The Complexity Optimization of Dependent Quantization in VVC by Delaying Starting Point

Shixuan Feng, Yifan Wang, Luge Wang, Fuzheng Yang, Shuai Wan

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

3 Scopus citations

Abstract

Compared with the video compression standard High Efficiency Video Coding (HEVC), the latest standard Versatile Video Coding (VVC) has achieved great improvement in coding efficiency due to the application of more sophisticated coding tools, which also results in high coding complexity. In this paper, to reduce the computational complexity of dependent quantization in VVC, an optimization method based on theoretical analysis of rate-distortion performance and statistical low-complexity model establishment is proposed to delay the starting point of the quantized path. Experimental results demonstrate that the proposed method can postpone the starting point to a position closer to the last non-zero quantized coefficient, reducing 3.57% encoding time, with a 0.42% increase in Bjntegaard delta bit-rate (BD-BR) compared with VVenC 1.0.0 under medium preset.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350359855
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 - Jeju, Korea, Republic of
Duration: 4 Dec 20237 Dec 2023

Publication series

Name2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023

Conference

Conference2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
Country/TerritoryKorea, Republic of
CityJeju
Period4/12/237/12/23

Keywords

  • Complexity Optimization
  • Dependent quantization
  • Video Coding
  • VVC

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