小波变换结合LZW压缩算法探究  

Data compression with wavelet transform and Lempel-Ziv-Welch(LZW) coding

作　　者：张凤元[1] 兰丽[1] 邹佳[1] 公绪艳[1] 杨东[1] 

机构地区：[1]北京化工大学信息科学与技术学院,北京100029

出　　处：《北京化工大学学报（自然科学版）》2013年第2期100-105,共6页Journal of Beijing University of Chemical Technology(Natural Science Edition)

基　　金：大学生创新创业训练计划国家重点资助项目(201210010125)

摘　　要：为解决传统桥梁振动数据压缩方法存在的问题,在深入分析小波变换原理的基础上,提出了一种小波变换结合LZW的压缩算法。该算法针对桥梁振动数据的特点,根据小波变换多分辨率分析的特性,对分解后各级的高频分量采用Donoho阀值压缩算法进行量化处理。而后采用改进的LZW编码压缩变换后的系数,对实测数据进行了压缩实验,结果证明小波变换结合LZW的数据压缩算法可有效提高数据压缩比,能量恢复系数优于10-4,压缩比小于9.25%。Based on the wavelet transform principle, a method of wavelet transform combined with Lempel -Ziv- Welch （LZW） coding has been proposed to solve the existing problems of traditional bridge vibration data compres- sion. In accordance of the characteristics of the bridge vibration data and the properties of wavelet transform-based multi-resolution anal.ysis, we adopted the Donoho threshold compression algorithm to quantify the high-frequency components that had been decomposed. Then with the improved LZW coding, we made further a depression of the bridge vibration data. To justify the proposed method, the measured data were simulated and the results indicated that the data compression based on the combination of LZW and wavelet transform can effectively improve the com- pression ratio, the energy recovery coefficient was smaller than 10-4, and the compression ratio was less than 9.25%

关 键 词：数据压缩 LZW 小波变换 Donoho阀值算法 桥梁振动 

分 类 号：TN911[电子电信—通信与信息系统]