基于模糊剪枝的最优小波包基图像压缩算法  

Best Wavelet Packet Basis Image Compression Algorithm Based on Fuzzy Cut

作　　者：欧阳春娟[1,2] 孙凌宇[1] 朱平[1] 

机构地区：[1]井冈山大学电子与信息工程学院,江西吉安343009 [2]深圳大学信息工程学院,广东深圳518060

出　　处：《计算机工程》2011年第8期236-237,240,共3页Computer Engineering

基　　金：国家自然科学基金资助项目(60576055);江西省教育厅科技计划基金资助项目(GJJ11538;GJJ10201)

摘　　要：提出一种基于模糊剪枝的最优小波包基图像压缩算法。图像经完全小波包分解后,以每个小波包分解的高频系数占所有高频系数的比值及每个节点子女熵值与原节点熵值的比值作为模糊系统的2个输入;通过构造模糊规则,将小波包系数分为裁剪类和保留类,由保留类构造最优小波包基;根据最优小波包基,在不同的小波包分解层次上采用不同的阈值对图像进行压缩。仿真实验结果表明,该算法与比特-失真率优化算法和小波包最优树全局阈值压缩算法相比性能更优。This paper proposes a fuzzy-cut best wavelet packet image compression algorithm.The ratio of each high-frequency coefficient to the total high-frequency coefficients of wavelet packet decomposition and the ratio of each node’s children entropy to the original node entropy are defined as two inputs of the fuzzy system.The wavelet packet coefficients are divided into cutting part and the best wavelet packet is got by the reservations parts.The image is compressed by using the different thresholds on different wavelet packet transform level based on the best wavelet packet.Simulation results show that the algorithm has better performance than the rate-distortion and the whole thresholds wavelet packet image compression algorithm.

关 键 词：小波包变换 最优小波包基 模糊系统 图像压缩 模糊剪枝 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]