Context formation by mutual information maximization

Zhen Liu, Lina Karam

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

1 Scopus citations

Abstract

In this paper, the problem of how to form the contexts for context-based entropy coding is studied. The mutual information (MI) between the context and the encoded data is used to measure the context optimality. The MI decreases when contexts are combined together. Given a desired number of contexts, an algorithm is proposed for finding the set of contexts by iteratively combining the pairs that give the minimum MI reduction. The proposed algorithm is applied to form the contexts for the zero coding (ZC) primitive of the JPEG2000 image compression standard. Experimental results show that the number of contexts used as part of the standard can be reduced without loss in the coding performance.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
Volume3
StatePublished - 2002
EventInternational Conference on Image Processing (ICIP'02) - Rochester, NY, United States
Duration: Sep 22 2002Sep 25 2002

Other

OtherInternational Conference on Image Processing (ICIP'02)
CountryUnited States
CityRochester, NY
Period9/22/029/25/02

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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