Simplifications of cross-component linear model
View Patent ↗A computing device performs a method of decoding video data by reconstructing a luma block corresponding to a chroma block; searching a sub-group of a plurality of reconstructed neighboring luma samples in a predefined order to identify a maximum luma sample and a minimum luma sample; computing a down-sampled maximum luma sample corresponding to the maximum luma sample; computing a down-sampled minimum luma sample corresponding to the minimum luma sample; generating a linear model using the down-sampled maximum luma sample, the down-sampled minimum luma sample, the first reconstructed chroma sample, and the second reconstructed chroma sample; computing down-sampled luma samples from luma samples of the reconstructed luma block, wherein each down-sampled luma sample corresponds to a chroma sample of the chroma block; and predicting chroma samples of the chroma block by applying the liner model to the corresponding down-sampled luma samples.
1. A method for encoding a video signal, comprising:
reconstructing a luma block corresponding to a chroma block, wherein the luma block is adjacent to a plurality of reconstructed neighboring luma samples, and wherein the chroma block is adjacent to a plurality of reconstructed neighboring chroma samples;
identifying, from a sub-group of the plurality of reconstructed neighboring luma samples, at least one maximum luma sample, wherein the at least one maximum luma sample corresponds to a first reconstructed chroma sample of the plurality of reconstructed neighboring chroma samples, the sub-group is composed of a predefined number of the reconstructed neighboring luma samples among the plurality of reconstructed neighboring luma samples;
identifying, from the sub-group of the plurality of reconstructed neighboring luma sample, at least one minimum luma sample, wherein the at least one minimum luma sample corresponds to a second reconstructed chroma sample of the plurality of reconstructed neighboring chroma samples;
fitting a linear model through the at least one maximum luma sample, the at least one minimum luma sample, the first reconstructed chroma sample, and the second reconstructed chroma sample; and
predicting chroma samples of the chroma block by applying the linear model to the luma samples of the luma block.
2. The method of claim 1 , wherein the chroma block and the luma block are encoded using a 4:4:4 chroma full sampling scheme, and wherein the chroma block and the luma block have the same resolution.
3. The method of claim 1 , wherein the plurality of reconstructed neighboring luma samples includes luma samples located above the reconstructed luma block and/or luma samples to left of the reconstructed luma block.
4. The method of claim 1 , wherein the fitting the linear model comprises fitting a linear equation through at least one data point associated with the at least one maximum luma sample and the first reconstructed chroma sample and at least one data point associated with the at least one minimum luma sample and the second reconstructed chroma sample.
5. A non-transitory computer readable storage medium storing a plurality of programs for execution by a computing device having one or more processors, wherein the plurality of programs, when executed by the one or more processors, cause the computing device to perform a method for encoding a video signal comprising:
reconstructing a luma block corresponding to a chroma block, wherein the luma block is adjacent to a plurality of reconstructed neighboring luma samples, and wherein the chroma block is adjacent to a plurality of reconstructed neighboring chroma samples;
identifying, from a sub-group of the plurality of reconstructed neighboring luma samples, at least one maximum luma sample, wherein the at least one maximum luma sample corresponds to a first reconstructed chroma sample of the plurality of reconstructed neighboring chroma samples, the sub-group is composed of a predefined number of the reconstructed neighboring luma samples among the plurality of reconstructed neighboring luma samples;
identifying, from the sub-group of the plurality of reconstructed neighboring luma sample, at least one minimum luma sample, wherein the at least one minimum luma sample corresponds to a second reconstructed chroma sample of the plurality of reconstructed neighboring chroma samples;
fitting a linear model through the at least one maximum luma sample, the at least one minimum luma sample, the first reconstructed chroma sample, and the second reconstructed chroma sample; and
predicting chroma samples of the chroma block by applying the linear model to the luma samples of the luma block.
6. The non-transitory computer readable storage medium of claim 5 , wherein the chroma block and the luma block are encoded using a 4:4:4 chroma full sampling scheme, and wherein the chroma block and the luma block have the same resolution.
7. The non-transitory computer readable storage medium of claim 5 , wherein the plurality of reconstructed neighboring luma samples includes luma samples located above the reconstructed luma block and/or luma samples to left of the reconstructed luma block.
8. The non-transitory computer readable storage medium of claim 5 , wherein the fitting the linear model comprises fitting a linear equation through at least one data point associated with the at least one maximum luma sample and the first reconstructed chroma sample and at least one data point associated with the at least one minimum luma sample and the second reconstructed chroma sample.
9. A non-transitory computer readable storage medium, comprising a bitstream stored therein, wherein, the bitstream is obtained by a method of encoding a video signal comprising:
reconstructing a luma block corresponding to a chroma block, wherein the luma block is adjacent to a plurality of reconstructed neighboring luma samples, and wherein the chroma block is adjacent to a plurality of reconstructed neighboring chroma samples;
identifying, from a sub-group of the plurality of reconstructed neighboring luma samples, at least one maximum luma sample, wherein the at least one maximum luma sample corresponds to a first reconstructed chroma sample of the plurality of reconstructed neighboring chroma samples, the sub-group is composed of a predefined number of the reconstructed neighboring luma samples among the plurality of reconstructed neighboring luma samples;
identifying, from the sub-group of the plurality of reconstructed neighboring luma sample, at least one minimum luma sample, wherein the at least one minimum luma sample corresponds to a second reconstructed chroma sample of the plurality of reconstructed neighboring chroma samples;
fitting a linear model through the at least one maximum luma sample, the at least one minimum luma sample, the first reconstructed chroma sample, and the second reconstructed chroma sample; and
predicting chroma samples of the chroma block by applying the linear model to the luma samples of the luma block.
10. The non-transitory computer readable storage medium of claim 9 , wherein the chroma block and the luma block are encoded using a 4:4:4 chroma full sampling scheme, and wherein the chroma block and the luma block have the same resolution.
11. The non-transitory computer readable storage medium of claim 9 , wherein the plurality of reconstructed neighboring luma samples includes luma samples located above the reconstructed luma block and/or luma samples to left of the reconstructed luma block.
12. The non-transitory computer readable storage medium of claim 9 , wherein the fitting the linear model comprises fitting a linear equation through at least one data point associated with the at least one maximum luma sample and the first reconstructed chroma sample and at least one data point associated with the at least one minimum luma sample and the second reconstructed chroma sample.