Informatics and Applications
2015, Volume 9, Issue 4, pp 78-84
PERFORMANCE IMPROVEMENT OF LEMPEL-ZIV-WELCH COMPRESSION ALGORITHM
- S. Frenkel
- M. Kopeetsky
- R. Molotkovski
- P. Borovsky
Abstract
The paper proposes two novel schemes which improve the dictionary-based Lempel-Ziv-Welch (LZW) compression algorithm. The first scheme proposes an improvement over the LZW algorithm by applying an exponential decay (ED) technique as a tool to manage and remove infrequently used entries in the LZW dictionary The presented results demonstrate that ED may be an efficient tool to manage and refresh the LZW dictionary. The achieved compression ratio (CR) is higher than in the traditional methods like Dictionary Reset (DR) and Least Recently Used (LRU). Another approach uses the Distance from Last Use (DLU) method. The DLU can be compressed by Huffman coding based on the frequencies of the phrases. The compression scheme, called HCD (Huffman Coding of Distance), was tested on different real-life data types such as text, programming code, audio, video and image files, characterized by different Shannon entropy The experimental results demonstrate that the ED and HCD scheme may provide higher CR, compared with the LZW algorithm.
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[+] About this article
Title
PERFORMANCE IMPROVEMENT OF LEMPEL-ZIV-WELCH COMPRESSION ALGORITHM
Journal
Informatics and Applications
2015, Volume 9, Issue 4, pp 78-84
Cover Date
2015-11-30
DOI
10.14357/19922264150408
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
(LZW) Dictionary Compression; dynamic dictionary; dictionary reset DR; least recently used LRU; exponential decay ED
Authors
S. Frenkel , , M. Kopeetsky ,
R. Molotkovski , and P. Borovsky
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Moscow State University of Information Technologies, Radioengineering, and Electronics, 78 Vernadskogo Ave., Moscow 119454, Russian Federation
Department of Software Engineering, Shamoon College of Engineering, Basel/Bialik Sts, Beer-Sheva, Israel
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