Fast mode decision algorithm for scalable video coding using bayesian theorem detection and markov process

Chia Hung Yeh*, Kai Jie Fan, Mei Juan Chen, Gwo Long Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The newest video coding standard called scalable video coding (SVC) provides broad applications in multimedia communications. SVC encoder consumes great computational complexity when compared to previous video coding standards. This paper presents a fast mode decision algorithm that speeds up the SVC encoding process through probabilistic analysis. The mode of the enhancement layer is first predicted by statistical analysis. Afterward, Bayesian theorem is utilized to detect whether the prediction mode of the current macroblock is the best or not. The mode is further predicted and refined by the Markov process. Experimental results show that the proposed algorithm significantly reduces computational complexity with negligible peak signal-to-noise ratio degradation and bitrate increase in the enhancement layers.

Original languageEnglish
Article number5401066
Pages (from-to)563-574
Number of pages12
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume20
Issue number4
DOIs
Publication statusPublished - 2010 Apr
Externally publishedYes

Keywords

  • Bayesian
  • Calable video coding
  • Coarse granular scalability
  • Markov
  • Mode decisions

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering

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