摘要
传统的二进小波变换对非2的整数幂的数据要进行大量的边界处理,针对这一局限性,提出一种自适应最优化小波变换算法。其核心是通过解析被处理数据长度来捕获其长度的最佳逼近值,实现边界处理的最优化;通过分解最佳逼近长度来获取各层次小波变换基数,实现小波变换基数选择的自适应。与二进小波变换相比,自适应最优化小波变换算法具有运算速度快,边界处理量少,数据压缩量大等特点。最后通过一个图像压缩的应用实例表明了此算法的可行性。
For the traditional dyadic wavelet transform, a lot of boundary treatments are needed when the data length is not 2 of integer power. Aiming at such a limitation, a new adaptive optimization wavelet transform algorithm was proposed. The core idea is analyzing the pending data to obtain the optimal approximate length, hence optimize the boundary treatment, while analyzing the optimal approximate length to select the wavelet transform bases adaptively. Compared with the traditional dyadic wavelet transform, the proposed algorithm hashigher speed, less boundary treatment, and greater data compression, etc. An image compression example was given to demonstrate the feasibility of the proposed algorithm.
出处
《重庆大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2008年第9期1028-1033,共6页
Journal of Chongqing University
基金
国家自然科学基金重点资助项目(50735008)
霍英东教育基金会11届青年教师基金资助项目(111057)
教育部长江学者和创新团队支持计划资助项目(PCSIRT0763)
关键词
边界处理
自适应最优化小波变换
最佳逼近长度
小坡变换基数
boundary treatment
adaptive optimization wavelet transform
optimal approximate length
wavelet trans{orm base