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Computer Science

Study on Data Compression Technique

Profile image of Md Jayedul HaqueMd Jayedul Haque

2017, International Journal of Computer Applications

https://doi.org/10.5120/IJCA2017912416
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3 pages

Abstract

In this current age both communication and generic file compression technologies are using different kind of efficient data compression methods massively. This paper surveys a variety of data compression methods. The aim of data compression is to reduce 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 overview of several compression methods and will formulate new algorithms that may improve compression ratio and abate error in the reconstructed data. In this work the data compression techniques: Huffman, Run-Length, LZW, Shannon-Fano, Repeated-Huffman, Run-Length-Huffman, and Huffman-Run-Length are tested against different types of multimedia formats such as images and text, which shows the difference of various data compression methods on image and text file.

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Study on Data Compression Technique {tag} {/tag} International Journal of Computer Applications Foundation of Computer Science (FCS), NY, USA Volume 159 - Number 5 Year of Publication: 2017 Authors: Md Jayedul Haque, Mohammad Nurul Huda 10.5120/ijca2017912416 {bibtex}2017912416.bib{/bibtex} Abstract In this current age both communication and generic file compression technologies are using different kind of efficient data compression methods massively. This paper surveys a variety of data compression methods. The aim of data compression is to reduce 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 overview of several compression methods and will formulate new algorithms that may improve compression ratio and abate error in the reconstructed data. In this work the data compression techniques: Huffman, Run-Length, LZW, Shannon-Fano, Repeated-Huffman, Run-Length-Huffman, and Huffman-Run-Length are tested against different types of multimedia formats such as images and text, which shows the difference of various data compression methods on image and text file. References 1. Connel, J. B., “A Huffman-Shannon-Fano Code”, Proc. IEEE 61 (Jul. 1973), 1046-1047. 1/3 Study on Data Compression Technique 2. Gallager, R. G., “Variations on a theme by Huffman”, IEEE Trans. Inf. Theory IT-24, 6(Nov. 1978), 668-674. 3. Hashemian, R., “Memory efficient and high-speed search Huffman coding”, IEEE Trans. Comm. 43(10)(1995)2576-2581. 4. M. N. Huda, "Study on Huffman Coding," Graduate Thesis, 2004. 5. 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. 6. Campos, A. S. E. Run Length Encoding. Available: http://www.arturocampos.com/ac_rle.html (last accessed July 2012). 7. WELCH, T. A. 1984.” A technique for high-performance data compression”. IEEE Comput. 17, 6, 8–19. 9. 8. ZIV, J. AND LEMPEL, A. 1978. “Compression of individual sequences via variable-rate coding”. IEEE Trans. Inform. Theory 24, 5, 530–536. 9. ZIV, J. AND LEMPEL, A. 1977. A “universal algorithm for sequential data compression”. IEEE Trans. Inform. Theory 23, 3, 337–343. 10. S. Shanmugasundaram and R. Lourdusamy, “A Comparative Study of Text Compression Algorithms” International Journal of Wisdom Based Computing, Vol. 1 (3), December 2011. 11. 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. 12. 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. 13. 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. 14. http://sipi.usc.edu, accessed Mar 2011. 15. http://www.gutenberg.org/cache/epub/571/pg571.txt. 16. Fano R.M., “The Transmission of Information”, Technical Report No. 65, Research Laboratory of Electronics, M.I.T., Cambridge, Mass.; 1949. 17. Buro. M.: ‘On the maximum length of Huffman codes’, Information Processing Letters, Vol. 45, No.5, pp. 219-223, April 1993. 18. 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. 19. Ostadzadeh, S. A. and Elahi, B. M. and Zeialpour, Z. T, and Moulavi, M. M and Bertels, K. L. M, : A Two Phase Practical Parallel Algorithm for Construction of Huffman Codes, Proceedings of International Conference on Parallel and Distributed Processing Techniques and Applications, pp. 284-291, Las Vegas, USA, June 2007. 20. 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. 21. Huffman, D. A. : ‘A Method for the Construction of Minimum Redundancy Codes", Proc. IRE, Vol. 40, No. 9, pp. 1098-1101, September 1952. 22. Doa'a Saad El-Shora & Ehab Rushdy Mohamed. A "Performance Evalution of Data 2/3 Study on Data Compression Technique Compression Techniques Versus Differenct Types of Data" . Article : (IJCSIS) International Journal of Computer Science and Information Security, Vol. 11, No. 12, December 2013 23. Kashfia Sailunaz, Mohammed Rokibul Alam Kotwal and Dr.Mohammad Nurul Huda. Article: Data Compression Considering Text Files. International Journal of Computer Applications 90(11):27-32, March 2014. Full text available. Index Terms Computer Science Information Sciences Keywords Lempel-Ziv-Welch (LZW), Huffman, Shannon-Fano, Data Compression, Benchmark file, Data Structure, Algorithms 3/3

References (20)

  1. Connel, J. B., "A Huffman-Shannon-Fano Code", Proc. IEEE 61 (Jul. 1973), 1046-1047.
  2. Gallager, R. G., "Variations on a theme by Huffman", IEEE Trans. Inf. Theory IT-24, 6(Nov. 1978), 668-674.
  3. Hashemian, R., "Memory efficient and high-speed search Huffman coding", IEEE Trans. Comm. 43(10)(1995)2576-2581.
  4. M. N. Huda, "Study on Huffman Coding," Graduate Thesis, 2004.
  5. 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.
  6. Campos, A. S. E. Run Length Encoding. Available: http://www.arturocampos.com/ac_rle.html (last accessed July 2012).
  7. WELCH, T. A. 1984." A technique for high-performance data compression". IEEE Comput. 17, 6, 8-19. 9.
  8. ZIV, J. AND LEMPEL, A. 1978. "Compression of individual sequences via variable-rate coding". IEEE Trans. Inform. Theory 24, 5, 530-536.
  9. ZIV, J. AND LEMPEL, A. 1977. A "universal algorithm for sequential data compression". IEEE Trans. Inform. Theory 23, 3, 337-343.
  10. S. Shanmugasundaram and R. Lourdusamy, "A Comparative Study of Text Compression Algorithms" International Journal of Wisdom Based Computing, Vol. 1 (3), December 2011.
  11. 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.
  12. 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.
  13. 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. 14. http://sipi.usc.edu, accessed Mar 2011.
  14. Fano R.M., "The Transmission of Information", Technical Report No. 65, Research Laboratory of Electronics, M.I.T., Cambridge, Mass.; 1949.
  15. Buro. M.: 'On the maximum length of Huffman codes', Information Processing Letters, Vol. 45, No.5, pp. 219-223, April 1993.
  16. 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.
  17. Ostadzadeh, S. A. and Elahi, B. M. and Zeialpour, Z. T, and Moulavi, M. M and Bertels, K. L. M, : A Two Phase Practical Parallel Algorithm for Construction of Huffman Codes, Proceedings of International Conference on Parallel and Distributed Processing Techniques and Applications, pp. 284-291, Las Vegas, USA, June 2007.
  18. 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.
  19. Huffman, D. A. : 'A Method for the Construction of Minimum Redundancy Codes", Proc. IRE, Vol. 40, No. 9, pp. 1098-1101, September 1952.
  20. Doa'a Saad El-Shora & Ehab Rushdy Mohamed. A "Performance Evalution of Data

FAQs

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What data compression methods were tested in the study?add

The study tests Huffman, Run-Length, LZW, Shannon-Fano, and several hybrid methods on multimedia formats.

How does Huffman coding compare to LZW in compression efficiency?add

The results indicate that Huffman coding achieves a compression ratio of 45% on average, whereas LZW averages 38%.

What types of multimedia formats were analyzed for compression?add

The research evaluates various image and text file types to compare the performance of compression methods.

What metrics were used to evaluate the performance of compression algorithms?add

The paper primarily focuses on compression ratio and error rate in reconstructed data as evaluation metrics.

When was this study on data compression techniques published?add

The study was published in the International Journal of Computer Applications in 2017, volume 159.

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