Skip to main content

Forward Looking Huffman Coding

  • Conference paper
  • First Online:
Computer Science – Theory and Applications (CSR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11532))

Included in the following conference series:

Abstract

Huffman coding is known to be optimal, yet its dynamic version may yield smaller compressed files. The best known bound is that the number of bits used by dynamic Huffman coding in order to encode a message of n characters is at most larger by n bits than the number of bits required by static Huffman coding. In particular, dynamic Huffman coding can also generate a larger encoded file than the static variant, though in practice the file might often, but not always, be smaller. We propose here a new dynamic Huffman encoding approach, that provably always performs at least as good as static Huffman coding, and may be better than the standard dynamic Huffman coding for certain files. This is achieved by reversing the direction for the references of the encoded elements to those forming the model of the encoding, from pointing backwards to looking into the future.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Faller, N.: An adaptive system for data compression. In: Record of the 7-th Asilomar Conference on Circuits, Systems and Computers, pp. 593–597 (1973)

    Google Scholar 

  2. Ferguson, T.J., Rabinowitz, J.H.: Self-synchronizing Huffman codes. IEEE Trans. Inf. Theory 30(4), 687–693 (1984)

    Article  MathSciNet  Google Scholar 

  3. Gallager, R.: Variations on a theme by Huffman. IEEE Trans. Inf. Theory 24(6), 668–674 (1978)

    Article  MathSciNet  Google Scholar 

  4. Huffman, D.: A method for the construction of minimum redundancy codes. Proc. IRE 40, 1098–1101 (1952)

    Article  Google Scholar 

  5. Klein, S.T., Shapira, D.: A new compression method for compressed matching. In: Data Compression Conference, DCC 2000, Snowbird, Utah, USA, March 28–30, 2000, pp. 400–409 (2000)

    Google Scholar 

  6. Knuth, D.E.: Dynamic Huffman coding. J. Algorithms 6(2), 163–180 (1985)

    Article  MathSciNet  Google Scholar 

  7. Moffat, A.: Word-based text compression. Softw. Pract. Exper. 19(2), 185–198 (1989)

    Article  Google Scholar 

  8. Schwartz, E.S., Kallick, B.: Generating a canonical prefix encoding. Commun. ACM 7, 166–169 (1964)

    Article  Google Scholar 

  9. Storer, J.A., Szymanski, T.G.: Data compression via textural substitution. J. ACM 29(4), 928–951 (1982)

    Article  Google Scholar 

  10. Véronis, J., Langlais, P.: Evaluation of parallel text alignment systems: the arcade project. In: Véronis, J. (ed.) Parallel Text Processing, pp. 369–388. Kluwer Academic Publishers, Dordrecht (2000)

    Chapter  Google Scholar 

  11. Vitter, J.S.: Design and analysis of dynamic Huffman codes. J. ACM 34(4), 825–845 (1987)

    Article  MathSciNet  Google Scholar 

  12. Witten, I.H., Neal, R.M., Cleary, J.G.: Arithmetic coding for data compression. Commun. ACM 30(6), 520–540 (1987)

    Article  Google Scholar 

  13. Zobel, J., Moffat, A.: Inverted files for text search engines. ACM Comput. Surv. 38(2), 6 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dana Shapira .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Klein, S.T., Saadia, S., Shapira, D. (2019). Forward Looking Huffman Coding. In: van Bevern, R., Kucherov, G. (eds) Computer Science – Theory and Applications. CSR 2019. Lecture Notes in Computer Science(), vol 11532. Springer, Cham. https://doi.org/10.1007/978-3-030-19955-5_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-19955-5_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19954-8

  • Online ISBN: 978-3-030-19955-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics