A unifying framework for lossless and progressive image coding

被引:4
|
作者
Benazza-Benyahia, A
Pesquet, JC
机构
[1] Univ Paris 12, Lab Syst Commun, F-77454 Marne la Vallee 2, France
[2] Ecole Super Commun Tunis, Dept Math Appl Signal & Commun, Ariana 2083, Tunisia
关键词
lossless image compression; progressive image reconstruction; nonlinear decompositions; subband coding; wavelets;
D O I
10.1016/S0031-3203(01)00065-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:627 / 638
页数:12
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