Unified Cross-Component Linear Model in VVC Based on a Subset of Neighboring Samples

Junyan Huo, Hongqing Du, Xinwei Li, Shuai Wan, Hui Yuan, Yanzhuo Ma, Fuzheng Yang

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

To compress industrial video content efficiently, H.266/Versatile Video Coding (VVC) introduces cross-component linear model (CCLM) prediction as a new coding tool, in which chroma components are predicted from the luma component based on a linear model. In this article, we propose a subset-based CCLM (S-CCLM), in which the model parameters are derived based on a subset of neighboring samples. To choose the most proper subset, we build the relationship between the prediction error and the geometric distance and resolve the optimal subset construction problem by minimizing the geometric distance. With the well-designed subset, a weight-guided parameter derivation algorithm is further proposed to improve the accuracy of the model parameters. The experimental results show that the proposed S-CCLM can achieve Bjontegaard delta bitrate (BD-rate) reductions of 0.14%, 0.64%, and 0.75% for the Y, Cb, and Cr components, respectively, when the number of samples in the subset, N, is 4 and BD-rate reductions of 0.22%, 0.80%, and 0.95% when N is 8. Given a small fixed N, fewer memory access operations are needed during the CCLM calculation, and a unified CCLM process can be achieved for coding blocks with different sizes and different modes. Due to its hardware-friendly architecture, the S-CCLM has been partially adopted by H.266/VVC.

Original languageEnglish
Pages (from-to)8654-8663
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume18
Issue number12
DOIs
StatePublished - 1 Dec 2022

Keywords

  • Cross-component linear model (CCLM)
  • H.266
  • subset construction
  • unified derivation
  • versatile video coding (VVC)
  • video coding

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