一种基于变位与反转变换的动态规划压缩算法  

A Dynamic Programming Compression Algorithm Based On Variable Identification And Reverse Transformation

作　　者：丁爱芬[1] 周华君[1] 石宜金[1] DING Ai-fen;ZHOU Hua-jun;SHI Yi-jin(Information School,Tourism and Culture College of Yunnan University,Lijiang Yunnan 674199,China)

机构地区：[1]云南大学旅游文化学院信息学院

出　　处：《西南师范大学学报（自然科学版）》2020年第1期37-41,共5页Journal of Southwest China Normal University(Natural Science Edition)

基　　金：云南省教育厅项目(2016ZDX261)

摘　　要：针对数据区域的集中化程度和平滑度特征,采用变位标识方法和反转变换策略,降低较大值数据区域的凹凸度,实现了数据无损压缩效率的提升.对比试验结果显示新算法的整体压缩效率优于原数据压缩算法和huffman统计编码.算法非常适合大数据环境的磁盘存储、网络传输和应用先进等流式压缩场景.Aiming at the concentration degree and smoothness of data region,using variable identification method and reverse transformation strategy to reduces the smoothness of large value data regions,the efficiency of the Lossless data compression algorithm is enhanced.The experimental results of comparison tests show that the compression efficiency of the new algorithm is better than the original data compression algorithm and the Huffman statistical coding.the algorithm is very suitable for flow compression such as disk storage,network transmission and application in big data environment.

关 键 词：无损数据压缩 变位标识 反转变换 流式压缩 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]