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A unifying framework for lossless and progressive image coding

delete2002-03-01
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PRE
AI
A
Amel Benazza‐Benyahia
J
Jean‐Christophe Pesquet *
DOI:10.1016/S0031-3203(01)00065-6delete
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Abstract

Abstract

En 中文
Progressive coding is a desirable feature for image database telebrowsing or image transmissions over low bandwidth channels. Furthermore, for some applications, exact image reconstruction is required. In this paper, we show that most of the lossless and progressive coders can be described by a common nonlinear subband decomposition scheme. This unifying framework provides useful guidelines for the analysis and improvement of the considered decomposition methods. Finally, we compare the respective performances of these methods in terms of Shannon entropy for several images and also evaluate their compression ability when combined with a hierarchical coding technique. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Keywords:
lossless image compression
progressive image reconstruction
nonlinear decompositions
subband coding
wavelets

Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
Papers:
1.4W
Citations:
4.5W

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