Mutual information-based analysis of JPEG2000 contexts

Zhen Liu, Lina Karam

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Context-based arithmetic coding has been widely adopted in image and video compression and is a key component of the new JPEG2000 image compression standard. In this paper, the contexts used in JPEG2000 are analyzed using the mutual information, which is closely related to the compression performance. We first show that, when combining the contexts, the mutual information between the contexts and the encoded data will decrease unless the conditional probability distributions of the combined contexts are the same. Given I, the initial number of contexts, and F, the final desired number of contexts, there are S(I, F) possible context classification schemes where S(I, F) is called the Stirling number of the second kind. The optimal classification scheme is the one that gives the maximum mutual information. Instead of using an exhaustive search, the optimal classification scheme can be obtained through a modified generalized Lloyd algorithm with the relative entropy as the distortion metric. For binary arithmetic coding, the search complexity can be reduced by using dynamic programming. Our experimental results show that the JPEG2000 contexts capture the correlations among the wavelet coefficients very well. At the same time, the number of contexts used as part of the standard can be reduced without loss in the coding performance.

Original languageEnglish (US)
Pages (from-to)411-422
Number of pages12
JournalIEEE Transactions on Image Processing
Volume14
Issue number4
DOIs
StatePublished - Apr 2005

Fingerprint

JPEG2000
Image compression
Mutual Information
Dynamic programming
Probability distributions
Arithmetic Coding
Entropy
Si
Image Compression
Context
Stirling numbers of the second kind
Video Compression
Relative Entropy
Exhaustive Search
Wavelet Coefficients
Conditional probability
Conditional Distribution
Dynamic Programming
Probability Distribution
Compression

Keywords

  • Context-based arithmetic coding
  • JPEG2000
  • Mutual information

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Cite this

Mutual information-based analysis of JPEG2000 contexts. / Liu, Zhen; Karam, Lina.

In: IEEE Transactions on Image Processing, Vol. 14, No. 4, 04.2005, p. 411-422.

Research output: Contribution to journalArticle

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