Block-layer bit allocation for quality constrained video encoding based on constant perceptual quality

Chao Wang, Xuanqin Mou, Wei Hong, Lei Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

In lossy image/video encoding, there is a compromise between the number of bits (rate) and the extent of distortion. Bits need to be properly allocated to different sources, such as frames and macro blocks (MBs). Since the human eyes are more sensitive to the difference than the absolute value of signals, the MINMAX criterion suggests to minimizing the maximum distortion of the sources to limit quality fluctuation. There are many works aimed to such constant quality encoding, however, almost all of them focus on the frame layer bit allocation, and use PSNR as the quality index. We suggest that the bit allocation for MBs should also be constrained in the constant quality, and furthermore, perceptual quality indices should be used instead of PSNR. Based on this idea, we propose a multi-pass block-layer bit allocation scheme for quality constrained encoding. The experimental results show that the proposed method can achieve much better encoding performance.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Visual Information Processing and Communication IV
DOIs
Publication statusPublished - 3 Jun 2013
EventVisual Information Processing and Communication IV - Burlingame, CA, United States
Duration: 6 Feb 20137 Feb 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8666
ISSN (Print)0277-786X

Conference

ConferenceVisual Information Processing and Communication IV
Country/TerritoryUnited States
CityBurlingame, CA
Period6/02/137/02/13

Keywords

  • Bit allocation
  • Block-layer
  • Constant quality
  • Perceptual quality
  • Quality constrained

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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