WO2024007825A1 - Procédé et appareil de mélange de modes explicites dans des systèmes de codage vidéo - Google Patents

Procédé et appareil de mélange de modes explicites dans des systèmes de codage vidéo Download PDF

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WO2024007825A1
WO2024007825A1 PCT/CN2023/099802 CN2023099802W WO2024007825A1 WO 2024007825 A1 WO2024007825 A1 WO 2024007825A1 CN 2023099802 W CN2023099802 W CN 2023099802W WO 2024007825 A1 WO2024007825 A1 WO 2024007825A1
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predictor
prediction
intra
cclm
block
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Hsin-Yi Tseng
Man-Shu CHIANG
Chih-Wei Hsu
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Mediatek Inc.
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/105—Selection of the reference unit for prediction within a chosen coding or prediction mode, e.g. adaptive choice of position and number of pixels used for prediction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103—Selection of coding mode or of prediction mode
    • H04N19/11—Selection of coding mode or of prediction mode among a plurality of spatial predictive coding modes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/154—Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/186—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a colour or a chrominance component
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
    • H04N19/51—Motion estimation or motion compensation
    • H04N19/513—Processing of motion vectors
    • H04N19/517—Processing of motion vectors by encoding
    • H04N19/52—Processing of motion vectors by encoding by predictive encoding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/91—Entropy coding, e.g. variable length coding [VLC] or arithmetic coding

Definitions

  • the present invention is a non-Provisional Application of and claims priority to U.S. Provisional Patent Application No. 63/367,820, filed on July 7, 2022 and U.S. Provisional Patent Application No. 63/482,816, filed on February 2, 2023.
  • the U.S. Provisional Patent Applications are hereby incorporated by reference in their entireties.
  • the present invention relates to video coding system.
  • the present invention relates to blending two intra-prediction modes and signalling coding modes and/or blending weight for improving coding performance.
  • VVC Versatile video coding
  • JVET Joint Video Experts Team
  • MPEG ISO/IEC Moving Picture Experts Group
  • ISO/IEC 23090-3 2021
  • Information technology -Coded representation of immersive media -Part 3 Versatile video coding, published Feb. 2021.
  • VVC is developed based on its predecessor HEVC (High Efficiency Video Coding) by adding more coding tools to improve coding efficiency and also to handle various types of video sources including 3-dimensional (3D) video signals.
  • HEVC High Efficiency Video Coding
  • Fig. 1A illustrates an exemplary adaptive Inter/Intra video coding system incorporating loop processing.
  • Intra Prediction 110 the prediction data is derived based on previously coded video data in the current picture.
  • Motion Estimation (ME) is performed at the encoder side and Motion Compensation (MC) is performed based of the result of ME to provide prediction data derived from other picture (s) and motion data.
  • Switch 114 selects Intra Prediction 110 or Inter Prediction 112 and the selected prediction data is supplied to Adder 116 to form prediction errors, also called residues.
  • the prediction error is then processed by Transform (T) 118 followed by Quantization (Q) 120.
  • T Transform
  • Q Quantization
  • the transformed and quantized residues are then coded by Entropy Encoder 122 to be included in a video bitstream corresponding to the compressed video data.
  • the bitstream associated with the transform coefficients is then packed with side information such as motion and coding modes associated with Intra prediction and Inter prediction, and other information such as parameters associated with loop filters applied to underlying image area.
  • the side information associated with Intra Prediction 110, Inter prediction 112 and in-loop filter 130, are provided to Entropy Encoder 122 as shown in Fig. 1A. When an Inter-prediction mode is used, a reference picture or pictures have to be reconstructed at the encoder end as well.
  • the transformed and quantized residues are processed by Inverse Quantization (IQ) 124 and Inverse Transformation (IT) 126 to recover the residues.
  • the residues are then added back to prediction data 136 at Reconstruction (REC) 128 to reconstruct video data.
  • the reconstructed video data may be stored in Reference Picture Buffer 134 and used for prediction of other frames.
  • incoming video data undergoes a series of processing in the encoding system.
  • the reconstructed video data from REC 128 may be subject to various impairments due to a series of processing.
  • in-loop filter 130 is often applied to the reconstructed video data before the reconstructed video data are stored in the Reference Picture Buffer 134 in order to improve video quality.
  • deblocking filter (DF) may be used.
  • SAO Sample Adaptive Offset
  • ALF Adaptive Loop Filter
  • the loop filter information may need to be incorporated in the bitstream so that a decoder can properly recover the required information. Therefore, loop filter information is also provided to Entropy Encoder 122 for incorporation into the bitstream.
  • DF deblocking filter
  • SAO Sample Adaptive Offset
  • ALF Adaptive Loop Filter
  • Loop filter 130 is applied to the reconstructed video before the reconstructed samples are stored in the reference picture buffer 134.
  • the system in Fig. 1A is intended to illustrate an exemplary structure of a typical video encoder. It may correspond to the High Efficiency Video Coding (HEVC) system, VP8, VP9, H. 264 or VVC.
  • HEVC High Efficiency Video Coding
  • the decoder can use similar or portion of the same functional blocks as the encoder except for Transform 118 and Quantization 120 since the decoder only needs Inverse Quantization 124 and Inverse Transform 126.
  • the decoder uses an Entropy Decoder 140 to decode the video bitstream into quantized transform coefficients and needed coding information (e.g. ILPF information, Intra prediction information and Inter prediction information) .
  • the Intra prediction 150 at the decoder side does not need to perform the mode search. Instead, the decoder only needs to generate Intra prediction according to Intra prediction information received from the Entropy Decoder 140.
  • the decoder only needs to perform motion compensation (MC 152) according to Inter prediction information received from the Entropy Decoder 140 without the need for motion estimation.
  • an input picture is partitioned into non-overlapped square block regions referred as CTUs (Coding Tree Units) , similar to HEVC.
  • CTUs Coding Tree Units
  • Each CTU can be partitioned into one or multiple smaller size coding units (CUs) .
  • the resulting CU partitions can be in square or rectangular shapes.
  • VVC divides a CTU into prediction units (PUs) as a unit to apply prediction process, such as Inter prediction, Intra prediction, etc.
  • the VVC standard incorporates various new coding tools to further improve the coding efficiency over the HEVC standard.
  • a cross-component linear model (CCLM) prediction mode is used in the VVC, for which the chroma samples are predicted based on the reconstructed luma samples of the same CU by using a linear model.
  • more new coding tools such as blending multiple prediction modes, have been disclosed.
  • methods and apparatus for blending two intra-prediction modes, wherein at least one mode is related to cross-component prediction mode (for example, CCLM or any other type of cross-component prediction mode) are disclosed to improve the coding performance.
  • a method and apparatus for video coding are disclosed. According to the method, input data associated with a current block comprising a first-colour block and a second-colour block are received, wherein the input data comprise pixel data for the current block to be encoded at an encoder side or coded data associated with the current block to be decoded at a decoder side.
  • a first predictor is determined from a first intra-prediction candidate set, wherein the first predictor provides first prediction for the second-colour block.
  • a second predictor is determined from a second intra-prediction candidate set, wherein the second predictor provides second prediction for the second-colour block. At least one of the first predictor and the second predictor is derived based on the first-colour block using a cross-component model.
  • a final predictor is generated by blending the first predictor and the second predictor.
  • the second-colour block is encoded or decoded by using prediction data comprising the final predictor.
  • the first-colour block corresponds to either a luma block or a chroma block and the second-colour block corresponds to one remaining colour-component block of the current block.
  • the first intra-prediction candidate set or the second intra-prediction candidate set comprises one or more CCP (Cross Colour Prediction) modes, wherein said one or more CCP modes derive prediction for one colour-component block based on another colour-component block.
  • said one or more CCP modes comprise one or more CCLM types, one or more MMLM types, one or more GLM types, one or more CCCM types, or any combination thereof.
  • the CCLM types may correspond to CCLM_LT, CCLM_L, CCLM_T, or any combination thereof.
  • the MMLM types may correspond to MMLM_LT, MMLM_L, MMLM_T, or any combination thereof.
  • the CCCM types may correspond to one CCCM model using a different convolutional filter shape, one CCCM model using non-down-sampled samples, one CCCM model with multiple down-sampling filters, one mixed CCCM model, one CCCM model derived with different numbers of reference lines, one CCCM model derived with templates at different locations, or any combination thereof.
  • the second intra-prediction candidate set is generated from the first intra-prediction candidate set by excluding the first predictor.
  • the first predictor or the second predictor is selected from the first intra-prediction candidate set or the second intra-prediction candidate set respectively based on TIMD costs associated with member candidates in the first intra-prediction candidate set or the second intra-prediction candidate set.
  • a target member candidate with a smallest TIMD cost is implicitly selected as the first predictor or the second predictor.
  • a list comprising k candidates with smallest TIMD costs is generated and an index is signalled in a bitstream or parsed from the bitstream to indicate the first predictor or the second predictor selected from the list, and wherein k is an integer smaller than a total number of candidates in the first intra-prediction candidate set or the second intra-prediction candidate set.
  • the first predictor or the second predictor is selected from the first intra-prediction candidate set or the second intra-prediction candidate set respectively.
  • the first predictor or the second predictor is determined according to an index signalled in a bitstream or parsed from the bitstream.
  • a flag for the current block is signalled in a bitstream or parsed from the bitstream to indicate whether to determine the first predictor, the second predictor and the final predictor for the current block and whether to encode or decode the current block by using the prediction data comprising the final predictor.
  • the flag is signalled or parsed at a CU level, PU level or CTU level.
  • the first intra-prediction candidate set consists of CCLM_LT, CCLM_L and CCLM_T
  • the second intra-prediction candidate set consists of MMLM_LT, MMLM_L and MMLM_T.
  • the final predictor corresponds to a weighted sum of the first predictor and the second predictor.
  • weights for the weighted sum correspond to ⁇ and (1- ⁇ ) , where 0 ⁇ ⁇ ⁇ 1.
  • the weights are determined based on first predictor TIMD cost and second predictor TIMD cost.
  • w 1 can equal to (first predictor TIMD cost / (first predictor TIMD cost + second predictor TIMD cost) )
  • w 2 can be equal to (second predictor TIMD cost / (first predictor TIMD cost + second predictor TIMD cost) ) .
  • Fig. 1A illustrates an exemplary adaptive Inter/Intra video coding system incorporating loop processing.
  • Fig. 1B illustrates a corresponding decoder for the encoder in Fig. 1A.
  • Fig. 2 shows the 67 intra prediction modes as adopted by the VVC video coding standard.
  • Figs. 3A-B illustrate examples of wide-angle intra prediction a block with width larger than height (Fig. 3A) and a block with height larger than width (Fig. 3B) .
  • Fig. 4 shows an example of the location of the left and above samples and the sample of the current block involved in the LM_LA mode.
  • Fig. 5 shows an example of classifying the neighbouring samples into two groups according to multiple mode CCLM.
  • Fig. 6A illustrates an example of the CCLM model.
  • Fig. 6B illustrates an example of the effect of the slope adjustment parameter “u” for model update.
  • Fig. 7 illustrates an example of template-based intra mode derivation (TIMD) mode, where TIMD implicitly derives the intra prediction mode of a CU using a neighbouring template at both the encoder and decoder.
  • TIMD template-based intra mode derivation
  • Fig. 8 illustrates an example of spatial part of the convolutional filter.
  • Fig. 9 illustrates an example of reference area with paddings used to derive the filter coefficients.
  • Fig. 10 illustrates the 16 gradient patterns for Gradient Linear Model (GLM) .
  • Fig. 11 illustrates a flowchart of an exemplary video coding system that incorporates intra-prediction mode blending according to an embodiment of the present invention.
  • the number of directional intra modes in VVC is extended from 33, as used in HEVC, to 65.
  • the new directional modes not in HEVC are depicted as dotted arrows in Fig. 2, and the planar and DC modes remain the same.
  • These denser directional intra prediction modes apply for all block sizes and for both luma and chroma intra predictions.
  • every intra-coded block has a square shape and the length of each of its side is a power of 2. Thus, no division operations are required to generate an intra-predictor using DC mode.
  • blocks can have a rectangular shape that necessitates the use of a division operation per block in the general case. To avoid division operations for DC prediction, only the longer side is used to compute the average for non-square blocks.
  • MPM most probable mode
  • a unified 6-MPM list is used for intra blocks irrespective of whether MRL and ISP coding tools are applied or not.
  • the MPM list is constructed based on intra modes of the left and above neighbouring block. Suppose the mode of the left is denoted as Left and the mode of the above block is denoted as Above, the unified MPM list is constructed as follows:
  • MPM list ⁇ ⁇ Planar, Max, DC, Max -1, Max + 1, Max -2 ⁇
  • MPM list ⁇ ⁇ Planar, Left, Left -1, Left + 1, DC, Left -2 ⁇
  • the first bin of the MPM index codeword is CABAC context coded. In total three contexts are used, corresponding to whether the current intra block is MRL enabled, ISP enabled, or a normal intra block.
  • TBC Truncated Binary Code
  • Conventional angular intra prediction directions are defined from 45 degrees to -135 degrees in clockwise direction.
  • VVC several conventional angular intra prediction modes are adaptively replaced with wide-angle intra prediction modes for non-square blocks.
  • the replaced modes are signalled using the original mode indexes, which are remapped to the indexes of wide angular modes after parsing.
  • the total number of intra prediction modes is unchanged, i.e., 67, and the intra mode coding method is unchanged.
  • top reference with length 2W+1 and the left reference with length 2H+1, are defined as shown in Fig. 3A and Fig. 3B respectively.
  • the number of replaced modes in wide-angular direction mode depends on the aspect ratio of a block.
  • the replaced intra prediction modes are illustrated in Table 1.
  • Chroma derived mode (DM) derivation table for 4: 2: 2 chroma format was initially ported from HEVC extending the number of entries from 35 to 67 to align with the extension of intra prediction modes. Since HEVC specification does not support prediction angle below -135° and above 45°, luma intra prediction modes ranging from 2 to 5 are mapped to 2. Therefore, chroma DM derivation table for 4: 2: 2: chroma format is updated by replacing some values of the entries of the mapping table to convert prediction angle more precisely for chroma blocks.
  • pred C (i, j) represents the predicted chroma samples in a CU and rec L (i, j) represents the downsampled reconstructed luma samples of the same CU.
  • the CCLM parameters ( ⁇ and ⁇ ) are derived with at most four neighbouring chroma samples and their corresponding down-sampled luma samples. Suppose the current chroma block dimensions are W ⁇ H, then W’ and H’ are set as
  • the four neighbouring luma samples at the selected positions are down-sampled and compared four times to find two larger values: x 0 A and x 1 A , and two smaller values: x 0 B and x 1 B .
  • Their corresponding chroma sample values are denoted as y 0 A , y 1 A , y 0 B and y 1 B .
  • Fig. 4 shows an example of the location of the left and above samples and the sample of the current block involved in the LM_LA mode.
  • Fig. 4 shows the relative sample locations of N ⁇ N chroma block 410, the corresponding 2N ⁇ 2N luma block 420 and their neighbouring samples (shown as filled circles) .
  • the division operation to calculate parameter ⁇ is implemented with a look-up table.
  • the diff value difference between maximum and minimum values
  • LM_A 2 LM modes
  • LM_L 2 LM modes
  • LM_A mode only the above template is used to calculate the linear model coefficients. To get more samples, the above template is extended to (W+H) samples. In LM_L mode, only left template are used to calculate the linear model coefficients. To get more samples, the left template is extended to (H+W) samples.
  • LM_LA mode left and above templates are used to calculate the linear model coefficients.
  • two types of down-sampling filter are applied to luma samples to achieve 2 to 1 down-sampling ratio in both horizontal and vertical directions.
  • the selection of down-sampling filter is specified by a SPS level flag.
  • the two down-sampling filters are as follows, which are corresponding to “type-0” and “type-2” content, respectively.
  • Rec L ′ (i, j) [rec L (2i-1, 2j-1) +2 ⁇ rec L (2i-1, 2j-1) +rec L (2i+1, 2j-1) + rec L (2i-1, 2j) +2 ⁇ rec L (2i, 2j) +rec L (2i+1, 2j) +4] >>3 (6)
  • Rec L ′ (i, j) rec L (2i, 2j-1) +rec L (2i-1, 2j) +4 ⁇ rec L (2i, 2j) +rec L (2i+1, 2j) + rec L (2i, 2j+1) +4] >>3 (7)
  • the one-dimensional filter [1, 2, 1] /4 is applied to the above neighboring luma samples in order to avoid the usage of more than one luma line above the CTU boundary.
  • This parameter computation is performed as part of the decoding process, and is not just as an encoder search operation. As a result, no syntax is used to convey the ⁇ and ⁇ values to the decoder.
  • chroma intra mode coding For chroma intra mode coding, a total of 8 intra modes are allowed for chroma intra mode coding. Those modes include five traditional intra modes and three cross-component linear model modes ( ⁇ LM_LA, LM_L, and LM_A ⁇ , or ⁇ CCLM_LT, CCLM_L, and CCLM_T ⁇ ) .
  • the terms of ⁇ LM_LA, LM_L, LM_A ⁇ and ⁇ CCLM_LT, CCLM_L, CCLM_T ⁇ are used interchangeably in this disclosure.
  • Chroma mode signalling and derivation process are shown in Table 2. Chroma mode coding directly depends on the intra prediction mode of the corresponding luma block.
  • one chroma block may correspond to multiple luma blocks. Therefore, for Chroma DM mode, the intra prediction mode of the corresponding luma block covering the center position of the current chroma block is directly inherited.
  • the first bin indicates whether it is regular (0) or CCLM modes (1) . If it is LM mode, then the next bin indicates whether it is LM_LA (0) or not. If it is not LM_LA, next 1 bin indicates whether it is LM_L (0) or LM_A (1) .
  • the first bin of the binarization table for the corresponding intra_chroma_pred_mode can be discarded prior to the entropy coding. Or, in other words, the first bin is inferred to be 0 and hence not coded.
  • This single binarization table is used for both sps_cclm_enabled_flag equal to 0 and 1 cases.
  • the first two bins in Table 3 are context coded with its own context model, and the rest bins are bypass coded.
  • the chroma CUs in 32x32 /32x16 chroma coding tree node are allowed to use CCLM in the following way:
  • all chroma CUs in the 32x32 node can use CCLM
  • all chroma CUs in the 32x16 chroma node can use CCLM.
  • CCLM is not allowed for chroma CU.
  • MMLM Multiple Model CCLM
  • MMLM multiple model CCLM mode
  • JEM J. Chen, E. Alshina, G.J. Sullivan, J. -R. Ohm, and J. Boyce, Algorithm Description of Joint Exploration Test Model 7, document JVET-G1001, ITU-T/ISO/IEC Joint Video Exploration Team (JVET) , Jul. 2017
  • MMLM multiple model CCLM mode
  • neighbouring luma samples and neighbouring chroma samples of the current block are classified into two groups, each group is used as a training set to derive a linear model (i.e., a particular ⁇ and ⁇ are derived for a particular group) .
  • the samples of the current luma block are also classified based on the same rule for the classification of neighbouring luma samples.
  • CCLM uses a model with 2 parameters to map luma values to chroma values as shown in Fig. 6A.
  • the slope parameter “a” and the bias parameter “b” define the mapping as follows:
  • mapping function is tilted or rotated around the point with luminance value y r .
  • Fig. 6A and 6B illustrates the process.
  • Slope adjustment parameter is provided as an integer between -4 and 4, inclusive, and signalled in the bitstream.
  • the unit of the slope adjustment parameter is (1/8) -th of a chroma sample value per luma sample value (for 10-bit content) .
  • Adjustment is available for the CCLM models that are using reference samples both above and left of the block (e.g. “LM_CHROMA_IDX” and “MMLM_CHROMA_IDX” ) , but not for the “single side” modes. This selection is based on coding efficiency versus complexity trade-off considerations. “LM_CHROMA_IDX” and “MMLM_CHROMA_IDX” refers to CCLM_LT and MMLM_LT in this invention. The “single side” modes refers to CCLM_L, CCLM_T, MMLM_L, and MMLM_T in this invention.
  • the proposed encoder approach performs an SATD (Sum of Absolute Transformed Differences) based search for the best value of the slope update for Cr and a similar SATD based search for Cb. If either one results as a non-zero slope adjustment parameter, the combined slope adjustment pair (SATD based update for Cr, SATD based update for Cb) is included in the list of RD (Rate-Distortion) checks for the TU.
  • SATD Sud of Absolute Transformed Differences
  • JVET-M0425 In the multi-hypothesis inter prediction mode (JVET-M0425) , one or more additional motion-compensated prediction signals are signalled, in addition to the conventional bi-prediction signal.
  • the resulting overall prediction signal is obtained by sample-wise weighted superposition.
  • the weighting factor ⁇ is specified by the new syntax element add_hyp_weight_idx, according to the following mapping (Table 4) :
  • more than one additional prediction signal can be used.
  • the resulting overall prediction signal is accumulated iteratively with each additional prediction signal.
  • the resulting overall prediction signal is obtained as the last p n (i.e., the p n having the largest index n) .
  • p n i.e., the p n having the largest index n
  • up to two additional prediction signals can be used (i.e., n is limited to 2) .
  • the motion parameters of each additional prediction hypothesis can be signalled either explicitly by specifying the reference index, the motion vector predictor index, and the motion vector difference, or implicitly by specifying a merge index.
  • a separate multi-hypothesis merge flag distinguishes between these two signalling modes.
  • MHP is only applied if non-equal weight in BCW is selected in bi-prediction mode. Details of MHP for VVC can be found in JVET-W2025 (Muhammed Coban, et. al., “Algorithm description of Enhanced Compression Model 2 (ECM 2) ” , Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29, 23rd Meeting, by teleconference, 7–16 July 2021, Document: JVET-W2025) .
  • ECM 2 Enhanced Compression Model 2
  • Template-based intra mode derivation (TIMD) mode implicitly derives the intra prediction mode of a CU using a neighbouring template at both the encoder and decoder, instead of signalling the intra prediction mode to the decoder.
  • the prediction samples of the template (712 and 714) for the current block 710 are generated using the reference samples (720 and 722) of the template for each candidate mode.
  • a cost is calculated as the SATD (Sum of Absolute Transformed Differences) between the prediction samples and the reconstruction samples of the template.
  • the intra prediction mode with the minimum cost is selected as the TIMD mode and used for intra prediction of the CU.
  • the candidate modes may be 67 intra prediction modes as in VVC or extended to 131 intra prediction modes.
  • MPMs can provide a clue to indicate the directional information of a CU.
  • the intra prediction mode can be implicitly derived from the MPM list.
  • the SATD between the prediction and reconstruction samples of the template is calculated.
  • First two intra prediction modes with the minimum SATD are selected as the TIMD modes. These two TIMD modes are fused with weights after applying PDPC process, and such weighted intra prediction is used to code the current CU.
  • Position dependent intra prediction combination (PDPC) is included in the derivation of the TIMD modes.
  • weight1 costMode2/ (costMode1+ costMode2)
  • weight2 1 -weight1.
  • pred (w0*pred0+w1*pred1+ (1 ⁇ (shift-1) ) ) >>shift.
  • pred0 is the predictor obtained by applying the non-LM mode
  • pred1 is the predictor obtained by applying the MMLM_LT mode
  • pred is the final predictor of the current chroma block.
  • CCCM Convolutional cross-component model
  • a convolutional model is applied to improve the chroma prediction performance.
  • the convolutional model has 7-tap filter consisting of a 5-tap plus sign shape spatial component, a nonlinear term and a bias term.
  • the input to the spatial 5-tap component of the filter consists of a center (C) luma sample which is collocated with the chroma sample to be predicted and its above/north (N) , below/south (S) , left/west (W) and right/east (E) neighbours as shown in Fig. 8.
  • the bias term (denoted as B) represents a scalar offset between the input and output (similarly to the offset term in CCLM) and is set to the middle chroma value (512 for 10-bit content) .
  • the filter coefficients c i are calculated by minimising MSE between predicted and reconstructed chroma samples in the reference area.
  • Fig. 9 illustrates an example of the reference area which consists of 6 lines of chroma samples above and left of the PU 910. Reference area extends one PU width to the right and one PU height below the PU boundaries. Area is adjusted to include only available samples. The extensions to the area (indicated as “paddings” ) are needed to support the “side samples” of the plus-shaped spatial filter in Fig. 8 and are padded when in unavailable areas.
  • the MSE minimization is performed by calculating autocorrelation matrix for the luma input and a cross-correlation vector between the luma input and chroma output.
  • Autocorrelation matrix is LDL decomposed and the final filter coefficients are calculated using back-substitution. The process follows roughly the calculation of the ALF filter coefficients in ECM, however LDL decomposition was chosen instead of Cholesky decomposition to avoid using square root operations.
  • the GLM utilizes luma sample gradients to derive the linear model. Specifically, when the GLM is applied, the input to the CCLM process, i.e., the down-sampled luma samples L, are replaced by luma sample gradients G. The other parts of the CCLM (e.g., parameter derivation, prediction sample linear transform) are kept unchanged.
  • C ⁇ G+ ⁇
  • the CCLM mode when the CCLM mode is enabled for the current CU, two flags are signalled separately for Cb and Cr components to indicate whether GLM is enabled for each component. If the GLM is enabled for one component, one syntax element is further signalled to select one of 16 gradient filters (1010-1040 in Fig. 10) for the gradient calculation.
  • the GLM can be combined with the existing CCLM by signalling one extra flag in bitstream. When such combination is applied, the filter coefficients that are used to derive the input luma samples of the linear model are calculated as the combination of the selected gradient filter of the GLM and the down-sampling filter of the CCLM.
  • an inter mode utilizes temporal information to predict the current block.
  • spatially neighbouring reference samples are used to predict the current block.
  • a coding tool is proposed. The coding tool creates a new blending mode to form a better predictor and more efficient signalling. The concept of this coding tool is described as follows.
  • an additional hypothesis of intra prediction (denoted as H2) is blended with the existing hypothesis of intra prediction (denoted as H1) by a pre-defined weighting to form the final prediction of the current block.
  • H1 is generated by one mode selected from the first mode set (denoted as Set1)
  • H2 is generated by one mode selected from the second mode set (denoted as Set2) .
  • the weighting to blend H1 and H2 be w1 and w2
  • Final prediction w 1 *H 1 +w 2 *H 2 ,
  • H1 and H2 can be any intra modes.
  • Intra modes refer modes used to generate intra block predictions. For example, the 67 intra prediction modes, the CCLM modes and the MMLM modes mentioned earlier.
  • H1 and H2 can be any cross-component prediction modes.
  • Cross-component prediction modes refer to modes that predict the second colour component of a block by the first colour component of a block with a model describing the relationship of the two colour components.
  • the first colour component can be luma component
  • the second colour component can be Cb or Cr.
  • the first colour component can be Cb and the second colour component can be Cr.
  • the model can be a linear model, a convolutional model or a mapping model.
  • Examples of cross-component prediction modes includes CCLM, MMLM, GLM, CCCM and variants of CCCM.
  • CCLM and MMLM predict chroma components by the luma component using a linear model.
  • a mapping models comprises lookup tables, in which the first colour component value and the second colour component value mapping relationship is recorded.
  • the first colour component values e.g., sample intensity
  • the collocated first colour component sample value is looked up in the lookup tables and the corresponding second colour component values in the tables are used to predict the second colour component sample value in the current block.
  • H1 and H2 can be any convolutional cross-component model modes (CCCM) and CCCM variants.
  • CCCM model using different convolutional filter shape CCCM model using non-downsampled samples
  • CCCM model with multiple down- sampling filters mixed CCCM model with various terms (e.g. spatial term, gradient term, location term, non-linear term and bias term)
  • CCCM model derived with different number of reference lines CCCM model derived with templates at different locations. All the CCCM modes mentioned in this paragraphs are referred as CCCM types in this disclosure.
  • H1 and H2 can be any LM modes.
  • LM modes refer to modes that predict chroma component of a block by the collocated reconstructed luma samples according to linear models, whose parameters are derived from already reconstructed luma and chroma samples that are adjacent to the block.
  • LM modes includes CCLM and MMLM.
  • H1 and H2 can be any LM modes and GLM modes.
  • H1 can be any CCLM mode and H2 can be any MMLM modes
  • this coding tool is applied to blocks of any colour component.
  • this coding tool can be applied to luma component and/or chroma components.
  • this coding tool is applied to blocks of chroma components.
  • a flag is signalled/parsed at block-level to indicate whether to apply the blending mode to the current block.
  • the flag can be signalled at CU level and/or PU level and/or CTU level.
  • the flag can be signal at CB level and/or PB level and/or CTB and/or TU/TB and/or any predefined region level.
  • the flag indicates that the blending mode is disabled
  • the original syntax for signalling/parsing an intra prediction mode for the current block is followed.
  • the flag indicates that the blending mode is enabled
  • the following syntax related to indicating the modes to generated H1 and H2 and/or weighting is needed to be decided and signalled at encoder or parsed at decoder.
  • the blending mode and other intra prediction modes are mutually exclusive, i.e., if blending mode is chosen, other intra prediction modes cannot be chosen, and vice versa. Only the syntax related to blending mode is signalled.
  • the blending mode and other intra prediction modes, indicated by original syntax are not mutually exclusive.
  • the original syntax is then sent after the syntax related to blending mode.
  • another hypothesis H3 generated by the mode indicated by the original syntax can be further blended with H1 and H2 by another pre-defined weighting to generate a block predictor.
  • the original syntax can also be sent before the syntax related to the blending mode. For example, when the fusion of chroma intra prediction flag is on, the DM mode and the four default modes can be fused with the blending mode, instead of MMLM_LT if blending mode is also enabled.
  • a flag is signalled after the flag enabling/disabling LM modes.
  • the flag is signalled after CclmEnabled flag.
  • CclmEnabled specifies if a cross-component chroma intra prediction mode is enabled (i.e., TRUE) or not enabled (i.e., FALSE) for the current chroma coding block.
  • the flag is signalled before the flag enabling/disabling LM modes.
  • the flag is signalled before CclmEnabled flag.
  • CclmEnabled specifies if a cross- component chroma intra prediction mode is enabled (i.e., TRUE) or not enabled (i.e., FALSE) for the current chroma coding block.
  • the flag is signalled after the flag specifying if the decoded residuals of the current coding unit are applied using a colour space conversion.
  • the flag is signalled after cu_act_enabled_flag.
  • cu_act_enabled_flag 1 specifies that the decoded residuals of the current coding unit are applied using a colour space conversion.
  • cu_act_enabled_flag 0 specifies that the decoded residuals of the current coding unit are applied without a colour space conversion.
  • cu_act_enabled_flag is not present, it is inferred to be equal to 0.
  • H1 is generated by one mode selected from the first mode set (denoted as Set1)
  • H2 is generated by one mode selected from the second mode set (denoted as Set2)
  • H1 and H2 can be any intra modes.
  • Set1 includes CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, MMLM_T, or any subset of the above modes, or any extension of LM family.
  • Set1 includes CCLM_LT, CCLM_L, CCLM_T, or any subset of the above modes.
  • the CCLM_LT, CCLM_L, CCLM_T are referred as CCLM types in this disclosure.
  • Set1 includes MMLM_LT, MMLM_L, MMLM_T, or any subset of the above modes.
  • the MMLM_LT, MMLM_L, MMLM_T are referred as MMLM types in this disclosure.
  • Set2 includes CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, MMLM_T, or any subset of the above modes, or any extension of LM family.
  • Set2 includes CCLM_LT, CCLM_L, CCLM_T, or any subset of the above modes.
  • Set2 includes MMLM_LT, MMLM_L, MMLM_T, or any subset of the above modes.
  • the MMLM_LT, MMLM_L, MMLM_T are referred as MMLM types in this disclosure.
  • the number of candidates in Set2 is less than the number of candidates in Set1.
  • Set2 is generated from Set1 by excluding the mode selected for generating H1.
  • the number of candidates in Set2 is one less than the number of candidates in Set1.
  • the size of Set2 can be further reduced. For example, if Set1 contains CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, and MMLM_T.
  • Set2 includes CCLM_L, CCLM_T, MMLM_LT, MMLM_L, and MMLM_T.
  • Set2 includes CCLM_T, MMLM_LT, MMLM_L, and MMLM_T.
  • Set2 includes MMLM_LT, MMLM_L, and MMLM_T.
  • Set2 includes MMLM_L and MMLM_T.
  • Set2 includes MMLM_T.
  • the mode selected from Set1 to generate H1 is indicated by an index (denoted as index0) which is signalled/parsed in the bitstream.
  • the mode selected from Set2 to generate H2 is indicated by an index (denoted as index1) which signalled/parsed in the bitstream.
  • Index0 ranges from 0 to N1 minus 1.
  • Index0 is context coded.
  • the context is decided by information from neighbouring blocks. It can be determined based on the neighbouring mode information. For example, we select one context if more neighbouring blocks are CCLM modes (e.g. CCLM_LT, CCLM_L, CCLM_T) , and another context if more neighbouring blocks are MMLM mode (e.g. MMLM_LT, MMLM_L, MMLM_T) . For another example, we select one context if more neighbouring blocks are LT modes (e.g. CCLM_LT, MMLM_LT) , another context if more neighbouring blocks are L modes (e.g. CCLM_L, MMLM_L) , and another context if more neighbouring blocks are T modes (e.g. CCLM_T, MMLM_T) .
  • CCLM_LT e.g. CCLM_LT, CCLM_L, CCLM_T
  • MMLM_T MMLM_T
  • Index0 is truncated unary coded.
  • Set1 contains CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, and MMLM_T, and if the frequency the modes are signalled with are also in this order (i.e., CCLM_LT the most frequently signalled and MMLM_T the least frequently signalled)
  • the truncated unary code used can be designed as shown in Table 5:
  • Index1 ranges from 0 to N2 minus 1.
  • Index1 is context coded.
  • the context is decided by information from neighbouring blocks. It can be determined based on the neighbouring mode information. For example, we select one context if more neighbouring blocks are CCLM modes (e.g. CCLM_LT, CCLM_L, CCLM_T) , and another context if more neighbouring blocks are MMLM mode (MMLM_LT, MMLM_L, MMLM_T) . For another example, we select one context if more neighbouring blocks are LT modes (e.g. CCLM_LT, MMLM_LT) , another context if more neighbouring blocks are L modes (e.g. CCLM_L, MMLM_L) , and another context if more neighbouring blocks are T modes (e.g. CCLM_T, MMLM_T) .
  • CCLM_LT e.g. CCLM_LT, CCLM_L, CCLM_T
  • T modes e.g. CCLM_T, MM
  • Index1 is truncated unary coded.
  • Set2 contains CCLM_L, CCLM_T, MMLM_LT, and MMLM_L, and MMLM_T, and if the frequency the modes are signalled with are also in this order (CCLM is the most frequently signalled and MMLM_T is the least frequently signalled)
  • the truncated unary code used can be designed as shown in Table 6:
  • codewords for Index1 are shorter than codewords for index0.
  • Set1 contains CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, and MMLM_T
  • truncated unary code is used for both Index0 and Index1
  • CCLM_LT is selected to generate H1.
  • Table 7 An example of truncated unary code for Index0.
  • the modes selected to generate H1 and H2 is indicated by a joint index (denoted as index2) which is signalled/parsed in the bitstream.
  • N3 denote the number of different mode combinations that can be used to generate H1 and H2, i.e., all the different mode combinations selected from Set1 and Set2.
  • the Index2 ranges from 0 to N3 minus 1.
  • Set 1 contains CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, and MMLM_T.
  • N3 equals 15 and all the different combinations are:
  • Index2 is context coded.
  • the context is decided by information from neighbouring blocks. It can be determined based on the neighbouring mode information. For example, we select one context if more neighbouring blocks are CCLM modes (CCLM_LT, CCLM_L, CCLM_T) , and another context if more neighbouring blocks are MMLM mode (MMLM_LT, MMLM_L, MMLM_T) .
  • CCLM_LT LT modes
  • MMLM_LT L modes
  • T modes CCLM_T, MMLM_T
  • Index2 is truncated unary coded.
  • Set1 contains CCLM_LT, CCLM_L, CCLM_T, MMLM_LT, MMLM_L, and MMLM_T.
  • N3 equals 15.
  • the mode combinations be listed in the descending order of how frequently this mode combination is being signalled: (CCLM_LT, CCLM_L) , (CCLM_LT, CCLM_T) , (CCLM_LT, MMLM_LT) , (CCLM_LT, MMLM_L) , (CCLM_LT, MMLM_T) , ..., (MMLM_L, MMLM_T) .
  • the truncated unary code used can be designed as shown in Table 9:
  • the weighting to combine H1 and H2 is indicated by an index (denoted as index3) which is signalled or parsed in the bitstream.
  • Index3 indicates a candidate from a weight set.
  • the weight set (w h1 , w h2 ) can also be (3, 5) , (5, 3) , (-2, 10) , (10, -2) , (4, 4) , or any subset of the above weights.
  • the weighting is implicitly decided.
  • the weighting can be inferred as equal weighting.
  • the weighting can be decided based on the block size. For example, the weighting used is determined based on whether the block width or height is greater than a pre-determined value.
  • the value can be 2, 4, 8, 16 or any other allowed value for block width/height.
  • the weighting used is determined based on whether the block area is greater than a pre-determine value.
  • the value can be 4*4, 8*8 or other allowed sizes for block area.
  • the weighting is decided by mode information from neighbouring blocks. For example, if H1 is LT mode (CCLM_LT and MMLM_LT) and H2 is not a LT mode, and more neighbouring blocks are LT modes, then H1 has larger weight. For another example, if H1 is CCLM mode (e.g. CCLM_LT, CCLM_L, CCLM_T) and H2 is MMLM mode (e.g. MMLM_LT, MMLM_L, MMLM_T) , and more neighbouring blocks are CCLM mode, then H1 has larger weight.
  • CCLM mode e.g. CCLM_LT, CCLM_L, CCLM_T
  • H2 is MMLM mode (e.g. MMLM_LT, MMLM_L, MMLM_T)
  • H1 has larger weight.
  • the weighting is decided by the TIMD cost.
  • TIMD cost is defined as follows. For each mode, as shown in Fig. 7, the prediction samples of the template are generated using the reference samples of the template. For the case of CCP modes, the CCP model is derived based on the reconstruction samples on the reference lines. The number of reference lines can be more than 1. The prediction samples of the second colour component of the template are generated based on the first colour component samples of the template using the derived CCP model. Take CCLM modes as examples.
  • a CCLM_LT model can be derived using the reconstructed luma and chroma samples on the top and left reference lines
  • a CCLM_L model can be derived using the reconstructed luma and chroma samples on the left reference lines
  • a CCLM_T model can be derived using the reconstructed luma and chroma samples on the top reference lines.
  • the prediction chroma samples of the templates are then generated based on the reconstructed luma samples of the template using the derived linear model.
  • TIMD cost is calculated as the difference between the prediction and the reconstruction samples of the template.
  • the difference can be SATD, SAD (Sum of Absolute Difference) , a weighted sum of SATD and SAD, or other difference measures.
  • H1 is changed to be generated by a pre-defined intra mode.
  • H2 is changed to be generated by a pre-defined intra mode.
  • the only one candidate is inferred to be used.
  • the modes selected to generate H1 and H2 are explicitly signalled, and the weighting to combine two modes is implicitly decided.
  • the method to signal the modes selected can be separately signalling two modes, by signalling Index0 and Index1.
  • the method can also be jointly signalling two modes together, by signalling Index2.
  • w h2 TIMD_cost h1 / (TIMD_cost h1 +TIMD_cost h2 ) )
  • a flag is signalled/parsed at block-level to indicate whether to apply the blending mode to the current block.
  • the modes selected to generate H1 and H2 are implicitly decided, and the weighting to combine two modes is implicitly decided.
  • the modes are implicitly decided by the TIMD cost.
  • the two modes with the lowest TIMD costs are selected.
  • the TIMD cost of one mode selected is much larger than the TIMD cost of another mode selected, only the mode with smaller TIMD cost is used to form the final prediction.
  • two default modes e.g.
  • CCLM_LT, CCLM_L are selected.
  • two default modes e.g. CCLM_L, MMLM_L
  • two default modes e.g. CCLM_T, MMLM_T
  • the weighting is implicitly decided by TIMD cost.
  • w h1 TIMD_cost h2 / (TIMD_cost h1 +TIMD_cost h2 ) )
  • w h2 TIMD_cost h1 / (TIMD_cost h1 +TIMD_oost h2 ) )
  • the modes selected to generate H1 and H2 are implicitly decided.
  • the blending mode is disabled.
  • the intra-prediction mode blending method as described above can be implemented in an encoder side or a decoder side.
  • any of the proposed mode blending method can be implemented in an Intra coding module (e.g. Intra pred. 150 in Fig. 1B) in a decoder or an Intra coding module is an encoder (e.g. Intra Pred. 110 in Fig. 1A) .
  • Any of the proposed cross-component prediction mode (for, example, CCLM or any other type of cross-component prediction mode) methods can also be implemented as a circuit coupled to the intra coding module at the decoder or the encoder.
  • the decoder or encoder may also use additional processing unit to implement the required mode blending method. While the Intra Pred.
  • unit 110 in Fig. 1A and unit 150 in Fig. 1B are shown as individual processing units, they may correspond to executable software or firmware codes stored on a media, such as hard disk or flash memory, for a CPU (Central Processing Unit) or programmable devices (e.g. DSP (Digital Signal Processor) or FPGA (Field Programmable Gate Array) ) .
  • a media such as hard disk or flash memory
  • CPU Central Processing Unit
  • programmable devices e.g. DSP (Digital Signal Processor) or FPGA (Field Programmable Gate Array)
  • Fig. 11 illustrates a flowchart of an exemplary video coding system that incorporates a intra-prediction blending method according to an embodiment of the present invention.
  • the steps shown in the flowchart may be implemented as program codes executable on one or more processors (e.g., one or more CPUs) at the encoder side.
  • the steps shown in the flowchart may also be implemented based hardware such as one or more electronic devices or processors arranged to perform the steps in the flowchart.
  • input data associated with a current block comprising a first-colour block and a second-colour block are received in step 1110, wherein the input data comprise pixel data for the current block to be encoded at an encoder side or coded data associated with the current block to be decoded at a decoder side.
  • a first predictor is determined from a first intra-prediction candidate set in step 1120, wherein the first predictor provides first prediction for the second-colour block.
  • a second predictor is determined from a second intra-prediction candidate set in step 1130, wherein the second predictor provides second prediction for the second-colour block, and wherein at least one of the first predictor and the second predictor is derived based on the first-colour block using a cross-component model.
  • a final predictor is generated in step 1140 by blending the first predictor and the second predictor.
  • the second-colour block is encoded or decoded by using prediction data comprising the final predictor in step 1150.
  • Embodiment of the present invention as described above may be implemented in various hardware, software codes, or a combination of both.
  • an embodiment of the present invention can be one or more circuit circuits integrated into a video compression chip or program code integrated into video compression software to perform the processing described herein.
  • An embodiment of the present invention may also be program code to be executed on a Digital Signal Processor (DSP) to perform the processing described herein.
  • DSP Digital Signal Processor
  • the invention may also involve a number of functions to be performed by a computer processor, a digital signal processor, a microprocessor, or field programmable gate array (FPGA) .
  • These processors can be configured to perform particular tasks according to the invention, by executing machine-readable software code or firmware code that defines the particular methods embodied by the invention.
  • the software code or firmware code may be developed in different programming languages and different formats or styles.
  • the software code may also be compiled for different target platforms.
  • different code formats, styles and languages of software codes and other means of configuring code to perform the tasks in accordance with the invention will not depart from the spirit and scope of the invention.

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Abstract

L'invention concerne un procédé et un appareil de mélange de modes de prédiction intra. Selon le procédé pour le côté décodeur, un premier prédicteur est déterminé à partir d'un premier ensemble de candidats d'intra-prédiction, le premier prédicteur fournissant une première prédiction pour le bloc de seconde couleur. Un second prédicteur est déterminé à partir d'un second ensemble de candidats d'intra-prédiction, le second prédicteur fournissant une seconde prédiction pour le bloc de seconde couleur. Le premier prédicteur et/ou le second prédicteur sont dérivés sur la base du bloc de première couleur à l'aide d'un modèle inter-composantes. Un prédicteur final est généré par mélange du premier prédicteur et du second prédicteur. Le bloc de seconde couleur est codé ou décodé en utilisant des données de prédiction comprenant le prédicteur final.
PCT/CN2023/099802 2022-07-07 2023-06-13 Procédé et appareil de mélange de modes explicites dans des systèmes de codage vidéo WO2024007825A1 (fr)

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CN104871537A (zh) * 2013-03-26 2015-08-26 联发科技股份有限公司 色彩间帧内预测的方法
CN107079166A (zh) * 2014-10-28 2017-08-18 联发科技（新加坡）私人有限公司 用于视频编码的引导交叉分量预测的方法
CN113396584A (zh) * 2018-12-07 2021-09-14 弗劳恩霍夫应用研究促进协会 用于增强交叉分量线性模型参数的计算的稳健性的编码器、解码器和方法
WO2021244935A1 (fr) * 2020-06-03 2021-12-09 Nokia Technologies Oy Procédé, appareil et produit-programme informatique pour codage vidéo et décodage vidéo

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CN104871537A (zh) * 2013-03-26 2015-08-26 联发科技股份有限公司 色彩间帧内预测的方法
CN107079166A (zh) * 2014-10-28 2017-08-18 联发科技（新加坡）私人有限公司 用于视频编码的引导交叉分量预测的方法
CN113396584A (zh) * 2018-12-07 2021-09-14 弗劳恩霍夫应用研究促进协会 用于增强交叉分量线性模型参数的计算的稳健性的编码器、解码器和方法
WO2021244935A1 (fr) * 2020-06-03 2021-12-09 Nokia Technologies Oy Procédé, appareil et produit-programme informatique pour codage vidéo et décodage vidéo

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