Cross-component compensation for intra-chroma block with block vector

Hyunki Jeong; Bumyoon Kim; Byeungwoo Jeon

doi:10.1117/12.3019354

2 May 2024 Cross-component compensation for intra-chroma block with block vector

Hyunki Jeong, Bumyoon Kim, Byeungwoo Jeon

Author Affiliations +

Proceedings Volume 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024; 131642N (2024) https://doi.org/10.1117/12.3019354
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2024, 2024, Langkawi, Malaysia

Abstract

Although VVC standardization is complete, there is a continued exploration of new video coding tools under the name of beyond VVC capability. In this effort, various new techniques such as cross-component or non-cross-component schemes have been developed so far, and among them, the direct block vector (DBV) mode, which is one of the non-cross-component prediction schemes, conducts block copy of the reference block by means of block vector information estimated using colocated luma area. However, in a dual tree structure, there can be multiple luma blocks in the co-located luma area corresponding to a chroma block, and one block vector which is estimated from the co-located luma area may not be optimal for the DBV mode. To overcome this, in this paper, a cross-component-based compensation method is proposed to use a convolution function for a chroma block prediction. Experiment under the AI configuration using the first 50 frames of sequences from JVET common test conditions shows 0.02% BDBR loss in Y channel but BDBR gains of 0.17% and 0.07% respectively in Cb and Cr channel with negligible encoding complexity increase against ECM-9.0.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hyunki Jeong, Bumyoon Kim, and Byeungwoo Jeon "Cross-component compensation for intra-chroma block with block vector", Proc. SPIE 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024, 131642N (2 May 2024); https://doi.org/10.1117/12.3019354

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KEYWORDS

Video coding

Nonlinear filtering

Statistical analysis

Statistical modeling

Visualization

Signal processing

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