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Article:High Performance Lossless Multimedia Data Compression through Improved Dictionary

by K. R. Kolhe, P. R. Devale, P. Shrivastava
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 10 - Number 1
Year of Publication: 2010
Authors: K. R. Kolhe, P. R. Devale, P. Shrivastava
10.5120/1444-1953

K. R. Kolhe, P. R. Devale, P. Shrivastava . Article:High Performance Lossless Multimedia Data Compression through Improved Dictionary. International Journal of Computer Applications. 10, 1 ( November 2010), 29-35. DOI=10.5120/1444-1953

@article{ 10.5120/1444-1953,
author = { K. R. Kolhe, P. R. Devale, P. Shrivastava },
title = { Article:High Performance Lossless Multimedia Data Compression through Improved Dictionary },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 10 },
number = { 1 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 29-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume10/number1/1444-1953/ },
doi = { 10.5120/1444-1953 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:58:40.489354+05:30
%A K. R. Kolhe
%A P. R. Devale
%A P. Shrivastava
%T Article:High Performance Lossless Multimedia Data Compression through Improved Dictionary
%J International Journal of Computer Applications
%@ 0975-8887
%V 10
%N 1
%P 29-35
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The advent of modern electronic world has opened up various fronts in multimedia interaction. They are used in various fields for various purposes of education, entertainment, research and many more. This has led to storage and retrieval of multimedia content regularly. But due to limitations of current technology the disk space and the transmission bandwidth fall behind in the race with the requirement of multimedia content. This imposes a need to compress multimedia content so that they can be easily stored requiring lesser space and easily transferred from one point to another. Some online dictionary based compression technique can be applied to reduce the data packet size. When the repetition rate of the same symbols within the data are high the compression techniques works very well. During the process of encoding and decoding, the building of online dictionary in the primary memory ensures the single pass over the data, and the dictionary need not to be transmitted over the network. Our proposed Improved Dictionary technique scans the data byte-wise, so that the chances of repetition of individual symbols are higher for text messages. Fixed length coding transmits fixed length codes for all dictionary entries. For bigger messages better optimization in terms of size reduction can be achieved through variable length coding with L-Z technique, where transmitted code length corresponding to individual dictionary entries will vary according to the requirement dynamically.

References
  1. Data Compression by Debra A. Lelewer and Daniel S. Hirschberg, http://www.ics.uci.edu
  2. Steven W. Smith, The Scientist and Engineer's Guide to Digital Signal Processing, http://www.dspguide.com
  3. [1.0] Introduction / Lossless Data Compression. (v1.1.1 / chapter 1 of 3 / 01 apr 05 / greg goebel / public domain), http://www.vectorsite.net
  4. Mark Nelson, Interactive Data Compression Tutor & The data compression book - -2nd Ed. by M&T books, http:// www.eee.bham. ac.uk
  5. LZW Data Compression by Mark Nelson, Dr. Dobb's Journal October, 1989.
  6. D. A. Huffman, ``A Method for the Construction of Minimum Redundancy Codes,'' Proceedings of the IRE, Vol. 40, pp. 1098--1101, 1952
  7. Jeffrey N. Ladino,”Data Compression Algorithms”, http://www.faqs.org/faqs/compression-faq/part2/section-1.html
  8. Article-Compressing and Decompressing Data using Java by Qusay H. Mahmoud with contributions from Konstantin Kladko February 2002
  9. The Data Compression Book, 2nd edition by Mark Nelson and Jean-loup Gailly, M&T Books, New York, NY 1995 ,ISBN 1-55851-434-1.
  10. T. A. Welch, ``A Technique for High-Performance Data Compression,'' Computer, pp. 8--18, 1984.
  11. J. Ziv and A. Lempel, ``Compression of Individual Sequences Via Variable-Rate Coding,'' IEEE Transactions on Information Theory, Vol. 24, pp. 530--536, 1978.
  12. J. Ziv and A. Lempel, ``A Universal Algorithm for Sequential Data Compression,'' IEEE Transactions on Information Theory, Vol. 23, pp. 337--342, 1977.
  13. K. Sayood, "Introduction to Data Compression".
  14. G. Held and T. R. Marshall, "Data and Image Compression: Tools and Techniques".
  15. D. Hankerson, P. D. Johnson, and G. A. Harris, "Introduction to Information Theory and Data Compression“.
  16. Storer, James A., Data Compression: Methods and Theory, Computer Science Press, Rockville, MD, 1988
  17. Soumit Chowdhury, Amit Chowdhury, S. R. Bhadra Chaudhuri, C.T. Bhunia “Data Transmission using Online Dynami Dictionary Based Compression Technique of Fixed and Variable Length Coding” published at International Conference on Computer Science and Information Technology, 2008.
  18. P.G.Howard and J.C.Vitter, “Arithmetic Coding for Data Compression,” Proceedings of the IEEE, vol. 82, no.6, 1994, pp.857-865
Index Terms

Computer Science
Information Sciences

Keywords

Multimedia Compression Lossless and lossy Compression LZ-77 LZ-78 LZW