Advertisement

Other Methods

  • David Salomon

Abstract

Previous chapters discuss the main classes of compression methods: RLE, statistical methods, and dictionary-based methods. There are data compression methods that are not easy to classify and do not clearly belong in any of the classes discussed so far. A few such methods are described here.

Keywords

Compression Method Input Stream Huffman Code Interword Space Arithmetic Encoder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. Burrows, Michael and D. J. Wheeler (1994) A Block-Sorting Lossless Data Compression Algorithm, Digital, Systems Research Center report 124, Palo Alto, Calif, May 10.Google Scholar
  2. Manber, U., and E. W. Myers (1993) “Suffix Arrays: A New Method for On-Line String Searches,” SIAM Journal on Computing 22(5):935–948, October.MathSciNetzbMATHCrossRefGoogle Scholar
  3. McCreight, E. M. (1976) “A Space Economical Suffix Tree Construction Algorithm,” Journal of the ACM 32(2):262–272, April.MathSciNetCrossRefGoogle Scholar
  4. Fenwick, P. (1996) Symbol Ranking Text Compression, Tech. Rep. 132, Dept. of Computer Science, University of Auckland, New Zealand, June.Google Scholar
  5. Shannon, C. (1951) “Prediction and Entropy of Printed English,” Bell System Technical Journal 30(l):50–64, January.zbMATHGoogle Scholar
  6. Buyanovsky, G. (1994), “Associative Coding,” (in Russian), Monitor, Moscow, #8, 10–19, August. (Hard copies of the Russian source and English translation are available from the author of this book. Send requests to “dxs@ecs.csun.edu”.)Google Scholar
  7. Fenwick, P. (1996), “Symbol Ranking Text Compression,” Tech. Rep. 132, Dept. of Computer Science, University of Auckland, New Zealand, June.Google Scholar
  8. Praenkel, A. S., and S. T. Klein (1985), “Novel Compression of Sparse Bit-Strings— Preliminary Report,” in A. Apostolico and Z. Galil, eds., Combinatorial Algorithms on Words, Vol. 12, NATO ASI Series F: 169–183, New York, Springer-Verlag.CrossRefGoogle Scholar
  9. Knuth, D. E. (1973), The Art of Computer Programming, Vol. 1, 2nd Ed., Reading, MA, Addison-Wesley.Google Scholar
  10. Horspool, N. R. and G. V. Cormack (1992) “Constructing Word-Based Text Compression Algorithms,” in Proceedings of the 1992 Data Compression Conference, J. Storer Ed., Los Alamitos, CA, IEEE Computer Society Press, pp. 62–71, April.CrossRefGoogle Scholar
  11. Witten, I. H., T. C. Bell, M. E. Harrison, M. L. James, and A. Moffat (1992) “Textual Image Compression,” in Proceedings of the 1992 Data Compression Conference, J. Storer ed., Los Alamitos, CA, IEEE Computer Society Press, pp. 42–51.CrossRefGoogle Scholar
  12. Witten, I. H., et al. (1994) Managing Gigabytes: Compressing and Indexing Documents and Images, New York, Van Nostrand Reinhold.zbMATHGoogle Scholar
  13. Cormack G. V. and R. N. S. Horspool (1987) “Data Compression Using Dynamic Markov Modelling,” The Computer Journal 30(6):541–550.MathSciNetCrossRefGoogle Scholar
  14. Yu, Tong Lai. (1996) “Dynamic Markov Compression,” Dr Dobb’s Journal pp. 30–31, January.Google Scholar

Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • David Salomon
    • 1
  1. 1.Department of Computer ScienceCalifornia State UniversityNorthridgeUSA

Personalised recommendations