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An Efficient Hidden Markov Model-Based Sample Adaptive Offset Mode Decision Algorithm for Versatile Video Coding

  • Feng Xing
  • , Yingwen Zhang
  • , Meng Wang
  • , Hengyu Man*
  • , Yongbing Zhang
  • , Shiqi Wang
  • , Xiaopeng Fan
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a highly efficient sample adaptive offset (SAO) mode decision algorithm. By leveraging both the directional correlations between the SAO and intra-prediction decisions, and the SAO decisions' spatial correlations, the SAO mode candidates are effectively pruned during the rate-distortion optimization process, accelerating the SAO encoding process with negligible BD-rate loss.

Original languageEnglish
Title of host publicationProceedings - DCC 2025
Subtitle of host publication2025 Data Compression Conference
EditorsAli Bilgin, James E. Fowler, Joan Serra-Sagrista, Yan Ye, James A. Storer
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages407
Number of pages1
ISBN (Electronic)9798331534714
DOIs
StatePublished - 2025
Externally publishedYes
Event2025 Data Compression Conference, DCC 2025 - Snowbird, United States
Duration: 18 Mar 202521 Mar 2025

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314

Conference

Conference2025 Data Compression Conference, DCC 2025
Country/TerritoryUnited States
CitySnowbird
Period18/03/2521/03/25

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