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Enhancements of Partitioning Techniques for Image Compression Using Weighted Finite Automata

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Implementation and Application of Automata (CIAA 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2494))

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Abstract

WFAs (weighted finite automata) are efficient structures for the storage of digital images. The choice of the image partitioning technique is important to achieve good compression results. In this paper we examine the fitness of various promising techniques by measuring the compression performance at well-known test images.

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References

  1. K. Culik II and J. Kari, Image Compression Using Weighted Finite Automata. Computers and Graphics 17, 3 (1993) 305–313.

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  8. University of Waterloo, Ontario, Canada, Waterloo BragZone: Comparison of Image Compression Systems. http://www.uwaterloo.ca/bragzone.base.html.

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Author information

Authors and Affiliations

  1. Department of Electr. Eng. and Computer Science, University of Siegen, Germany

    Frank Katritzke & Wolfgang Merzenich

  2. Mathematical Department, University of Siegen, Germany

    Michael Thomas

Authors
  1. Frank Katritzke
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  2. Wolfgang Merzenich
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  3. Michael Thomas
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Pretoria, Lynwood Road, Pretoria, 0002, South Africa

    Bruce W. Watson

  2. Department of Computer Science, Hong Kong University of Science and Technology, Clearwater Bay, Kowloon, Hong Kong

    Derick Wood

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© 2002 Springer-Verlag Berlin Heidelberg

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Katritzke, F., Merzenich, W., Thomas, M. (2002). Enhancements of Partitioning Techniques for Image Compression Using Weighted Finite Automata. In: Watson, B.W., Wood, D. (eds) Implementation and Application of Automata. CIAA 2001. Lecture Notes in Computer Science, vol 2494. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36390-4_15

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  • DOI: https://doi.org/10.1007/3-540-36390-4_15

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00400-4

  • Online ISBN: 978-3-540-36390-3

  • eBook Packages: Springer Book Archive

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