EZWアルゴリズムに基づいた進化的画像圧縮法

概要

論文の詳細を見る
A simple method based on the EZW algorithm is presented for improving image compression performance. Recent success in wavelet image coding is mainly attributed to recognition of the importance of data organization and representation. There have been several very competitive wavelet coders developed, namely, Shapiros EZW(Embedded Zerotree Wavelets)(1), Said and Pearlmans SPIHT(Set Partitioning In Hierarchical Trees)(2), and Bing-Bing Chais SLCCA(Significance-Linked Connected Component Analysis for Wavelet Image Coding)(3). The EZW algorithm is based on five key concepts: (1) a DWT(Discrete Wavelet Transform) or hierarchical subband decomposition, (2) prediction of the absence of significant information across scales by exploiting self-similarity inherent in images, (3) entropy-coded successive-approximation quantization, (4) universal lossless data compression which is achieved via adaptive arithmetic coding. and (5) DWT coefficients degeneration from high scale subbands to low scale subbands. In this paper, we have improved the self-similarity statistical characteristic in concept (5) and present a progressive image compression method.
社団法人電気学会の論文
2005-07-01