This chapter first introduces the principium of trellis coded vector quantization , then focuses on analyzing the algorithm of wavelet image classified weighted tcvq and its realization process , also gives tcvq application to wavelet image coding and its simulation results 首先分析了網格編碼矢量量化的原理,在第三章矢量量化的基礎上詳細介紹了小波圖像分類加權tcvq算法的原理和實現過程,并給出了tcvq在小波圖像量化中的應用實例和仿真結果。
Based on the analysis of image wavelet transformation and the space / frequency distributing characteristics of different subbands " coefficients , this dissertation fully exploits the following theories and methods : scalar quantization , vector quantization , trellis coded quantization , trellis coded vector quantization , vector classification , codebook expansion and weighted mean square error rule basing mankind visual characteristics , etc . from different angles of information amalgamation , it develops several innovative algorithms of image compression and coding , gives their realization schemes , and makes plentiful simulation tests 本文在分析了圖像小波變換的原理和子帶系數空間及頻率分布特點的基礎上,充分利用標量量化、矢量量化、網格編碼量化、網格編碼矢量量化、矢量分類、碼書擴展和基于人眼視覺特性的加權均方誤差準則等思想和方法,從信息融合的不同角度展開了對小波圖像的壓縮編碼研究,同時也討論了這些方法在靜止圖像量化中的具體應用。