Cross-component-based correction for intra predictor of chroma block

Abstract

A cross-component-based correction technique for an intra predictor of a chroma block is disclosed. A video encoder or a video decoder may: generate first chroma prediction values for chroma samples of a chroma block by using an intra prediction technique; derive a cross-component model on the basis of luma prediction values for luma samples of a luma block corresponding to the chroma block and the first chroma prediction values; and generate second chroma prediction values for the chroma samples of the chroma block from reconstructed values for the luma samples by using the cross-component model. The video encoder or the video decoder may generate modified chroma prediction values for the chroma samples of the chroma block on the basis of a weighted average of the first chroma prediction values and the second chroma prediction values, and encode or decode the chroma block on the basis of the modified chroma prediction values.

Description

Cross-component-based correction for intra predictors of chroma blocks

[0001] The present disclosure relates to encoding and decoding of video data, and more particularly, to a technique for correcting an intra predictor of a chroma block based on a correlation between a chroma predictor and a luma predictor.

[0002] The content described below merely provides background information related to the present embodiment and does not constitute prior art.

[0003] Since video data has a large amount of data compared to voice data or still image data, it requires a lot of hardware resources, including memory, to store or transmit it without processing for compression.

[0004] Therefore, when storing or transmitting video data, the encoder compresses the video data and stores or transmits it, and the decoder receives the compressed video data, decompresses it, and plays it back. These video compression technologies include H.264 / AVC, HEVC (High Efficiency Video Coding), and VVC (Versatile Video Coding), which improves encoding efficiency by about 30% compared to HEVC.

[0005] However, as the size, resolution, and frame rate of images are gradually increasing, and the amount of data that needs to be encoded is also increasing, a new compression technology that has better encoding efficiency and better image quality improvement than existing compression technologies is required.

[0006] The present disclosure proposes a method for correcting prediction values ​​of chroma samples based on a correlation between prediction values ​​of chroma samples and prediction values ​​of corresponding luma samples when an intra prediction technique is used in a chroma block.

[0007] One aspect of the present disclosure provides a method of decoding video data. The method comprises the steps of: generating first chroma prediction values ​​for chroma samples of a chroma block using an intra prediction technique; deriving a cross-component model based on luma prediction values ​​for luma samples of a luma block corresponding to the chroma block and the first chroma prediction values; generating second chroma prediction values ​​for the chroma samples of the chroma block from reconstructed values ​​for the luma samples using the cross-component model; generating modified chroma prediction values ​​for the chroma samples of the chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values; and generating reconstructed values ​​for the chroma samples of the chroma block by adding chroma residual values ​​to the modified chroma prediction values.

[0008] Another aspect of the present disclosure provides a method of encoding video data. The method comprises the steps of: generating first chroma prediction values ​​for chroma samples of a chroma block using an intra prediction technique; deriving a cross-component model based on luma prediction values ​​for luma samples of a luma block corresponding to the chroma block and the first chroma prediction values; generating second chroma prediction values ​​for the chroma samples of the chroma block from reconstructed values ​​for the luma samples using the cross-component model; generating modified chroma prediction values ​​for the chroma samples of the chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values; and encoding residual data representing a difference between the modified chroma prediction values ​​and original sample values ​​of the chroma block.

[0009] Another aspect of the present disclosure discloses a method for providing video data to a video decoding device. The method includes encoding the video data into a bitstream and transmitting the bitstream to the video decoding device. The encoding of the video data into the bitstream includes generating first chroma prediction values ​​for chroma samples of a chroma block using an intra prediction technique; deriving a cross-component model based on the first chroma prediction values ​​and luma prediction values ​​for luma samples of a luma block corresponding to the chroma block; generating second chroma prediction values ​​for chroma samples of the chroma block from reconstructed values ​​for the luma samples using the cross-component model; generating modified chroma prediction values ​​for chroma samples of the chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values; and encoding residual data representing a difference between the modified chroma prediction values ​​and original sample values ​​of the chroma block.

[0010] FIG. 1 is an exemplary block diagram of an image encoding device capable of implementing the techniques of the present disclosure.

[0011] Figure 2 is a drawing for explaining a method of dividing a block using the QTBTTT (QuadTree plus BinaryTree TernaryTree) structure.

[0012] FIGS. 3A and 3B are diagrams illustrating multiple intra prediction modes, including wide-angle intra prediction modes.

[0013] Figure 4 is a conceptual diagram illustrating the surrounding blocks of the current block.

[0014] FIG. 5 is an exemplary block diagram of an image decoding device capable of implementing the techniques of the present disclosure.

[0015] Figure 6 is a conceptual diagram illustrating an example of the spatial part of a convolution filter.

[0016] Figure 7 is a conceptual diagram illustrating an exemplary reference domain used to derive CCCM filter coefficients.

[0017] Figure 8 is a conceptual diagram illustrating spatial samples for GL-CCCM.

[0018] Figure 9 is a conceptual diagram illustrating multiple downsampling filters that can be applied to a luma block.

[0019] Figure 10 is a conceptual diagram illustrating six non-downsampled luma samples corresponding to chroma samples (C) to be predicted in CCCM-ND mode.

[0020] Figure 11 is a conceptual diagram illustrating an exemplary reference area for BVG-CCCM.

[0021] Figure 12 is a conceptual diagram illustrating five locations within a co-located luma block region for a chroma block.

[0022] FIG. 13 is a conceptual diagram illustrating a process of correcting chroma prediction values ​​using a cross-component model and deriving reconstructed values ​​of a chroma block using the corrected chroma prediction values, according to one embodiment of the present disclosure.

[0023] FIG. 14 is a conceptual diagram illustrating spatial luma samples corresponding to predicted chroma sample locations for 4:2:0, 4:2:2, and 4:4:4 color formats, according to one embodiment of the present disclosure.

[0024] FIG. 15 is a conceptual diagram illustrating examples in which some areas within a chroma block are excluded from a predictor correction process depending on the angle of the intra prediction mode, according to one embodiment of the present disclosure.

[0025] FIG. 16 is a flowchart illustrating a method by which a video decoder determines a cross-component model to use to correct a chroma predictor, according to one embodiment of the present disclosure.

[0026] Figure 17 is a conceptual diagram explaining the surrounding blocks adjacent to the current block.

[0027] FIG. 18 is a flowchart illustrating a method of coding video data according to one embodiment of the present disclosure.

[0028] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to exemplary drawings. When designating components in each drawing, it should be noted that, where possible, identical components are given the same reference numerals, even if they appear in different drawings. Furthermore, in describing the present embodiments, detailed descriptions of related known structures or functions will be omitted if they are deemed to obscure the gist of the present embodiments.

[0029] FIG. 1 is an exemplary block diagram of an image encoding device capable of implementing the techniques of the present disclosure. Hereinafter, the image encoding device and its subcomponents will be described with reference to the illustration in FIG. 1.

[0030] The video encoding device may be configured to include a picture segmentation unit (110), a prediction unit (120), a subtractor (130), a transformation unit (140), a quantization unit (145), a reordering unit (150), an entropy encoding unit (155), an inverse quantization unit (160), an inverse transformation unit (165), an adder (170), a loop filter unit (180), and a memory (190).

[0031] Each component of the video encoding device may be implemented in hardware, software, or a combination of hardware and software. Furthermore, the functions of each component may be implemented in software, with a microprocessor executing the software functions corresponding to each component.

[0032] A single image (video) is composed of one or more sequences containing multiple pictures. Each picture is divided into multiple regions, and encoding is performed for each region. For example, a single picture is divided into one or more tiles and / or slices. Here, one or more tiles can be defined as a tile group. Each tile or slice is divided into one or more Coding Tree Units (CTUs). Each CTU is then divided into one or more Coding Units (CUs) by a tree structure. Information applied to each CU is encoded as the syntax of the CU, and information commonly applied to CUs included in a CTU is encoded as the syntax of the CTU. In addition, information commonly applied to all blocks within a single slice is encoded as the syntax of the slice header, and information applied to all blocks constituting one or more pictures is encoded in the Picture Parameter Set (PPS) or the picture header. Furthermore, information commonly referenced by multiple pictures is encoded in a Sequence Parameter Set (SPS). And, information commonly referenced by one or more SPS is encoded in a Video Parameter Set (VPS). In addition, information commonly applied to one tile or tile group may be encoded as syntax of a tile or tile group header. Syntaxes included in an SPS, PPS, slice header, tile or tile group header may be referred to as high level syntax.

[0033] The picture segmentation unit (110) determines the size of the CTU. Information about the size of the CTU (CTU size) is encoded as the syntax of SPS or PPS and transmitted to the image decoding device.

[0034] The picture segmentation unit (110) divides each picture constituting an image into a plurality of CTUs having a predetermined size, and then recursively divides the CTUs using a tree structure. A leaf node in the tree structure becomes a CU, which is a basic unit of encoding.

[0035] The tree structure may be a QuadTree (QT) in which an upper node (or parent node) is divided into four lower nodes (or child nodes) of the same size, a BinaryTree (BT) in which an upper node is divided into two lower nodes, or a TernaryTree (TT) in which an upper node is divided into three lower nodes in a 1:2:1 ratio, or a structure that mixes two or more of the QT structures, BT structures, and TT structures. For example, a QTBT (QuadTree plus BinaryTree) structure may be used, or a QTBTTT (QuadTree plus BinaryTree TernaryTree) structure may be used. Here, BTTT may be combined and referred to as a MTT (Multiple-Type Tree).

[0036] Figure 2 is a drawing for explaining a method of dividing a block using the QTBTTT structure.

[0037] As illustrated in FIG. 2, a CTU may first be split into a QT structure. The quadtree splitting may be repeated until the size of the splitting block reaches the minimum block size (MinQTSize) of the leaf node allowed in the QT. A first flag (QT_split_flag) indicating whether each node of the QT structure is split into four nodes of the lower layer is encoded by the entropy encoding unit (155) and signaled to the image decoding device. If the leaf node of the QT is not larger than the maximum block size (MaxBTSize) of the root node allowed in the BT, it may be further split into one or more of the BT structure or the TT structure. There may be multiple splitting directions in the BT structure and / or the TT structure. For example, there may be two directions in which the block of the corresponding node is split horizontally and two directions in which the block is split vertically. As illustrated in FIG. 2, when MTT splitting begins, a second flag (mtt_split_flag) indicating whether nodes have been split, and if splitting has occurred, a flag indicating the splitting direction (vertical or horizontal) and / or a flag indicating the splitting type (Binary or Ternary) are encoded by the entropy encoding unit (155) and signaled to the image decoding device.

[0038] Alternatively, before encoding the first flag (QT_split_flag) indicating whether each node is split into four nodes of a lower layer, a CU split flag (split_cu_flag) indicating whether the node is split may be encoded. If the CU split flag (split_cu_flag) value indicates that the node is not split, the block of the corresponding node becomes a leaf node in the split tree structure and becomes a CU (coding unit), which is a basic unit of encoding. If the CU split flag (split_cu_flag) value indicates that the node is split, the video encoding device starts encoding from the first flag in the above-described manner.

[0039] As another example of a tree structure, when QTBT is used, there may be two types: a type that horizontally splits the block of the corresponding node into two blocks of the same size (i.e., symmetric horizontal splitting) and a type that vertically splits it (i.e., symmetric vertical splitting). A split flag (split_flag) indicating whether each node of the BT structure is split into blocks of a lower layer and split type information indicating the type of split are encoded by the entropy encoding unit (155) and transmitted to the image decoding device. Meanwhile, there may additionally be a type that splits the block of the corresponding node into two blocks of an asymmetrical shape. The asymmetric shape may include a shape that splits the block of the corresponding node into two rectangular blocks with a size ratio of 1:3, or a shape that splits the block of the corresponding node in a diagonal direction.

[0040] A CU can have various sizes depending on the QTBT or QTBTTT partitioning from the CTU. Hereinafter, the block corresponding to the CU to be encoded or decoded (i.e., the leaf node of the QTBTTT) is referred to as the "current block." Depending on the QTBTTT partitioning employed, the current block may be rectangular as well as square.

[0041] The prediction unit (120) predicts the current block and generates a prediction block. The prediction unit (120) includes an intra prediction unit (122) and an inter prediction unit (124).

[0042] In general, each current block within a picture can be predictively coded. Prediction of the current block can typically be performed using either intra-prediction (using data from the picture containing the current block) or inter-prediction (using data from a picture coded before the picture containing the current block). Inter-prediction encompasses both unidirectional and bidirectional prediction.

[0043] The intra prediction unit (122) predicts pixels within the current block using pixels (reference pixels) located around the current block within the current picture including the current block. There are multiple intra prediction modes depending on the prediction direction. For example, as shown in Fig. 3a, the multiple intra prediction modes may include two non-directional modes including the Planar mode and the DC mode, and 65 directional modes. The surrounding pixels to be used and the calculation formula are defined differently depending on each prediction mode.

[0044] For efficient directional prediction for a rectangular current block, directional modes (intra prediction modes 67 to 80 and -1 to -14) indicated by dotted arrows in Fig. 3b may be additionally used. These may be referred to as "wide-angle intra-prediction modes." In Fig. 3b, the arrows point to corresponding reference samples used for prediction, and do not indicate the prediction direction. The prediction direction is opposite to the direction indicated by the arrows. Wide-angle intra-prediction modes are modes that perform prediction in the opposite direction of a specific directional mode without additional bit transmission when the current block is rectangular. At this time, among the wide-angle intra-prediction modes, some wide-angle intra-prediction modes available for the current block may be determined based on the ratio of the width and height of the rectangular current block. For example, wide-angle intra prediction modes (intra prediction modes 67 to 80) having an angle less than 45 degrees are available when the current block is a rectangular shape whose height is smaller than its width, and wide-angle intra prediction modes (intra prediction modes -1 to -14) having an angle greater than -135 degrees are available when the current block is a rectangular shape whose width is larger than its height.

[0045] The intra prediction unit (122) can determine an intra prediction mode to be used to encode the current block. In some examples, the intra prediction unit (122) can encode the current block using multiple intra prediction modes and select an appropriate intra prediction mode to be used from the tested modes. For example, the intra prediction unit (122) can calculate bit-rate distortion values ​​using rate-distortion analysis for multiple tested intra prediction modes and select an intra prediction mode with the best bit-rate distortion characteristics among the tested modes.

[0046] The intra prediction unit (122) selects one intra prediction mode from among multiple intra prediction modes and predicts the current block using surrounding pixels (reference pixels) and an operation formula determined according to the selected intra prediction mode. Information about the selected intra prediction mode is encoded by the entropy encoding unit (155) and transmitted to the image decoding device.

[0047] The inter prediction unit (124) generates a prediction block for the current block using a motion compensation process. The inter prediction unit (124) searches for a block most similar to the current block within reference pictures that were encoded and decoded before the current picture, and generates a prediction block for the current block using the searched block. Then, a motion vector (MV) corresponding to the displacement between the current block within the current picture and the prediction block within the reference picture is generated. Generally, motion estimation is performed on the luma component, and the motion vector calculated based on the luma component is used for both the luma component and the chroma component. The motion information including information on the reference picture used to predict the current block and information on the motion vector is encoded by the entropy encoding unit (155) and transmitted to the image decoding device.

[0048] The inter prediction unit (124) may perform interpolation on a reference picture or a reference block to improve prediction accuracy. That is, subsamples between two consecutive integer samples are interpolated by applying filter coefficients to a plurality of consecutive integer samples including the two integer samples. When a process of searching for a block most similar to the current block is performed on the interpolated reference picture, the motion vector can be expressed up to a precision in decimal units rather than a precision in integer sample units. The precision or resolution of the motion vector can be set differently for each target region to be encoded, such as a slice, tile, CTU, CU, etc. When such adaptive motion vector resolution (AMVR) is applied, information on the motion vector resolution to be applied to each target region must be signaled for each target region. For example, when the target region is a CU, information on the motion vector resolution applied to each CU is signaled. Information on the motion vector resolution may be information indicating the precision of a differential motion vector, which will be described later.

[0049] Meanwhile, the inter prediction unit (124) can perform inter prediction using bi-prediction. In the case of bi-prediction, two reference pictures and two motion vectors indicating the block position most similar to the current block within each reference picture are used. The inter prediction unit (124) selects a first reference picture and a second reference picture from reference picture list 0 (referred to as RefPicList0 or simply L0) and reference picture list 1 (referred to as RefPicList1 or simply L1), respectively, and searches for a block similar to the current block within each reference picture to generate a first reference block and a second reference block. Then, the first reference block and the second reference block are averaged or weighted averaged to generate a prediction block for the current block. Then, motion information including information on two reference pictures used to predict the current block and information on two motion vectors is transmitted to the entropy encoding unit (155). Here, reference picture list 0 may be composed of pictures that are before the current picture in display order among the restored pictures, and reference picture list 1 may be composed of pictures that are after the current picture in display order among the restored pictures. However, this is not necessarily limited to this, and restored pictures that are after the current picture in display order may be additionally included in reference picture list 0, and conversely, restored pictures that are before the current picture may be additionally included in reference picture list 1.

[0050] Various methods can be used to minimize the number of bits required to encode motion information.

[0051] For example, if the reference picture and motion vector of the current block are identical to those of a neighboring block, the motion information of the current block can be transmitted to the image decoding device by encoding information that can identify the neighboring block. This method is called 'merge mode'.

[0052] In merge mode, the inter prediction unit (124) selects a predetermined number of merge candidate blocks (hereinafter referred to as 'merge candidates') from the surrounding blocks of the current block.

[0053] As the surrounding blocks for deriving merge candidates, all or part of the left block (A0), the lower left block (A1), the upper block (B0), the upper right block (B1), and the upper left block (B2) adjacent to the current block within the current picture may be used, as illustrated in FIG. 4. In addition, a block located within a reference picture (which may or may not be the same as the reference picture used to predict the current block) other than the current picture in which the current block is located may be used as a merge candidate. For example, a block co-located with the current block within the reference picture or blocks adjacent to the block at the co-located block may be additionally used as a merge candidate. If the number of merge candidates selected by the method described above is less than a preset number, a 0 vector is added to the merge candidates.

[0054] The inter prediction unit (124) uses these surrounding blocks to construct a merge list containing a predetermined number of merge candidates. Among the merge candidates included in the merge list, the merge candidate to be used as motion information of the current block is selected and merge index information for identifying the selected candidate is generated. The generated merge index information is encoded by the entropy encoding unit (155) and transmitted to the video decoding device.

[0055] Merge Skip mode is a special case of merge mode. After quantization, when all transform coefficients for entropy encoding are close to zero, only neighboring block selection information is transmitted without transmitting residual signals. By utilizing merge skip mode, relatively high encoding efficiency can be achieved for low-motion images, still images, and screen content images.

[0056] Hereinafter, merge mode and merge skip mode are collectively referred to as merge / skip mode.

[0057] Another method for encoding motion information is Advanced Motion Vector Prediction (AMVP) mode.

[0058] In AMVP mode, the inter prediction unit (124) derives predicted motion vector candidates for the motion vector of the current block using neighboring blocks of the current block. As neighboring blocks used to derive predicted motion vector candidates, all or some of the left block (A0), the lower left block (A1), the upper block (B0), the upper right block (B1), and the upper left block (B2) adjacent to the current block in the current picture as shown in FIG. 4 may be used. In addition, a block located in a reference picture (which may or may not be the same as the reference picture used to predict the current block) other than the current picture in which the current block is located may be used as the neighboring block used to derive predicted motion vector candidates. For example, a block co-located with the current block in the reference picture or blocks adjacent to the block in the co-located block may be used. If the number of motion vector candidates is less than a preset number by the method described above, a 0 vector is added to the motion vector candidates.

[0059] The inter prediction unit (124) derives predicted motion vector candidates using the motion vectors of these surrounding blocks, and determines a predicted motion vector for the motion vector of the current block using the predicted motion vector candidates. Then, the predicted motion vector is subtracted from the motion vector of the current block to produce a differential motion vector.

[0060] The predicted motion vector can be obtained by applying a predefined function (e.g., median, mean, etc.) to the predicted motion vector candidates. In this case, the image decoding device also knows the predefined function. In addition, since the surrounding blocks used to derive the predicted motion vector candidates are blocks that have already been encoded and decoded, the image decoding device also already knows the motion vectors of the surrounding blocks. Therefore, the image encoding device does not need to encode information to identify the predicted motion vector candidates. Therefore, in this case, information about the differential motion vector and information about the reference picture used to predict the current block are encoded.

[0061] Alternatively, the predicted motion vector can be determined by selecting one of the predicted motion vector candidates. In this case, information for identifying the selected predicted motion vector candidate is additionally encoded, along with information about the differential motion vector and the reference picture used to predict the current block.

[0062] The subtractor (130) subtracts the prediction block generated by the intra prediction unit (122) or inter prediction unit (124) from the current block to generate a residual block.

[0063] The transformation unit (140) transforms residual signals within a residual block having pixel values ​​in a spatial domain into transform coefficients in a frequency domain. The transformation unit (140) may transform the residual signals within the residual block using the entire size of the residual block as a transformation unit, or may divide the residual block into a plurality of sub-blocks and use the sub-blocks as transformation units to perform the transformation. Alternatively, the residual signals may be transformed using only the transformation domain sub-block as a transformation unit by dividing the sub-blocks into two sub-blocks, that is, a transformation domain and a non-transform domain. Here, the transformation domain sub-block may be one of two rectangular blocks having a size ratio of 1:1 with respect to the horizontal axis (or vertical axis). In this case, a flag (cu_sbt_flag) indicating that only a sub-block has been converted, directionality (vertical / horizontal) information (cu_sbt_horizontal_flag), and / or position information (cu_sbt_pos_flag) are encoded by the entropy encoding unit (155) and signaled to the image decoding device. In addition, the size of the conversion area sub-block may have a size ratio of 1:3 with respect to the horizontal axis (or vertical axis), and in this case, a flag (cu_sbt_quad_flag) distinguishing the corresponding division is additionally encoded by the entropy encoding unit (155) and signaled to the image decoding device.

[0064] Meanwhile, the transformation unit (140) can individually perform transformations on the residual block in the horizontal and vertical directions. For the transformation, various types of transformation functions or transformation matrices can be used. For example, a pair of transformation functions for horizontal transformation and vertical transformation can be defined as a Multiple Transform Set (MTS). The transformation unit (140) can select one transformation function pair with the best transformation efficiency among the MTS and transform the residual block in the horizontal and vertical directions, respectively. Information (mts_idx) on the transformation function pair selected among the MTS is encoded by the entropy encoding unit (155) and signaled to the image decoding device.

[0065] The quantization unit (145) quantizes the transform coefficients output from the transform unit (140) using quantization parameters and outputs the quantized transform coefficients to the entropy encoding unit (155). The quantization unit (145) may directly quantize a related residual block without transformation for a certain block or frame. The quantization unit (145) may also apply different quantization coefficients (scaling values) according to the positions of the transform coefficients within the transform block. The quantization matrix applied to the quantized transform coefficients arranged in two dimensions may be encoded and signaled to an image decoding device.

[0066] The rearrangement unit (150) can perform rearrangement of coefficient values ​​for quantized residual values.

[0067] The reordering unit (150) can change a two-dimensional coefficient array into a one-dimensional coefficient sequence by using coefficient scanning. For example, the reordering unit (150) can output a one-dimensional coefficient sequence by scanning from the DC coefficient to the coefficients of the high-frequency region by using a zig-zag scan or a diagonal scan. Depending on the size of the transformation unit and the intra prediction mode, a vertical scan that scans the two-dimensional coefficient array in the column direction or a horizontal scan that scans the two-dimensional block-shaped coefficients in the row direction may be used instead of the zig-zag scan. That is, depending on the size of the transformation unit and the intra prediction mode, the scanning method to be used may be determined among the zig-zag scan, the diagonal scan, the vertical scan, and the horizontal scan.

[0068] The entropy encoding unit (155) generates a bitstream by encoding a sequence of one-dimensional quantized transform coefficients output from the rearrangement unit (150) using various encoding methods such as CABAC (Context-based Adaptive Binary Arithmetic Code) and Exponential Golomb.

[0069] In addition, the entropy encoding unit (155) encodes information related to block division, such as CTU size, CU division flag, QT division flag, MTT division type, and MTT division direction, so that the image decoding device can divide the block in the same manner as the image encoding device. In addition, the entropy encoding unit (155) encodes information about the prediction type indicating whether the current block is encoded by intra prediction or inter prediction, and encodes intra prediction information (i.e., information about the intra prediction mode) or inter prediction information (information about the encoding mode of motion information (merge mode or AMVP mode), a merge index in the case of the merge mode, and a reference picture index and a differential motion vector in the case of the AMVP mode) according to the prediction type. In addition, the entropy encoding unit (155) encodes information related to quantization, that is, information about quantization parameters and information about a quantization matrix.

[0070] The inverse quantization unit (160) inversely quantizes the quantized transform coefficients output from the quantization unit (145) to generate transform coefficients. The inverse transform unit (165) transforms the transform coefficients output from the inverse quantization unit (160) from the frequency domain to the spatial domain to restore the residual block.

[0071] An adder (170) adds the restored residual block and the predicted block generated by the prediction unit (120) to restore the current block. The pixels within the restored current block are used as reference pixels when intra-predicting the next block.

[0072] The loop filter unit (180) performs filtering on restored pixels to reduce blocking artifacts, ringing artifacts, blurring artifacts, etc. that occur due to block-based prediction and transformation / quantization. The loop filter unit (180) may include all or part of a deblocking filter (182), a sample adaptive offset (SAO) filter (184), and an adaptive loop filter (ALF, 186) as an in-loop filter.

[0073] The deblocking filter (182) filters the boundaries between restored blocks to remove blocking artifacts caused by block-based encoding / decoding, and the SAO filter (184) and the ALF (186) perform additional filtering on the deblocking-filtered image. The SAO filter (184) and the ALF (186) are filters used to compensate for the differences between restored pixels and original pixels caused by lossy coding. The SAO filter (184) improves not only subjective image quality but also encoding efficiency by applying an offset in units of CTUs. In contrast, the ALF (186) performs block-based filtering, and compensates for distortion by applying different filters by distinguishing the edges and degrees of variation of the corresponding block. Information on filter coefficients to be used in the ALF can be encoded and signaled to an image decoding device.

[0074] The restored blocks filtered through the deblocking filter (182), SAO filter (184), and ALF (186) are stored in the memory (190). When all blocks within a picture are restored, the restored picture can be used as a reference picture for inter-predicting blocks within a picture to be encoded later.

[0075] The video encoding device can store the bitstream of encoded video data on a non-transitory storage medium or transmit it to the video decoding device using a communication network.

[0076] FIG. 5 is an exemplary block diagram of an image decoding device capable of implementing the techniques of the present disclosure. Hereinafter, the image decoding device and its subcomponents will be described with reference to FIG. 5.

[0077] The video decoding device may be configured to include an entropy decoding unit (510), a rearrangement unit (515), an inverse quantization unit (520), an inverse transformation unit (530), a prediction unit (540), an adder (550), a loop filter unit (560), and a memory (570).

[0078] Similar to the video encoding device of FIG. 1, each component of the video decoding device may be implemented in hardware, software, or a combination of hardware and software. Furthermore, the functions of each component may be implemented in software, with a microprocessor executing the software functions corresponding to each component.

[0079] The entropy decoding unit (510) decodes the bitstream generated by the image encoding device to extract information related to block division, thereby determining the current block to be decoded, and extracts prediction information, information on residual signals, etc. required to restore the current block.

[0080] The entropy decoding unit (510) extracts information about the CTU size from the Sequence Parameter Set (SPS) or the Picture Parameter Set (PPS), determines the size of the CTU, and divides the picture into CTUs of the determined size. Then, the CTU is determined as the top layer of the tree structure, i.e., the root node, and the CTU is divided using the tree structure by extracting division information about the CTU.

[0081] For example, when splitting a CTU using the QTBTTT structure, first, the first flag (QT_split_flag) related to the splitting of QT is extracted, and each node is split into four nodes of the lower layer. Then, for the nodes corresponding to the leaf nodes of QT, the second flag (mtt_split_flag) related to the splitting of MTT and the split direction (vertical / horizontal) and / or split type (binary / ternary) information are extracted, and the corresponding leaf nodes are split into the MTT structure. Accordingly, each node below the leaf nodes of QT are split recursively into the BT or TT structure.

[0082] As another example, when splitting a CTU using the QTBTTT structure, the CU split flag (split_cu_flag) indicating whether the CU is split is first extracted, and if the block is split, the first flag (QT_split_flag) may be extracted. During the splitting process, each node may undergo zero or more repeated QT splits followed by zero or more repeated MTT splits. For example, a CTU may undergo an MTT split right away, or conversely, may undergo only multiple QT splits.

[0083] As another example, when splitting a CTU using the QTBT structure, the first flag (QT_split_flag) related to the splitting of QT is extracted, and each node is split into four nodes of the lower layer. Furthermore, for nodes corresponding to leaf nodes of QT, a split flag (split_flag) indicating whether to further split into BTs and splitting direction information are extracted.

[0084] Meanwhile, when the entropy decoding unit (510) determines the current block to be decoded by using the division of the tree structure, it extracts information on the prediction type indicating whether the current block is intra-predicted or inter-predicted. If the prediction type information indicates intra-prediction, the entropy decoding unit (510) extracts syntax elements for intra-prediction information (intra-prediction mode) of the current block. If the prediction type information indicates inter-prediction, the entropy decoding unit (510) extracts syntax elements for inter-prediction information, i.e., information indicating a motion vector and a reference picture referenced by the motion vector.

[0085] Additionally, the entropy decoding unit (510) extracts information about the quantized transform coefficients of the current block as information related to quantization and information about residual signals.

[0086] The rearrangement unit (515) can change the sequence of one-dimensional quantized transform coefficients entropy-decoded in the entropy decoding unit (510) back into a two-dimensional coefficient array (i.e., block) in the reverse order of the coefficient scanning performed by the image encoding device.

[0087] The inverse quantization unit (520) inversely quantizes the quantized transform coefficients and inversely quantizes the quantized transform coefficients using the quantization parameters. The inverse quantization unit (520) may also apply different quantization coefficients (scaling values) to the quantized transform coefficients arranged in two dimensions. The inverse quantization unit (520) may perform inverse quantization by applying a matrix of quantized coefficients (scaling values) from an image encoding device to a two-dimensional array of quantized transform coefficients.

[0088] The inverse transform unit (530) inversely transforms the inverse quantized transform coefficients from the frequency domain to the spatial domain to restore residual signals, thereby generating a residual block for the current block.

[0089] In addition, when the inverse transform unit (530) inversely transforms only a portion of a transform block (sub-block), it extracts a flag (cu_sbt_flag) indicating that only a sub-block of the transform block has been transformed, directionality (vertical / horizontal) information (cu_sbt_horizontal_flag) of the sub-block, and / or position information (cu_sbt_pos_flag) of the sub-block, and inversely transforms the transform coefficients of the corresponding sub-block from the frequency domain to the spatial domain to restore residual signals, and fills “0” values ​​with residual signals for areas that have not been inversely transformed, thereby generating a final residual block for the current block.

[0090] In addition, when MTS is applied, the inverse transform unit (530) determines a transform function or a transform matrix to be applied in the horizontal and vertical directions using MTS information (mts_idx) signaled from the image encoding device, and performs inverse transform on the transform coefficients within the transform block in the horizontal and vertical directions using the determined transform function.

[0091] The prediction unit (540) may include an intra prediction unit (542) and an inter prediction unit (544). The intra prediction unit (542) is activated when the prediction type of the current block is intra prediction, and the inter prediction unit (544) is activated when the prediction type of the current block is inter prediction.

[0092] The intra prediction unit (542) determines the intra prediction mode of the current block among a plurality of intra prediction modes from the syntax elements for the intra prediction mode extracted from the entropy decoding unit (510), and predicts the current block using reference pixels around the current block according to the intra prediction mode.

[0093] The inter prediction unit (544) uses the syntax elements for the inter prediction mode extracted from the entropy decoding unit (510) to determine the motion vector of the current block and the reference picture referenced by the motion vector, and predicts the current block using the motion vector and the reference picture.

[0094] An adder (550) adds the residual block output from the inverse transform unit (530) and the predicted block output from the inter prediction unit (544) or the intra prediction unit (542) to restore the current block. The pixels within the restored current block are used as reference pixels when intra-predicting a block to be decoded later.

[0095] The loop filter unit (560) may include a deblocking filter (562), an SAO filter (564), and an ALF (566) as in-loop filters. The deblocking filter (562) deblocks the boundaries between restored blocks to remove blocking artifacts caused by block-by-block decoding. The SAO filter (564) and the ALF (566) perform additional filtering on restored blocks after deblocking filtering to compensate for differences between restored pixels and original pixels caused by lossy coding. The filter coefficients of the ALF are determined using information about filter coefficients decoded from the non-stream.

[0096] The restored blocks filtered through the deblocking filter (562), SAO filter (564), and ALF (566) are stored in the memory (570). When all blocks within a picture are restored, the restored picture is used as a reference picture for inter-predicting blocks within a picture to be encoded later.

[0097] Now, improved coding techniques that can be performed by the aforementioned video encoder (e.g., the video encoding device illustrated in FIG. 1) or video decoder (e.g., the video decoding device illustrated in FIG. 5) are disclosed. The techniques of the present disclosure correct the intra predictor of a chroma block based on the correlation between the chroma predictor and the luma predictor.

[0098] This section describes the cross-component linear model (CCLM). To reduce cross-component redundancy, the CCLM prediction mode was introduced in VVC, where chroma samples are predicted based on reconstructed luma samples of the same CU using a linear model as follows.

[0099]

[0100] pred here C (i,j) represents the predicted chroma samples within the CU. represents the downsampled reconstructed luma samples of the same CU. The CCLM parameters (α, β) are derived from adjacent chroma samples and their corresponding downsampled luma samples.

[0101] VVC defines three CCLM modes, CCLM_LT, CCLM_L, and CCLM_T. These modes differ in the positions of the reconstructed adjacent samples used to derive the linear model parameters. The upper reconstructed adjacent samples (simply, the upper template) are used in CCLM_T mode, and the left reconstructed adjacent samples (simply, the left template) are used in CCLM_L mode. In both CCLM_T and CCLM_L modes, the upper template is extended with (W+H) samples, and the left template is extended with (H+W) samples to accommodate more samples. In CCLM_LT mode, both the upper and left reconstructed adjacent samples are used.

[0102] In the Enhanced Compression Model (ECM), various chroma prediction methods, such as CCLM, have been introduced that utilize the correlation between luma and chroma components. These prediction methods can be referred to as cross-component prediction (CCP).

[0103] First, we describe the Multi-model CCLM (MM-CCLM). The CCLM included in VVC is extended by adding three MM-CCLM modes. In each MM-CCLM mode, reconstructed neighboring luma samples are classified into two classes using a threshold value that is the average of the reconstructed neighboring luma samples. The linear model (i.e., parameters α and β) for each class is derived using the Least-Mean-Square (LMS) method. Furthermore, samples in the current luma block are also classified according to the same rules as those for neighboring luma samples.

[0104] The convolutional cross-component model (CCCM) is described. CCCM can be used for chroma prediction. CCCM is applied to predict chroma samples from reconstructed luma samples in a manner similar to that performed in CCLM mode. Similar to CCLM, when chroma subsampling is used, the reconstructed luma samples are downsampled to match the lower-resolution chroma grid. Similar to CCLM, the top, left, or top and left reference samples are used as templates for model induction.

[0105] Similarly to CCLM, there are options for using a single or multiple CCCM models. In multi-model CCCM (MM-CCCM) mode, two models are used: one model is derived for samples above the mean value of the luma reference samples, and the other model is derived for the remaining samples.

[0106] The convolutional 7-tap filter used in CCCM consists of a 5-tap plus a sign-shaped spatial filter part, a nonlinear term, and a bias term. As illustrated in Figure 6, the input to the spatial filter part consists of a central (C) luma sample co-located with the chroma sample to be predicted, and its upper / north (N), lower / south (S), left / west (W), and right / east (E) neighboring luma samples.

[0107] If the chroma format is not 4:4:4 (i.e., chroma has fewer samples than luma), the luma samples described above are downsampled luma samples.

[0108] The nonlinear term (P) is a scale of the power of 2 of the center (C) luma sample to the range of sample values ​​that can be represented in the current bit depth, as shown in the mathematical equation below.

[0109]

[0110] The bias term (B) represents a scalar offset between the input and output, set to the chroma midpoint (e.g., 512 for 10-bit content).

[0111]

[0112] The output of the filter is the filter coefficients (c i ) is calculated by convolution between the input values.

[0113]

[0114] FIG. 7 is a conceptual diagram illustrating an exemplary reference area used to derive CCCM filter coefficients. The filter coefficients (ci) are determined in a reference area (702) for a PU (700) such that the mean squared error (MSE) between chroma samples predicted from luma samples using CCCM and reconstructed chroma samples of the reference area is minimized. In the example of FIG. 7, the reference area (702) includes chroma samples of six lines on the left and above the PU (700). The reference area (702) extends from the PU boundary of the PU (700) to the right by the width of the PU and downward by the height of the PU. An extension (704) for the reference area (702) is used to support side samples of the plus-shaped spatial filter and is padded when it is in an unusable area.

[0115] MSE minimization is performed by computing the autocorrelation matrix for the luma input and the cross-correlation vector between the luma input and the chroma output. The autocorrelation matrix is ​​LDL decomposed, and the final filter coefficients are computed using back-substitution. This process is very similar to computing the filter coefficients of the adaptive linear filter (ALF) in ECM, but LDL decomposition is chosen instead of Cholesky decomposition to avoid using square root operations.

[0116] This paper describes GL-CCCM (Gradient and Location-based CCCM). Figure 8 is a conceptual diagram illustrating spatial samples for GL-CCCM. GL-CCCM mode uses gradient and location information instead of the four spatial neighboring samples used in the CCCM mode filter. The GL-CCCM filter for prediction is as follows.

[0117]

[0118] Here, Gy and Gx are the vertical gradient and horizontal gradient, respectively, and are calculated as follows.

[0119]

[0120]

[0121] In the above mathematical equation, N, NW, NE, S, SW, SE, W, NW, and E represent the north luma sample, the northwest luma sample, the northeast luma sample, the south luma sample, the southwest luma sample, the southeast luma sample, the west luma sample, and the east luma sample, respectively, adjacent to the central luma sample (C), as illustrated in FIG. 8. In addition, the parameters Y and X are the vertical and horizontal positions of the central luma sample (C) relative to the upper-left coordinate of the block. The remaining parameters are the same as in the CCCM mode, and the reference area for parameter calculation is also the same as in the CCCM mode. From a signaling perspective, GL-CCCM is regarded as a submode of CCCM. That is, the GL-CCCM flag is signaled only when the CCCM flag is true.

[0122] A CCCM-MDF (CCCM with Multiple Downsampling Filters) technique is described. In CCCM-MDF, multiple downsampling filters are applied to a group of luma samples reconstructed from CCCM. Figure 9 is a conceptual diagram illustrating multiple downsampling filters that can be applied to a luma block. A linear combination of these downsampled reconstructed samples is multiplied by the derived filter coefficients to form the final chroma predictor. In the tested models below, the horizontal position (X) or vertical position (Y) of the center luma sample is also considered. After selecting the optimal model among the cross-component models shown below, the video encoder can signal information (e.g., mode index) in the bitstream about which model is used to predict the current chroma block.

[0123] (1) Model 1: predChroma = c0*H(C) + c1*G1(C) + c2*G2(C) + c3*G3(C) + c4*P(H(C)) + c5*P(G1(C)) + c6*P(G2(C)) + c7*X + c8*Y + c9*B

[0124] (2) Model 2: predChroma = c0*H(C) + c1*H(W) + c2*H(E) + c3*G1(C) + c4*G1(W) + c5*G1(E) + c6*P(H(C)) + c7*P(H(W)) + c8*P(H(E)) + c9*X + c10*B

[0125] (3) Model 3: predChroma = c0*H(C) + c1*H(NE) + c2*H(SW) + c3*G3(C) + c4*G3(NE) + c5*G3(SW) + c6*P(H(C)) + c7*P(H(NE)) + c8*P(H(SW)) + c9*Y + c10*B

[0126] Here, H (·), G1 (·), G2 (·), G3 (·) are various downsampling filters as illustrated in Fig. 9, C represents the current chroma sample position, and N, S, W, E, NE, and SW represent the positions of samples around C. ci is a filter coefficient, P and B are nonlinear terms and bias terms, and X and Y are the horizontal and vertical positions of the center luma sample with respect to the upper left coordinate of the block.

[0127] A CCCM-ND (CCCM using non-downsampled luma samples) technique is described. The CCCM-ND mode is a method of predicting a chroma block using non-downsampled luma samples of a luma block. Fig. 10 is a conceptual diagram illustrating six non-downsampled luma samples corresponding to a chroma sample (C) to be predicted in the CCCM-ND mode. Referring to the mathematical equation below, the predicted value of the chroma sample can be calculated using a 6-tap spatial filter part using six luma samples (L0, L1, L2, L3, L4, L5 samples in Fig. 10) and four non-linear terms and a bias term using luma samples (L0, L3, L2, L1 samples).

[0128]

[0129] Here, α i are coefficients and β is an offset. To derive the filter coefficients, chroma samples from up to six rows and six columns above and to the left of the current CU are applied, similar to the conventional CCCM design. The filter coefficients are derived based on the same LDL decomposition method used in CCCM. The CCCM-ND method is signaled as an additional CCCM model in addition to the CCCM method. When CCCM is selected, a single flag is signaled to indicate whether the default CCCM model or the CCCM-ND model is applied to both chroma components.

[0130] A block vector guided CCCM (BVG-CCCM) technique is described. The BVG-CCCM technique determines a reference region for calculating CCCM parameters using a block vector of a co-located luma block coded in IBC or intraTMP mode. Fig. 11 is a conceptual diagram illustrating an exemplary reference region for BVG-CCCM. A video encoder and a video decoder can determine a luma reference region (1106) using a block vector (1104) of a co-located luma block (1102) coded in IBC or intraTMP mode. In addition, the video encoder and the video decoder can determine a block vector (1108) corresponding to the block vector (1104) to determine a chroma reference region (1110) for a current chroma block (1100). Then, the CCCM parameters can be calculated using the luma reference region (1106) and the chroma reference region (1110). Prediction is performed using co-located luma samples and computed CCCM parameters.

[0131] In the dual tree partitioning structure, as shown in FIG. 12, the block vector to be used in the BVG-CCCM technique is determined by scanning five locations (TL, TR, C, BL, BR) of the co-located luma block area, and the block vector (1108) is determined by scaling the block vector (1104) to fit the chroma format.

[0132] A GLM (Gradient linear model) technique is described. For the YUV 4:2:0 chroma format, the GLM method can be used to predict chroma samples from luma sample gradients. Two-parameter GLM and three-parameter GLM modes are supported. Compared to CCLM, instead of downsampling reconstructed luma samples, GLM uses luma sample gradients to derive a linear model. Specifically, when the two-parameter GLM mode is applied, the input to the CCLM process, i.e., the downsampled luma sample L, is replaced with the luma sample gradient G. Other parts of the CCLM mode (e.g., parameter derivation, prediction sample linearization) remain unchanged. Therefore, in the two-parameter GLM mode, a video encoder and a video decoder can use the luma sample gradient G, the gradient parameter α, and the bias parameter β to determine the prediction value of the chroma sample C as follows.

[0133]

[0134] In 3-parameter GLM mode, chroma samples can be predicted based on both luma sample gradients and downsampled luma values. The model parameters of 3-parameter GLM mode are derived from six rows and six columns of adjacent samples using the MSE minimization technique used in CCCM mode. For example, in 3-parameter GLM mode, a video encoder and decoder can determine the predicted value of chroma sample C as follows.

[0135]

[0136] The slope adjustment technique of CCLM is described. Slope adjustment is applied to CCLM and MM-CCLM prediction. When slope adjustment is applied, the video encoder and video decoder tilt the linear function that maps luma values ​​to chroma values ​​around a center point determined by the average luma value of reference samples. Slope adjustment can only be applied to either Cb or Cr, and when slope adjustment is applied to MM-CCLM, the same slope offset is applied to both linear models.

[0137] The Local-Boosting Cross-Component Prediction (LB-CCP) technique is described. When the LB-CCP mode is applied, a 3X3 low-pass filter is applied to filter the prediction samples generated by MM-CCLM / MM-CCCM. For samples at the upper / left boundary, the input of the filter includes neighboring reconstructed samples. For the unreconstructed neighboring sample positions, padding may be performed with adjacent prediction samples. A flag is signaled to indicate whether filtering is to be applied to blocks encoded with MM-CCLM / MM-CCCM.

[0138] This section describes the CCP Merge (Cross-component prediction merge) mode. In CCP Merge, the cross-component model parameters of the current chroma block can be inherited from a block already coded in a CCP mode (including CCLM, CCCM, GLM, and their variants). Additionally, information used for inverse transformation, such as the inverse transform kernel or the directional mode used to determine the inverse transform kernel, can be inherited from the already coded block. The CCP merge candidate list consists of spatially adjacent candidates, temporal candidates, spatially non-adjacent candidates, and history-based candidates. After including these candidates, default models are added to fill in the remaining gaps in the list. Pruning is applied to prevent duplicate CCP models from being included in the list. The video encoder and video decoder can determine the template cost for each model and use the cost value to sort multiple models. The video encoder can then signal an index within the sorted candidate list indicating which candidate (model) to use to code the current block.

[0139] Unlike the CCP Merge mode, the video decoder may also select the candidate with the lowest cost based on the template cost from the candidate list of CCP modes as the CCP mode for predicting the current chroma block. The template cost is determined based on a comparison between the predicted values ​​generated by each CCP mode and the reconstructed samples for the samples in the template of the current chroma block. The candidate list of CCP modes may include single-model CCLM, single-model CCCM, MM-CCCM, single-model GL-CCCM, single-model LB-CCP, and single-model LB-CCP. CCP fusion candidates derived from various decoders may be added to the candidate list. A CCP fusion candidate may be a combination of two CCP modes selected from the existing candidate list reordered according to the template cost. A mode flag and a fusion flag may be signaled to indicate the mode usage.

[0140] As described in the examples above, there may be multiple models that model the correlation between luma and chroma components. In the following description, a model may refer to a video coding technique that determines model parameters based on previously reconstructed samples and applies the model parameters to luma samples to generate a predicted block for a chroma block. The technique for determining the model parameters, the technique for determining the samples to which the model parameters are applied, and / or the technique for applying the model parameters to the samples may vary depending on the model. Depending on the context, a model may also refer to a filter used by the model, such as a linear filter or a convolutional filter.

[0141]

[0142] Now, a method for encoding and decoding a chroma block according to an embodiment of the present disclosure is described. A video encoder and a decoder can generate chroma prediction values ​​of chroma samples in a current chroma block using various prediction techniques / prediction modes. The video encoder and decoder can correct the chroma prediction values ​​based on a correlation between the chroma prediction values ​​and luma prediction values ​​of luma samples corresponding to the chroma samples. The video encoder and decoder can encode or decode the chroma block based on the corrected chroma prediction values.

[0143] FIG. 13 is a conceptual diagram illustrating a process of correcting chroma prediction values ​​using a cross-component model and deriving reconstructed values ​​of a chroma block using the corrected chroma prediction values, according to one embodiment of the present disclosure.

[0144] A video decoder can obtain chroma prediction values ​​(predC) of chroma samples in a current chroma block and luma prediction values ​​(predL) of luma samples corresponding to the current chroma block using various prediction techniques / prediction modes. Here, predC may represent prediction values ​​of a Cb component or prediction values ​​of a Cr component, and may also be referred to as "original" chroma prediction values ​​or "initial" chroma prediction values.

[0145] The chroma prediction values ​​(predC) may be generated by an intra prediction technique. For example, the chroma prediction values ​​(predC) may be generated by a prediction mode of one of Planar, DC, directional prediction modes, TIMD derived mode, DIMD derived mode, MIP (Matrix-based intra prediction) mode, IntraTMP, DBV (Direct Block Vector) mode, cross-component prediction modes (CCLM, MMLM, CCCM, GLM and their variants) or another intra mode. The luma prediction values ​​(predL) may be generated by an intra prediction technique (i.e., a prediction mode belonging to the mode type 'intra'), an inter prediction technique (i.e., a prediction mode belonging to the mode type 'inter'), or an IBC prediction technique (i.e., a prediction mode belonging to the mode type 'IBC'). The prediction mode belonging to the mode type 'inter' may be, for example, a skip mode, a merge mode, a MMVD mode, an affine mode, sbTMVP, AMVR, or another inter mode. A prediction mode belonging to mode type 'IBC' can be, for example, IBC Merge or IBC AMVP.

[0146] A video decoder can derive the parameters of a cross-component model for each chroma component individually using predL and predC. That is, for each chroma component, a cross-component model can be derived that models the correlation between the predicted values ​​of chroma samples (predC) and the predicted values ​​of the corresponding luma samples (predL).

[0147] Then, the video decoder can apply the derived cross-component model to the reconstructed values ​​(recL) of the luma samples corresponding to the chroma samples of the current chroma block to generate another predicted values ​​(predC') of the chroma samples of the current chroma block. Finally, the video decoder can fuse (i.e., weighted average) predC and predC' to generate corrected predicted values ​​(predC") of the chroma samples of the current chroma block. The corrected predicted values ​​(predC") are used as the final predicted values ​​of the chroma samples of the current chroma block. Therefore, the reconstructed values ​​(recC) of the chroma samples of the current chroma block can be generated by adding the chroma residual to predC".

[0148] As an example, the final chroma prediction values ​​(predC") for each chroma component can be calculated as follows:

[0149]

[0150]

[0151] Here, n and u can be integers greater than or equal to 1, and the weights M and N are M+N=2. n It can be an integer greater than or equal to 0 satisfying , and the weights P and Q are P+Q=2 u It can be an integer greater than or equal to 0 that satisfies . For example, M=P=3, N=Q=1, n=u=2.

[0152] A k-tap convolution filter can be used as a cross-component model to generate chroma prediction values ​​(predC'), which include k-2 spatial luma sample terms, a nonlinear term, and a bias term. The value of k and the positions of the luma samples used depend on the video color format. The spatial luma samples are obtained by selecting the k-2 reconstructed luma samples that are closest to the chroma sample positions in the luma picture without downsampling.

[0153] In one embodiment, for the YUV 4:2:0 color format, an 8-tap convolution filter, as shown in the following mathematical expression, may be used as a cross-component model. It includes six spatial luma samples (L0 to L5), a nonlinear term, and a bias term. The spatial luma samples (L0 to L5) are reconstructed luma values ​​of the six spatial luma samples closest to the chroma sample location C to be predicted, as shown in (a) of FIG. 14. c0 to c7 are eight model parameters (i.e., filter parameters).

[0154]

[0155]

[0156]

[0157] For the YUV 4:2:2 color format, L3 to L5 in the above equation are set to 0, which means that the three spatial luma samples (L1, L0, L2) shown in (b) of Fig. 14 are used in the cross-component model. For example, the reconstructed luma samples of the three spatial luma samples (L0, L1, L2) corresponding to the chroma sample position (i, j) are recL(2i, j), recL(2i-1, j), and recL(2i+1, j).

[0158] For the YUV 4:4:4 color format, L1 to L5 in the above equation are set to 0, which means that only one spatial luma sample (L0) shown in (c) of Fig. 14 is used in the cross-component model. For example, the reconstructed luma sample of one spatial luma sample (L0) corresponding to chroma sample position (i, j) is recL(i, j).

[0159] Filter coefficients (c i) may be determined such that the mean square error (MSE) based on the predicted values ​​(predC) of the chroma samples of the current chroma block and the predicted values ​​(predL) of the corresponding luma samples is minimized. For example, the Gaussian elimination method may be used.

[0160] A flag indicating whether correction based on a cross-component model is used for the predicted values ​​(predC) of the current chroma block may be signaled in the bitstream. If there is no residual signal of a luma block corresponding to the current chroma block (e.g., cbf_luma or root_cbf is 0), the flag may not be signaled, and correction may not be performed on the chroma predicted values ​​of the current chroma block.

[0161] Variants

[0162] In deriving and applying filter coefficients to correct the predicted values ​​of chroma samples of a chroma block (i.e., a chroma predictor), different methods may be used depending on the prediction method of the chroma block used to generate the chroma predictor.

[0163] FIG. 15 is a conceptual diagram illustrating examples in which some areas within a chroma block are excluded from a predictor correction process depending on the angle of the intra prediction mode, according to one embodiment of the present disclosure.

[0164] In some embodiments, when a chroma block is predicted using a directional intra prediction mode, some areas within the chroma block determined by the angle of the intra prediction mode may be excluded from the predictor correction process.

[0165] For example, referring to (a) of Fig. 15, when the angle (θ) of the directional intra prediction mode is 0 ≤ θ ≤ 90°, predictor correction may not be applied to the chroma sample positions of the upper A rows within the chroma block. As shown in (b) of Fig. 15, when the angle (θ) of the directional intra prediction mode is 90° < θ < 180°, predictor correction may not be applied to the sample positions of the upper A rows and the left B columns within the chroma block. As shown in (c) of Fig. 15, when the angle (θ) of the directional intra prediction mode is 180° ≤ θ ≤ 270°, predictor correction may not be applied to the chroma sample positions of the left B columns within the chroma block. Here, A and B may be integers greater than or equal to 1, and may be determined depending on the height and width of the chroma block.

[0166] Additionally, the predicted values ​​(predC) of chroma sample locations to which predictor correction is not applied and the predicted values ​​(predL) of the corresponding luma samples can also be excluded when deriving filter coefficients.

[0167] In some embodiments, when a chroma block is predicted using a cross-component prediction (CCP) mode, instead of the convolution filter represented by the above-described equation (13), a filter (model) of the same type as the CCP filter (model) used to generate the chroma predictor can also be used to correct the chroma predictor. Here, the CCP mode can include CCLM, MM-CCLM, CCCM, MM-CCCM, GLM and their variants (e.g., DDCCP, CCP merge, BVG-CCCM, CCCM-MDF, CCCM-ND, GL-CCCM, CCLM with slope adjustment, LB-CCP, etc.).

[0168] FIG. 16 is a flowchart illustrating a method by which a video decoder determines a cross-component model to use to correct a chroma predictor, according to one embodiment of the present disclosure.

[0169] The video decoder may determine, in response to the current chroma block being predicted using the CCP mode, whether correction information for the chroma predictor is determined based on prediction information for the chroma predictor. For example, a first flag indicating whether correction information for the chroma predictor is determined based on prediction information for the chroma predictor may be signaled as a syntax element of a higher-order data unit (e.g., a sequence, a picture, a slice, a tile, a CTU, etc.).

[0170] When the first flag is false (e.g., has a value of 0), the filter coefficients of the convolution filter expressed by the aforementioned mathematical expression 13 can be derived, and correction of the chroma predictor can be performed based on the convolution filter having the derived filter coefficients.

[0171] If the first flag is true (e.g., has a value of 1), a second flag may be parsed from the bitstream to indicate whether a filter of the same type as the CCP filter used to generate the chroma predictor is used to correct the chroma predictor. For example, the CCP filter may be a linear model used in CCLM, or a convolution-based model used in CCCM.

[0172] When the second flag is true (e.g., has a value of 1), correction of the chroma predictor of the current chroma block can be performed using a filter of the same type as the CCP filter used to generate the chroma predictor of the current chroma block, instead of the convolution filter expressed by Equation 13.

[0173] For example, if the current chroma block is predicted in CCLM mode using a linear model, the coefficients of the linear model that will be used to correct the chroma predictor of the current chroma block can be derived. If a slope adjustment technique is applied to the linear model of CCLM, the slope adjustment value applied to the linear model in the prediction process can be applied to the linear model in the correction process as well. In other words, after deriving the linear model in the correction process, the slope parameter of the linear model can be adjusted to update the linear model.

[0174] As another example, if the current chroma block is predicted in CCCM mode using a linear model, the coefficients of the convolution filter that will be used to compensate for the chroma predictor of the current chroma block can be derived.

[0175] As another example, if the current chroma block is predicted by a weighted sum of two or more CCP prediction signals, the type of the filter associated with the CCP predictor with the largest weight can be inherited and used for predictor correction. If two or more CCP prediction signals with the largest weight values ​​compete, the signaling and parsing of the second flag can be omitted, and the video encoder can derive the filter coefficients of the convolution filter expressed by the aforementioned mathematical expression 13, and perform correction of the chroma predictor based on the convolution filter with the derived filter coefficients.

[0176] If the second flag is false (e.g., has a value of 0), a filter index indicating a filter to be used for predictor correction of the current chroma block can be parsed from the bitstream. The filter index indicates a filter to be used for predictor correction of the current chroma block from a list of available filters of various shapes. The list of available filters may be determined depending on the CCP mode of the current chroma block. For example, if the current chroma block is predicted in CCCM mode, the list of available filters may not include a linear filter (used in CCLM mode).

[0177] In some other embodiments, if the current chroma block is predicted using CCP mode, the same type of filter as the CCP filter used for CCP-based prediction of the current chroma block can also be used to correct the prediction signal of the current chroma block, without signaling / parsing the flags and filter indices used in the method illustrated in FIG. 16.

[0178] Derivation of weight pairs

[0179] As described above, the corrected chroma prediction values ​​(predC") are derived by a weighted average of the original chroma prediction values ​​(predC) and another chroma prediction value (predC) obtained through a cross-component filter. Various methods for determining the weights (M, N, P, Q) used in Equations 11 and 12 are described below.

[0180] Below, a method for determining weights M and N of the chroma Cb component is described, assuming that the same weight pairs are used for the chroma Cb and Cr components (i.e., M=P and N=Q). Alternatively, a weight pair may be determined individually for each chroma component, so that the weights M and N may be different from the weights P and Q.

[0181] In one embodiment, the values ​​or information about the values ​​of the weights (M, N) to be used for the current chroma block may be signaled in the bitstream. As an example, an index indicating a weight pair within a predefined weight table may be signaled in the bitstream.

[0182] In another embodiment, weights (M, N) for the current chroma block may be implicitly determined based on whether predictor correction has been used for neighboring blocks of the current chroma block. The locations of neighboring blocks of the current chroma block may be determined as in the example of FIG. 17, and neighboring blocks that are not adjacent to the current chroma block may also be included in addition to the neighboring blocks illustrated in FIG. 17.

[0183] As an example, weights (M, N) for the current chroma block may be implicitly determined depending on the number or proportion of blocks on which predictor correction is performed among the neighboring blocks of the current chroma block. The weights (M, N) for the current chroma block may be determined such that the weight N for predC' has a larger value than the weight M for predC as the number or proportion of blocks on which predictor correction is performed among the neighboring blocks of the current chroma block increases. When calculating the number or proportion of neighboring blocks on which predictor correction is performed, information on the residual signal of the corresponding luma block of the neighboring block (e.g., whether the residual signal exists) may be taken into consideration. That is, even if the number of blocks on which predictor correction is performed is the same, the weights (M, N) for the current chroma block may be determined differently depending on information on the residual signal of the corresponding luma block of the neighboring block (e.g., whether the residual signal exists).

[0184] In some embodiments, a merge candidate list may be constructed for the current chroma block, with respect to information about surrounding blocks to which predictor correction has been applied. In this case, information added to the merge candidate list may include coefficients (c) of the filter used for predictor correction of the candidate.i ) and weights (M, N). A merge candidate index may be signaled for the current chroma block. The merge candidate index identifies one of the candidates in the merge candidate list. The coefficients (c) of the filter from the candidate identified by the merge candidate index i ) and weights (M, N) may be inherited, or only the coefficients of the filter or only the weights may be inherited. In case of inheriting the coefficients of the filter, the video decoder can apply the weights of the filter of the neighboring block as is to the current chroma block, or alternatively, modify the weights inherited from the neighboring block (e.g., modify them based on the correlation between the prediction signal of the current chroma block and the prediction signal of the corresponding luma block) and use them for the current chroma block.

[0185] In another embodiment, the weights (M, N) for a chroma block may be implicitly determined based on the prediction technique and / or prediction mode of the luma block corresponding to the chroma block.

[0186] For example, when the block partitioning structure is a single tree, the weights (M, N) for the chroma blocks may be determined differently depending on whether the prediction technology of the corresponding luma block is an intra prediction technology, an IBC prediction technology, or an inter prediction technology. For example, in the case of an intra-screen prediction technology, it may be determined as (M:N)=(3:1), in the case of an inter-screen prediction technology, it may be determined as (M:N)=(1:3), and in the case of an IBC prediction technology, it may be determined as (M:N)=(1:3).

[0187] As another example, when the block partitioning structure is a dual tree, the prediction techniques and / or prediction modes of the luma blocks at the five locations (TL, TR, C, BL, BR) illustrated in FIG. 12 may be checked, and based on this, weights (M, N) for the chroma blocks may be implicitly determined. For example, among the luma blocks at the five locations, if the number of blocks on which the intra prediction technique is performed is greater, (M:N)=(3:1) may be determined, and if the number of blocks on which the inter prediction technique and / or IBC prediction technique is greater, (M:N)=(1:3) may be determined.

[0188] In another embodiment, the weights (M, N) for a chroma block may be implicitly determined based on the quantization parameter (QP) of the luma block corresponding to the chroma block. For example, when the partitioning structure is a single tree, if the inverse quantization is performed using a QP greater than a predefined threshold while a residual signal of the corresponding luma block exists, the weight N may be determined to have a larger value than the weight M. As another example, when the partitioning structure is a dual tree, if the average or maximum value of the QPs of the luma blocks at the five positions (TL, TR, C, BL, BR) illustrated in FIG. 12 is greater than the threshold, the weight N may be determined to have a larger value than the weight M. As another example, if the difference between the QP of the chroma block and the QP of the corresponding luma block exceeds a certain threshold, the weight N may be determined to have a larger value than the weight M.

[0189] In another embodiment, if a residual signal of a corresponding luma block of a current chroma block exists, weights (M, N) for the current chroma block can be implicitly determined based on an inverse transform method of the luma block. For example, the weights (M, N) can be determined differently based on whether a non-separable inverse transform or a separable inverse transform is applied to the luma block. For example, if a non-separable first inverse transform is performed on the luma block, (M:N)=(7:1) can be determined, if a non-separable second inverse transform is performed on the luma block, (M:N)=(3:1) can be determined, and if a non-separable second inverse transform is not performed on the luma block, (M:N)=(1:3) can be determined.

[0190] In another embodiment, the weights (M, N) for a chroma block can be implicitly determined based on the statistics of the residual data of the luma block corresponding to the chroma block. For example, if the proportion of samples with residual values ​​of 0 in the corresponding luma block is more than half, (M:N)=(3:1) can be determined. Otherwise, (M:N)=(1:3) can be determined. As another example, if the variance of the residual values ​​of the corresponding luma block is greater than a predefined threshold, (M:N)=(1:3) can be determined. As another example, if the maximum absolute value of the residual values ​​of the corresponding luma block is higher than a certain threshold, (M:N)=(1:3) can be determined. As an example, if the sum of the absolute values ​​of the residual values ​​of the corresponding luma block is higher than a certain threshold, (M:N)=(1:3) can be determined. As an example, if the average of the absolute values ​​of the residual values ​​of the corresponding luma block is higher than a certain threshold, (M:N)=(1:3) can be determined.

[0191] In another embodiment, when fusion-based prediction is applied to a chroma block and at least one of the predictors used for fusion is a CCP-based predictor, the weights (M, N) in the predictor correction step can be implicitly determined based on the weights used for fusion of the predictors. Here, the same filter as the CCP filter used for generating the CCP-based predictor can be used for predictor correction in the predictor correction step.

[0192] For example, if one of the two predictors used in fusion-based prediction is a CCP-based predictor, the weights used in fusion-based prediction can be applied equally to the weights (M, N) in the predictor calibration step. That is, the weight M can be the same as the weight (w0) applied to the non-CCP-based predictor, and the weight N can be the same as the weight (w1) applied to the CCP-based predictor. Alternatively, the weights (M, N) can be implicitly determined based on the order relationship between the weights w0 and w1. For example, if the weight w1 is smaller than the weight w0, (M:N)=(3:1) can be determined, if the weight w1 is greater than the weight w0, (M:N)=(1:3) can be determined, and if the weight w1 is equal to the weight w0, (M:N)=(1:1) can be determined.

[0193] As another example, two or more different CCP-based predictors can be used for fusion-based prediction. For example, the mathematical formula "PredChroma = w0ХCCLM + w1ХCCCM + w2ХIntra" can be used in the prediction step. In this case, if PredChroma is corrected using the same filter as CCLM in the predictor correction step, (M:N)=((w1+w2):w0) can be determined. Alternatively, the weights (M, N) can be implicitly determined based on the magnitude relationship between w0 and "w1+w2". For example, if w0 is greater than "w1+w2", (M:N)=(1:3), if w0 is less than "w1+w2", (M:N)=(3:1), and if w0 is equal to "w1+w2", (M:N)=(1:1).

[0194] The values ​​of weights such as (3:1), (7:1) exemplified in the various embodiments described above are merely examples of one of the various possible combinations of (M:N) where M>N. Similarly, the values ​​of weights such as (1:3), (1:7) are M <N인 (M:N)의 다양한 가능한 조합들 중 하나를 예시한 것에 불과하다. 또한, 전술한 다양한 실시예들의 방법들 중 두 개 이상의 방법들이 결합되어 예측자 보정 단계에서 가중치들을 결정하는 데에 함께 사용될 수도 있음을 이해하여야 한다.

[0195]

[0196] FIG. 18 is a flowchart illustrating a method of coding (i.e., encoding or decoding) video data according to one embodiment of the present disclosure.

[0197] A video encoder or a video decoder may generate first chroma prediction values ​​for chroma samples of a current chroma block using an intra prediction technique (S1810). For example, the chroma prediction values ​​may be generated by one of the prediction modes of Planar, DC, directional prediction modes, TIMD derivation mode, DIMD derivation mode, Matrix-based intra prediction (MIP) mode, IntraTMP, direct block vector (DBV) mode, cross-component prediction (CCP) modes (CCLM, MMLM, CCCM, GLM, and variations thereof), or another intra mode.

[0198] A video encoder or video decoder may derive parameters of a cross-component model based on luma prediction values ​​and first chroma prediction values ​​for luma samples of a luma block corresponding to a current chroma block (S1820). The parameters of the cross-component model may be derived separately for the Cb chroma component and the Cr chroma component.

[0199] A video encoder or video decoder can generate second chroma prediction values ​​for chroma samples of a chroma block from reconstructed values ​​for luma samples using parameters of a cross-component model (S1830). Here, the reconstructed values ​​for the luma samples are generated by adding luma residual values ​​to the luma prediction values.

[0200] A video encoder or video decoder can generate modified chroma prediction values ​​for chroma samples of a chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values ​​(S1840).

[0201] A video encoder may encode a current chroma block based on modified chroma prediction values ​​(S1850). For example, the video encoder may encode residual data representing the difference between original sample values ​​of the current chroma block and modified chroma prediction values. A video decoder may decode the current chroma block based on the modified chroma prediction values ​​(S1850). For example, the video decoder may add chroma residual values ​​to the modified chroma prediction values ​​to generate reconstructed values ​​for chroma samples of the chroma block.

[0202] When the first chroma prediction values ​​are generated using a directional intra prediction mode, the generation of the second chroma prediction values ​​may be skipped for chroma samples in the upper A columns or the left B columns of the chroma block depending on the angle of the directional intra prediction mode. That is, the chroma samples in the upper A columns or the left B columns of the chroma block may not have their prediction values ​​corrected.

[0203] When the intra prediction technique used to generate the first chroma prediction value is not in CCP mode (i.e., in non-CCP mode), the cross-component model may be a k-tap convolution filter including k-2 spatial luma sample terms, a nonlinear term, and a bias term.

[0204] When the first chroma prediction values ​​are generated using the CCP mode, the cross-component model may be a model of the same type as the CCP model used to generate the first chroma prediction values ​​in the CCP mode. For example, when the first chroma prediction values ​​are generated using the CCLM mode, the cross-component model may be a linear model. When a linear model with slope adjustment applied is used in the CCLM mode, slope adjustment may be applied to the derived cross-component model. As another example, when the first chroma prediction values ​​are generated using the CCCM mode, the cross-component model may be a convolution-based model.

[0205] In some embodiments, the weights for the first chroma prediction values ​​and the weights for the second chroma prediction values ​​may be implicitly determined based on the prediction mode of the luma block corresponding to the chroma block.

[0206] In some embodiments, the weights for the first chroma prediction values ​​and the weights for the second chroma prediction values ​​may be determined based on statistics of the luma residual values ​​of the luma block corresponding to the chroma block.

[0207] In some embodiments, when the first chroma prediction values ​​are generated by fusion-based prediction and at least one of the predictors used in the fusion-based prediction is generated in CCP mode, the weights for the first chroma prediction values ​​and the weights for the second chroma prediction values ​​may be determined based on the weights used in the fusion of the predictors.

[0208]

[0209] Although the flowchart / timing diagram of this specification describes each process as being executed sequentially, this is merely an illustrative description of the technical idea of ​​one embodiment of the present disclosure. In other words, a person of ordinary skill in the art to which one embodiment of the present disclosure belongs may modify and apply various modifications and variations by changing the order described in the flowchart / timing diagram without departing from the essential characteristics of one embodiment of the present disclosure, or by executing one or more of the processes in parallel. Therefore, the flowchart / timing diagram is not limited to a chronological order.

[0210] It should be understood that the exemplary embodiments described above can be implemented in many different ways. The functions or methods described in one or more examples can be implemented in hardware, software, firmware, or any combination thereof. It should be understood that the functional components described herein are labeled as "units" to further emphasize their implementation independence.

[0211] Meanwhile, the various functions or methods described in this embodiment may also be implemented as instructions stored on a non-transitory storage medium that can be read and executed by one or more processors. Non-transitory storage media include, for example, all types of storage devices that store data in a form readable by a computer system. For example, non-transitory storage media include storage media such as erasable programmable read-only memory (EPROM), flash drives, optical drives, magnetic hard drives, and solid-state drives (SSDs).

[0212] The above description is merely an example of the technical idea of ​​the present embodiment, and those skilled in the art to which the present embodiment pertains may make various modifications and variations without departing from the essential characteristics of the present embodiment. Therefore, the present embodiments are not intended to limit the technical idea of ​​the present embodiment, but to explain it, and the scope of the technical idea of ​​the present embodiment is not limited by these embodiments. The protection scope of the present embodiment should be interpreted by the following claims, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of rights of the present embodiment.

[0213] CROSS-REFERENCE TO RELATED APPLICATION

[0214] This patent application claims priority to Korean Patent Application No. 10-2024-0060593, filed on May 8, 2024, which is incorporated herein by reference in its entirety.

Claims

1. A method for decrypting video data, A step of generating first chroma prediction values ​​for chroma samples of a chroma block using an intra prediction technique; A step of deriving a cross-component model based on luma prediction values ​​for luma samples of a luma block corresponding to the chroma block and the first chroma prediction values; generating second chroma prediction values ​​for chroma samples of the chroma block from reconstructed values ​​for the luma samples using the cross-component model, wherein the reconstructed values ​​for the luma samples are generated by adding luma residual values ​​to the luma prediction values; generating modified chroma prediction values ​​for chroma samples of the chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values; and A step of generating reconstructed values ​​for chroma samples of the chroma block by adding chroma residual values ​​to the above-mentioned modified chroma prediction values. A method comprising:

2. In paragraph 1, A method characterized in that the above cross-component model is derived separately for the Cb chroma component and the Cr chroma component.

3. In paragraph 1, A method characterized in that, when the first chroma prediction values ​​are generated using a directional intra prediction mode, generation of the second chroma prediction values ​​is skipped for chroma samples of the upper A columns or the left B columns of the chroma block depending on the angle of the directional intra prediction mode.

4. In paragraph 1, A method, characterized in that when the intra prediction technique used to generate the first chroma prediction value is not a cross-component prediction (CCP) mode, the cross-component model is a k-tap convolution filter including k-2 spatial luma sample terms, a nonlinear term, and a bias term.

5. In paragraph 1, A method, characterized in that, when the first chroma prediction values ​​are generated using a cross-component prediction (CCP) mode, the cross-component model is a model of the same type as the CCP model used to generate the first chroma prediction values ​​in the CCP mode.

6. In paragraph 5, A method characterized in that, when the first chroma prediction values ​​are generated using the CCLM mode, the cross-component model is a linear model.

7. In paragraph 6, When a linear model with slope adjustment is used in the above CCLM mode, A method characterized in that slope adjustment is applied to the above-described derived cross-component model.

8. In paragraph 5, A method characterized in that, when the first chroma prediction values ​​are generated using the CCCM mode, the cross-component model is a convolution-based model.

9. In paragraph 1, A method, characterized in that the weights for the first chroma prediction values ​​and the weights for the second chroma prediction values ​​are implicitly determined based on the prediction mode of the luma block corresponding to the chroma block.

10. In paragraph 1, A method, characterized in that the weights for the first chroma prediction values ​​and the weights for the second chroma prediction values ​​are implicitly determined based on statistics of the luma residual values ​​of the luma block corresponding to the chroma block.

11. In paragraph 1, A method characterized in that when the first chroma prediction values ​​are generated by fusion-based prediction and at least one of the predictors used in the fusion-based prediction is generated in CCP mode, the weights for the first chroma prediction values ​​and the weights for the second chroma prediction values ​​are implicitly determined based on the weights used in the fusion of the predictors.

12. A method for encoding video data, A step of generating first chroma prediction values ​​for chroma samples of a chroma block using an intra prediction technique; A step of deriving a cross-component model based on luma prediction values ​​for luma samples of a luma block corresponding to the chroma block and the first chroma prediction values; generating second chroma prediction values ​​for chroma samples of the chroma block from reconstructed values ​​for the luma samples using the cross-component model, wherein the reconstructed values ​​for the luma samples are generated by adding luma residual values ​​to the luma prediction values; generating modified chroma prediction values ​​for chroma samples of the chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values; and A step of encoding residual data representing the difference between the modified chroma prediction values ​​and the original sample values ​​of the chroma block. A method comprising:

13. A method for providing video data to a video decoding device. A step of encoding the above video data into a bitstream; and A step of transmitting the bitstream to the video decoding device and the step of encoding the video data into a bitstream includes: A step of generating first chroma prediction values ​​for chroma samples of a chroma block using an intra prediction technique; A step of deriving a cross-component model based on luma prediction values ​​for luma samples of a luma block corresponding to the chroma block and the first chroma prediction values; generating second chroma prediction values ​​for chroma samples of the chroma block from reconstructed values ​​for the luma samples using the cross-component model, wherein the reconstructed values ​​for the luma samples are generated by adding luma residual values ​​to the luma prediction values; generating modified chroma prediction values ​​for chroma samples of the chroma block based on a weighted average of the first chroma prediction values ​​and the second chroma prediction values; and A step of encoding residual data representing the difference between the modified chroma prediction values ​​and the original sample values ​​of the chroma block. A method characterized by including:

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