[1]高怀远,陈英豪. 基于多参数的数据压缩算法[J].计算机技术与发展,2014,24(09):41-44.
 GAO Huai-yuan,CHEN Ying-hao. A Lossless Compression Algorithm Based on Multi-parameter[J].,2014,24(09):41-44.
点击复制

 基于多参数的数据压缩算法()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年09期
页码:
41-44
栏目:
智能、算法、系统工程
出版日期:
2014-09-10

文章信息/Info

Title:
 A Lossless Compression Algorithm Based on Multi-parameter
文章编号:
1673-629X(2014)09-0041-04
作者:
 高怀远陈英豪
 上海大学 自动化系
Author(s):
 GAO Huai-yuanCHEN Ying-hao
关键词:
 无损压缩元素合并1元即时码区分码
Keywords:
 lossless compressionelement mergingone-unit codedistinction code
分类号:
TP301.6
文献标志码:
A
摘要:
 通过对Huffman编码方法的研究,文中提出了一种基于多参数的数据无损压缩算法。基于原始数据集的元素个数统计,对原始数据集进行多次的合并,使合并后所得到的新数据集满足Huffman最佳编码要求,由此生成规模较小的数据合并对应表,并将数据编码分为一元即时码(前缀)和区分码(后缀)两个部分。数据多次合并的不同起始点为文中无损压缩方法的多参数,利用这些参数结合编码前缀及后缀即可唯一表示原始数据,去除了编码表。解码时无需逐位匹配即可复原原始数据。与传统方法相比,文中构造的基于多参数的数据无损压缩方法,编码结构简单,运算开销小,编解码效率较高。
Abstract:
 According to the study and analysis of Huffman coding method, propose a kind of lossless compression algorithm which is based on multi-parameter. Through sort and statistical for the number of original data,then merge them to meet the requirement of best Huffman encoding,thereby generating a data merging table which occupies less space,and encode the original data which is divided to one-unit code ( prefix code) and distinction code ( suffix code) . The start point of the data merging is the multi-parameter in this re-search. The original data can be determined by using these parameter. There is no need to bit by bit matching or generating encoding table when decoding. Compared with the original method,the lossless compression algorithm which is based on multi-parameter has simple coding structure and operating. It has higher efficiency in both coding and decoding.

相似文献/References:

[1]孙毅 韩坤亮.地震数据的无损压缩存储[J].计算机技术与发展,2011,(08):177.
 SUN Yi,HAN Kun-liang.Lossless Compression of Seismic Data[J].,2011,(09):177.
[2]高健,饶珺,孙瑞鹏.二元序列游长多次缩减的无损压缩编码方法[J].计算机技术与发展,2013,(06):31.
 GAO Jian,RAO Jun,SUN Rui-peng.A Lossless Compression Algorithm of Multiple Run-length Reduction for Binary Sequences[J].,2013,(09):31.
[3]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
 ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(09):1.
[4]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
 LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(09):5.
[5]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
 HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(09):13.
[6]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
 HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(09):21.
[7]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
 LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(09):25.
[8]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
 WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(09):29.
[9]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
 LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(09):34.
[10]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
 SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(09):38.

更新日期/Last Update: 2015-04-01