Video Coding With Cross-Component Sample Offset

Beyond the exploration of traditional spatial, temporal and subjective visual signal redundancy in image and video compression, recent research has focused on leveraging cross-color component redundancy to enhance coding efficiency. Cross-component coding approaches are motivated by the statistical correlations among different color components, such as those in the Y'CbCr color space, where luma (Y) color component typically exhibits finer details than chroma (Cb/Cr) color components. Inspired by previous cross-component coding algorithms, this paper introduces a novel in-loop filtering approach named Cross-Component Sample Offset (CCSO). CCSO utilizes co-located and neighboring luma samples to generate correction signals for both luma and chroma reconstructed samples. It is a multiplication-free, non-linear mapping process implemented using a look-up-table. The input to the mapping is a group of reconstructed luma samples, and the output is an offset value applied on the center luma or co-located chroma sample. Experimental results demonstrate that the proposed CCSO can be applied to both image and video coding, resulting in improved coding efficiency and visual quality. The method has been adopted into an experimental next-generation video codec beyond AV1 developed by the Alliance for Open Media (AOMedia), demonstrating average -0.81% and -0.69% coding gain on PSNR and VMAF quality metric, respectively, under random access configuration. Additionally, CCSO notably improves the subjective visual quality.

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Publication Details

Journal
IEEE Transactions on Image Processing
Published
2025-01-01
DOI
https://doi.org/10.1109/tip.2025.3579992
Citations
4
Primary Topic
Advanced Data Compression Techniques
Type
article
Field-Weighted Citation Impact
5.10
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article

Video Coding With Cross-Component Sample Offset

Tianqi Liu, Han Gao, Shan Liu, Xin Zhao
4 citations
IEEE Transactions on Image Processing
Advanced Data Compression Techniques
5.10
article

Video Coding With Cross-Component Sample Offset

Tianqi Liu, Han Gao, Shan Liu, Xin Zhao
article en
4 citations

Abstract

Beyond the exploration of traditional spatial, temporal and subjective visual signal redundancy in image and video compression, recent research has focused on leveraging cross-color component redundancy to enhance coding efficiency. Cross-component coding approaches are motivated by the statistical correlations among different color components, such as those in the Y'CbCr color space, where luma (Y) color component typically exhibits finer details than chroma (Cb/Cr) color components. Inspired by previous cross-component coding algorithms, this paper introduces a novel in-loop filtering approach named Cross-Component Sample Offset (CCSO). CCSO utilizes co-located and neighboring luma samples to generate correction signals for both luma and chroma reconstructed samples. It is a multiplication-free, non-linear mapping process implemented using a look-up-table. The input to the mapping is a group of reconstructed luma samples, and the output is an offset value applied on the center luma or co-located chroma sample. Experimental results demonstrate that the proposed CCSO can be applied to both image and video coding, resulting in improved coding efficiency and visual quality. The method has been adopted into an experimental next-generation video codec beyond AV1 developed by the Alliance for Open Media (AOMedia), demonstrating average -0.81% and -0.69% coding gain on PSNR and VMAF quality metric, respectively, under random access configuration. Additionally, CCSO notably improves the subjective visual quality.

IEEE Transactions on Image ProcessingVol. 34
KLA (United States) (US)
Openalex Percentile: Top 5%
Advanced Data Compression Techniques
5.10
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