计算机应用与软件2016，Vol.33Issue(6)：287-290,4.DOI:10.3969/j.issn.1000-386x.2016.06.068
基于大字典的LZW压缩算法的降熵改进
IMPROVEMENT OF ENTROPY REDUCTION FOR LZW COMPRESSION ALGORITHM BASED ON BIG DICTIONARY
陆振龙 1张箐2
作者信息
- 1. 中国科学院遥感与数字地球研究所 北京 100094
- 2. 中国科学院大学 北京 100094
- 折叠
摘要
Abstract
Based on the analysis of compression algorithm LZW,this paper puts forward an improved compression algorithm aimed at the deficiency of LZW that the average information entropy block of compressed data grows dramatically along with the increase of dictionary scale.This algorithm utilises the spatial correlation commonly existed in data,while saving the big dictionary it also narrows the range of the dictionary that actually used in each compression,so as to reduce the information entropy of the compressed data.The paper provides performance comparison between the improved algorithm and LZW compression algorithm,the result of experiment indicates that the improved algorithm achieves an optimisation by 2%~16.9% in the aspect of data information entropy after the compression is reduced.关键词
数据压缩/算法/信息熵/数据相关性Key words
Data compression/Algorithms/Entropy of information/Data correlation分类
信息技术与安全科学引用本文复制引用
陆振龙,张箐..基于大字典的LZW压缩算法的降熵改进[J].计算机应用与软件,2016,33(6):287-290,4.
