CFP last date
01 May 2024
Reseach Article

Data Compression Methods and Analysis

by Nazmun Nahar, Md Jayedul Haque
Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 7
Year of Publication: 2017
Authors: Nazmun Nahar, Md Jayedul Haque

Nazmun Nahar, Md Jayedul Haque . Data Compression Methods and Analysis. Communications on Applied Electronics. 7, 7 ( Oct 2017), 1-7. DOI=10.5120/cae2017652630

@article{ 10.5120/cae2017652630,
author = { Nazmun Nahar, Md Jayedul Haque },
title = { Data Compression Methods and Analysis },
journal = { Communications on Applied Electronics },
issue_date = { Oct 2017 },
volume = { 7 },
number = { 7 },
month = { Oct },
year = { 2017 },
issn = { 2394-4714 },
pages = { 1-7 },
numpages = {9},
url = { },
doi = { 10.5120/cae2017652630 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2023-09-04T20:01:35.560819+05:30
%A Nazmun Nahar
%A Md Jayedul Haque
%T Data Compression Methods and Analysis
%J Communications on Applied Electronics
%@ 2394-4714
%V 7
%N 7
%P 1-7
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

During the advanced era of modern science data has become a salient part of research as well as other methodologies. Along with the cumulative use of data, data redundancy has become an ache for both user and researcher end. Not only communication but also generic file compression technologies are using different kind of efficient data compression methods massively day by day. This paper concerns with a variety of data compression methods with some efficient innovation. The purpose of data compression is to wan redundancy in stored or communicated data. Data compression has important application in the area of file storage and distributed system. This paper will provide an overture of several compression methods and will formulate new methods that may improve compression ratio and lessen error in the reconstructed data. In this work the data compression techniques: Huffman, Run-Length, LZW, LZW-Huffman, Huffman-LZW, Run-Length-LZW and LZW-Run-Length are used to compress different types of multimedia formats such as images and text, which depicts the discrepancy of various data compression methods on image and text file.

  1. WELCH, T. A. 1984.” A technique for high-performance data compression”. IEEE Comput. 17, 6, 8–19. 9.
  2. ZIV, J. AND LEMPEL, A. 1978. “Compression of individual sequences via variable-rate coding”. IEEE Trans. Inform. Theory 24, 5, 530–536.
  3. ZIV, J. AND LEMPEL, A. 1977. A “universal algorithm for sequential data compression”. IEEE Trans. Inform. Theory 23, 3, 337–343.
  4. Campos, A. S. E. Run Length Encoding. Available: (last accessed July 2012).
  5. Connel, J. B., “A Huffman-Shannon-Fano Code”, Proc. IEEE 61 (Jul. 1973), 1046-1047.
  6. Gallager, R. G., “Variations on a theme by Huffman”, IEEE Trans. Inf. Theory IT-24, 6(Nov. 1978), 668-674.
  7. Hashemian, R., “Memory efficient and high-speed search Huffman coding”, IEEE Trans. Comm. 43(10)(1995)2576-2581.
  8. M. N. Huda, "Study on Huffman Coding," Graduate Thesis, 2004.
  9. S. Porwal, Y. Chaudhary, J. Joshi and M. Jain , “ Data Compression Methodologies for Lossless Data and Comparison between Algorithms” International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 2, March 2013.
  10. Huffman, D. A. : ‘A Method for the Construction of Minimum Redundancy Codes", Proc. IRE, Vol. 40, No. 9, pp. 1098-1101, September 1952.
  11. Buro. M.: ‘On the maximum length of Huffman codes’, Information Processing Letters, Vol. 45, No.5, pp. 219-223, April 1993.
  12. Chen, H. C. and Wang, Y. L. and Lan, Y. F.: ‘A Memory Efficient and Fast Huffman Decoding Algorithm’Information Processing Letters, Vol. 69, No. 3, pp. 119- 122, February 1999.
  13. Mashhur Sattorov, Heau-Jo Kang. :’ Huffman Coding Approach to Performance of 16-QAM/OFDM’.
  14. Wong, S. and Cotofana, D. and Vassiliadis, S.: General-Purpose Processor Huffman Encoding Extension, Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC 2000), pp. 158-163, Las Vegas, Nevada, March 2000.
  15. S. Shanmugasundaram and R. Lourdusamy, “A Comparative Study of Text Compression Algorithms” International Journal of Wisdom Based Computing, Vol. 1 (3), December 2011.
  16. Kao, Ch., H, and Hwang, R. J.: 'Information Hiding in Lossy Compression Gray Scale Image', Tamkang Journal of Science and Engineering, Vol. 8, No 2, 2005, pp. 99- 108.
  17. Ueno, H., and Morikawa, Y.: 'A New Distribution Modeling for Lossless Image Coding Using MMAE Predictors'. The 6th International Conference on Information Technology and Applications, 2009.
  18. Grgic, S., Mrak, M., and Grgic, M.: 'Comparison of JPEG Image Coders'. University of Zagreb, Faculty of Electrical Engineering and Computing Unska 3 / XII, HR-10000 Zagreb, Croatia.
  19. Md Jayedul Haque and Mohammad Nurul Huda. Study on Data Compression Technique. International Journal of Computer Applications 159(5):6-13, February 2017.
  20., accessed Mar 2011.
  21. Fano R.M., “The Transmission of Information”, Technical Report No. 65, Research Laboratory of Electronics, M.I.T., Cambridge, Mass.; 1949.
Index Terms

Computer Science
Information Sciences


Lempel-Ziv-Welch (LZW) Huffman Run-Length