TEXT COMPRESSION ALGORITHMS - A COMPARATIVE STUDY
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffc09b080000007464010001000100
Data Compression may be defined as the science and art of the representation of information in a crisply condensed form. For decades, Data compression has been one of the critical enabling technologies for the ongoing digital multimedia revolution. There are a lot of data compression algorithms which are available to compress files of different formats. This paper provides a survey of different basic lossless data compression algorithms. Experimental results and comparisons of the lossless compression algorithms using Statistical compression techniques and Dictionary based compression techniques were performed on text data. Among the Statistical coding techniques, the algorithms such as Shannon-Fano Coding, Huffman coding, Adaptive Huffman coding, Run Length Encoding and Arithmetic coding are considered. Lempel Ziv scheme which is a dictionary based technique is divided into two families: one derived from LZ77 (LZ77, LZSS, LZH, LZB and LZR) and the other derived from LZ78 (LZ78, LZW, LZFG, LZC and LZT). A set of interesting conclusions are derived on this basis.

Authors
S. Senthil 1 and L. Robert 2
1Vidyasagar College of Arts and Science, Tamil Nadu, India,2Community College in Al-Qwaiya, Shaqra University, KSA (Government Arts College, Coimbatore),Tamil Nadu, India

Keywords
Encoding, Decoding, Lossless Compression, Dictionary Methods
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
111012000120
Published By :
ICTACT
Published In :
ICTACT Journal on Communication Technology
( Volume: 2 , Issue: 4 , Pages: 444-451 )
Date of Publication :
December 2011
Page Views :
688
Full Text Views :
13

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.