A Hardware Architecture for the LZW Compression and Decompression Algorithms Based on Parallel Dictionaries

  • Ming-Bo Lin


In this paper, a parallel dictionary based LZW algorithm called PDLZW algorithm and its hardware architecture for compression and decompression processors are proposed. In this architecture, instead of using a unique fixed-word-width dictionary a hierarchical variable-word-width dictionary set containing several dictionaries of small address space and increasing word widths is used for both compression and decompression algorithms. The results show that the new architecture not only can be easily implemented in VLSI technology because of its high regularity but also has faster compression and decompression rate since it no longer needs to search the dictionary recursively as the conventional implementations do.

lossless data compression lossless data decompression lossy data compression lossy data decompression LZW algorithm parallel dictionary and PDLZW algorithm 


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  1. 1.
    Ming-Bo Lin, “A parallel VLSI architecture for the LZW data compression algorithm,” International Symposium on VLSI Technology, Systems, and Applications, June 3-5, 1997, Taiwan, pp. 98–101.Google Scholar
  2. 2.
    T.C. Bell, J.G. Cleary, and I.H. Witten, Text Compression, Englewood Cliffs, N.J.: Prentice-Hall, 1990.Google Scholar
  3. 3.
    Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Reading, Massachusetts: Addison-Welsley Publishing Company, 1992.Google Scholar
  4. 4.
    D. Huffman, “A method for the construction of minimum redundancy codes,” Proceeding of IRE, vol. 40, 1952, pp. 1098–1101.CrossRefGoogle Scholar
  5. 5.
    J.S. Vitter, “Design and analysis of dynamic Huffman codes,” J. Association for Computing Machinery, vol. 34, no.4, 1987, pp. 825–845.MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    C.E. Shannon and W. Weaver, The Mathematical Theory of Communication, Urbana, IL: Univ. Illinois Press, 1949.MATHGoogle Scholar
  7. 7.
    P. Elias, “Universal codeword sets and representations of the integers,” IEEE Trans. Inform. Theory, vol. 21, 1975, pp. 194–203.MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    A. Mukheriee, N. Ranganthan, and M. Bassiouni, “Efficient VLSI designs for data transformation of tree-based codes,” IEEE Trans. Circuits Syst., vol. 38, 1991, pp. 306–314.CrossRefGoogle Scholar
  9. 9.
    A. Mukheriee, N. Ranganthan, and J.W. Flieder, “MARVLE: A VLSI chip for data compression using tree-based codes,” IEEE Trans. VLSI Syst., vol. 1, no.2, 1993, pp. 203–214.CrossRefGoogle Scholar
  10. 10.
    J. Ziv and A. Lempel, “A universal algorithm for sequential data compression,” IEEE Trans. Information Theory, vol. IT-23, no.3, 1977, pp. 337–343.MathSciNetCrossRefGoogle Scholar
  11. 11.
    J. Ziv and A. Lempel, “A compression of individual sequences via variable-rate coding,” IEEE Trans. Information Theory, vol. IT-24, no.5, 1978, pp. 530–536.MathSciNetCrossRefGoogle Scholar
  12. 12.
    Terry A. Welch, “A technique for high-performance data compression,” IEEE Computer, vol. 17, no.6, 1984, pp. 8–19.CrossRefGoogle Scholar
  13. 13.
    D.J. Craft, “ADLC and a pre-processor extension, BDLC, provide ultra fast compression for general-purpose and bit-mapped image data,” Proc. Data Compression Conf., 1995, p. 440.Google Scholar
  14. 14.
    Bongjin Jung and Wayne P. Burleson, “Efficienct VLSI for Lempel-Ziv compression in wireless data communication networks,” IEEE Trans. VLSI Syst., vol. 6, no.3, 1998, pp. 475–483.CrossRefGoogle Scholar
  15. 15.
    Gilbert Held, Data and Image Compression: Tools and Techniques, 4th edn., New York: John Wiley & Sons, 1996.Google Scholar
  16. 16.
    S. Bunton and G. Borriello, “Practical dictionary management for hardware data compression,” Communications of ACM, vol. 35, no.1, 1992, pp. 95–104.CrossRefGoogle Scholar
  17. 17.
    E. Fiala and D. Greene, “Data compression with finite windows,” Communications of ACM, vol. 32, no.4, 1989, pp. 490–505.CrossRefGoogle Scholar
  18. 18.
    J. Storer, Data Compression Methods and Theory, Rockville, MD: Computer Science Press, 1988.Google Scholar
  19. 19.
    T. Halfhill, “How safe is data compression,” BYTE, 1994, pp. 56–74.Google Scholar
  20. 20.
    J. Jiang and S. Jones, “Word-based dynamic algorithms for data compression,” IEE Proceedings-I, vol. 139, no.6, 1992, pp. 582–586.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Ming-Bo Lin
    • 1
  1. 1.Department of Electronic EngineeringNational Taiwan University of Science and TechnologyTaipeiTaiwan

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