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Fast Coding Unit Partition Decision for Intra Prediction in Versatile Video Coding

  • Harbin Institute of Technology
  • De Montfort University

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

Abstract

In recent years, the state-of-the-art video coding standard – Versatile Video Coding (VVC) has been widely investigated. VVC achieves impressive performance by adopting more flexible partitioning method compared to its predecessor High Efficiency Video Coding (HEVC). However, the superior performance is realized at the expense of huge time consumption and increasing hardware costs, which obstructs its applications in real-time scenarios. To address this problem, we present a fast implementation for the decision process of the nested multi-type tree (QTMT) partitioning, and it significantly reduces the run-time of encoder while maintaining almost the same coding performance. Firstly, the inherent texture property of source frame is utilized to identify the prediction depth for Coding Tree Unit (CTU). Then, the spatial correlation is used to further narrow the depth range down. Finally, we skip unnecessary partition types according to the predicted Coding Unit (CU) depth, which is determined by the above predicted CTU depth and adjacent CU’s depth together. Experimental results demonstrate the effectiveness of our proposed method in VVC Test Model (VTM). Compared with the original implementation of the VTM4.0 anchor, the proposed algorithm achieves an average of 49.01% encoding time savings, accompanied by only an increase of 2.18% in Bj ϕ ntegaard delta Bitrate (BDBR) and a loss of 0.138 dB in Bj ϕ ntegaard delta PSNR (BDPSNR).

Original languageEnglish
Title of host publicationImage and Graphics - 11th International Conference, ICIG 2021, Proceedings
EditorsYuxin Peng, Shi-Min Hu, Moncef Gabbouj, Kun Zhou, Michael Elad, Kun Xu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages700-711
Number of pages12
ISBN (Print)9783030873547
DOIs
StatePublished - 2021
Event11th International Conference on Image and Graphics, ICIG 2021 - Haikou, China
Duration: 6 Aug 20218 Aug 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12888 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Image and Graphics, ICIG 2021
Country/TerritoryChina
CityHaikou
Period6/08/218/08/21

Keywords

  • Partition decision
  • Spatial correlation
  • Texture property
  • Versatile Video Coding

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