【作者】 黄晴；

【导师】 张书玲；

【作者基本信息】 西北大学 ， 计算数学， 2004， 硕士

【摘要】 图像数据压缩是数字图像处理技术所研究的主要内容，它在图像存储和图像传输方面有着非常重要的地位。小波变换和矢量量化都是现代图像编码领域的重要工具。矢量量化能够将小波系数有效地转化为比特流，实现图像数据压缩，为这一领域带来新的变革和生机。 针对以上背景，本文对传统的图像数据压缩方法、小波分析、矢量量化技术、小波变换编码以及WT／VQ系统在静态图像数据压缩领域的应用方法做了详尽的分析和总结，主要工作包括对一些常用的量化编码方法作了仿真实验：给出了一种基于多级矢量量化的图像渐进传输方法，实验表明该方法可以减少计算复杂度和存储空间，加快图像传输速度；给出了一种基于小波变换和矢量量化的图像压缩方法，实验表明该方法在高压缩比下仍可以较好的恢复图像，满足图像海量存储和快速传输的需要。更多还原

【Abstract】 Image compression is the main content of digital image processing technology,and it is vital to image storage and transmission. Wavelet transform and vector quantization both are important tools of modern image coding.Because vector quantization can turn wavelet coefficients efficiently into bit stream to realize image compression,it can bring innovation and vital force to this field.In this paper, the conventional methods of image compression,wavelet analysis,vector quantization, wavelet transform coding and the use of WT/VQ system in image compression are analysed and summarized detailedly.My own work are as follows. First, the common used quantization and coding methods are simulated;Second,a new image progressive transmission method based on MSVQ,is put forward.And simulation shows that it can reduce the computations and memory space,and quicken the transmission speed;Third,a novel image compressive method,based on wavelet transform and vector quantization,is given.And simulation shows that it can compress images efficiently under high compression ratio.更多还原