基于树结构矢量分类的小波图像图编码矢量量化

本文基于零树编码，矢量分类和网络编码量化的思想，提出了对小波图象采用树结构矢量组合和分类后进行网络编码矢量量化的新方法，该方法充分利用了带系统的带间和带内的相关性，分类信息上中用比特数少，对重要类矢量实行加权网络编码矢量量化，利用卷积编码扩展信号空间以增大量化信号间的欧氏距离，用维特比算法搜索最优量化序列，并采用基于人眼视觉性特性的加权均方误差准则作为失真度量和码字匹配，提高了量化增益，仿真结果表明，该方法编码计算复杂度适中，解码简单，可达到很好的压缩效果。

Trellis coded vector quantiztion of wavelet image using tree structure vector combination and classification

Based on zerotree coding,vector classification and trellis coded quantizaion,A new method which performs tree structure vector formation and classification to wavelet image then uses TCVQ is proposed the method utilizes correlation between the subbands and within the subbands fully,the classified information need a little bites to express In order to improve quantizaiton gain,the important vectors are quantified by weighted TCVQ,which uses convolutional coding to expand signal space and increase Euclid distance between signals,uses Viterbi algorithm to find a optimized survived quantized sequence and adopts weighted mean square error rule to that using mankind visual characteristic to measure the distortion Simulation states that this method has modest encoding complexity with simple decoding and it can achieve much better compression effect