Multiple description image coding for noisy channels by pairing transform coefficients

Yao Wang, Michael T. Orchard, Amy R. Reibman

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

Abstract

Multiple description coding (MDC) is a way of trading off coding gain with robustness to channel errors. This paper presents a new method for MDC using the framework of transform coding. Instead of using the Karhunen-Loeve transform (KLT) that decorrelates all the coefficients, we choose the transform bases so that the coefficients are correlated pair-wise. This is accomplished by rotating every two basis vectors in the KLT. Each pair of correlated coefficients are then split between two descriptions. Only 45° rotation is considered which leads to two balanced streams. In the actual implementation, the DCT is employed in place of the KLT and the rotation of transform bases is accomplished by rotating the DCT coefficients. Experimental results show that this method can lead to satisfactory image reconstruction from any one description with a relatively small (20% for "lena") overhead over a standard JPEG coder.

Original languageEnglish (US)
Title of host publication1997 IEEE 1st Workshop on Multimedia Signal Processing, MMSP 1997
EditorsYao Wang, Amy R. Reibman, B. H. Juang, Tsuhan Chen, Sun-Yuan Kung
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages419-424
Number of pages6
ISBN (Electronic)0780337808, 9780780337800
DOIs
StatePublished - 1997
Event1st IEEE Workshop on Multimedia Signal Processing, MMSP 1997 - Princeton, United States
Duration: Jun 23 1997Jun 25 1997

Publication series

Name1997 IEEE 1st Workshop on Multimedia Signal Processing, MMSP 1997

Other

Other1st IEEE Workshop on Multimedia Signal Processing, MMSP 1997
Country/TerritoryUnited States
CityPrinceton
Period6/23/976/25/97

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology

Fingerprint

Dive into the research topics of 'Multiple description image coding for noisy channels by pairing transform coefficients'. Together they form a unique fingerprint.

Cite this