Distributed stereo image coding with improved disparity and noise estimation

David Chen, David Varodayan, Markus Flierl, Bernd Girod

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Distributed coding of correlated grayscale stereo images is effectively addressed by a recently proposed codec that learns block-wise disparity at the decoder. Based on the Slepian-Wolf theorem, one image can be transmitted at a rate approaching the conditional entropy if the other image is referenced as side information at the decoder. This paper improves the methods in the decoder design by refining disparity estimates to pixel resolution, generating more accurate initial disparity estimates, and modeling noise as a nonstationary random field. The new decoder enables up to an additional 9 percent bit rate savings for lossless coding. When the rate is insufficient for lossless reconstruction, the new decoder improves PSNR and significantly reduces visually unpleasant blocking artifacts.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages1137-1140
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Data compression
  • Estimation
  • Image coding
  • Stereo vision

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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