上的 候选位置。
  28. 根据权利要求24所述的方法，其中，在所述得到第二采样间隔之后，所述方法还包括：
    在所述当前块的边上确定基准点，以所述第二采样间隔确定所述基准点两侧的候选位置。
  29. 根据权利要求24所述的方法，其中，在所述得到第二采样间隔之后，所述方法还包括：
    在所述当前块的边上确定基准点，以所述第一采样间隔确定所述基准点一侧对应的候选位置，以所述第二采样间隔确定所述基准点另一侧对应的候选位置。
  30. 根据权利要求23至29中任一项所述方法，其中，所述方法还包括：
    确定所述当前块的边的预设跳过像素数K，其中，K是非负整数；
    从所述当前块的边的端位置起，将第K个像素位置设置为所述基准点；
    其中，所述当前块的边的端位置是所述当前块的边的起始像素位置或末端像素位置。
  31. 根据权利要求1所述的方法，其中，所述利用所述参考像素子集，计算预测模型的模型参数，包括：
    利用所述参考像素子集中的参考像素和所述当前块的参考块的位于所述参考像素子集中参考像素的同位置的像素，计算预测模型的模型参数；
    其中，所述参考像素子集中参考像素的同位置的像素是位于所述参考块所在图像中、与参考块之间的相对位置与所述第二参考像素集合中的参考像素与所述当前块之间相对位置相同的像素。
  32. 根据权利要求1所述的方法，其中，在所述计算预测模型的模型参数之后，所述方法还包括：
    根据所述预测模型和所述当前块的参考块，计算所述当前块的待预测图像分量的预测值。
  33. 根据权利要求31或32所述的方法，其中，所述方法还包括：
    所述参考块是所述当前块的帧间预测参数指示的图像块。
  34. 一种编码器，所述编码器包括第一确定单元和第一计算单元，其中，
    所述第一确定单元，配置为确定当前块的待预测图像分量的第一参考像素集合；
    所述第一确定单元，还配置为从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
    所述第一计算单元，配置为利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
  35. 一种编码器，所述编码器包括第一存储器和第一处理器，其中，
    所述第一存储器，用于存储能够在所述第一处理器上运行的计算机程序；
    所述第一处理器，用于在运行所述计算机程序时，执行如权利要求1至33任一项所述的方法。
  36. 一种解码器，所述解码器包括第二确定单元和第二计算单元，其中，
    所述第二确定单元，配置为确定当前块的待预测图像分量的第一参考像素集合；
    所述第二确定单元，还配置为从所述第一参考像素集合中，确定参考像素子集；其中，所述参考像素子集包含从所述第一参考像素集合中选择的一个或多个候选像素；
    所述第二计算单元，配置为利用所述参考像素子集，计算预测模型的模型参数；其中，所述预测模型用于对所述当前块的待预测图像分量进行跨分量预测处理。
  37. 一种解码器，所述解码器包括第二存储器和第二处理器，其中，
    所述第二存储器，用于存储能够在所述第二处理器上运行的计算机程序；
    所述第二处理器，用于在运行所述计算机程序时，执行如权利要求1至33任一项所述的方法。
  38. 一种计算机存储介质，其中，所述计算机存储介质存储有图像预测程序，所述图像预测程序被第一处理器或第二处理器执行时实现如权利要求1至33任一项所述的方法。
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