the homepage for information on compressing 3D graphics and other complex datasets for fast transmission and cheap storage
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This site and all its pages are Copyright (C) 1999 - 2002, Davis King, all rights reserved.

Net Resources on Data Compression and Information Theory

Data Compression is the art of squeezing a large amount of information into a small space.  Compression algorithms are widely used in applications that depend on storing and transmitting data efficiently, including the Internet, fax machines, cell phones, DVD players, database applications, and satellite communications.

Information Theory provides the scientific basis for data compression and for other technologies such as encryption, error correction, pattern recognition, signal processing, and similarity comparisons.  Information theory has also been widely influential in research on theoretical computer science, the physics of computation, fiber optics, psychology, and even music and molecular biology.

Overviews and Tutorials

Seminal Papers and literature surveys

  • C. E. Shannon, "A Mathematical Theory of Communication," Bell System Tech Journal,vol. 27, pp. 379-423 and 623-656, July and October, 1948.  (the original paper on information theory)
  • Kolmogorov Complexity or algorithmic complexity -- see G. Chaitin, "An Invitation to Algorithmic Information Theory," DMTCS'96 Proceedings, 1997.
  • Huffman, paper on huffman coding
  • Witten, Neal, and Cleary, "Arithmetic Coding for Data Compression," Comm. ACM, 30(6):520--541, June 1987 (long considered the standard for arithmetic coding)
  • Moffat, Neal, and Witten, "Arithmetic Coding Revisited", ACM Transactions on Information Systems, 16(3):256-294, July 1998 (modern improvements to the speed of arithmetic coding)
  • wavelets for compression
  • R. M. Gray and D. L. Neuhoff, "Quantization", invited to IEEE Transactions on Information Theory, October 1998. (a comprehensive overview of scalar and vector quantization)
  • fractal compression

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Some Frequently Asked Questions on Data Compression

  1. Can all data sets be compressed? How far can a data set be compressed?
  2. Can any compression algorithm achieve the maximum possible compression rate for a text string?
  3. How can a string of symbols be compressed with less than one bit per symbol?
  4. Why isn't arithmetic coding used more often?
  5. What is the best compression method to use for (text? images? music? speech? video? 3D graphics?)
  6. Are these algorithms patented?
  7. What are open research topics in compression?


Copyright (C) 1999-2001, Davis King

This page, the database, and all the pages on this site are copyright (C) 1999-2001, Davis King, all rights reserved, and it may not be reproduced or mirrored in any form or medium without permission, except for automatic caching or, with proper citation and attribution, for "fair use." Anyone is welcome to link to any of the pages on this site; we have included all the links here in good faith and will remove any links at the request of the author or owner of the linked page.  This site is intended for informational and research purposes only, and nothing in this site should be construed as an offer to sell or an endorsement of any product, or as a warranty of the suitability or effectiveness of any technology for any particular application.