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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.

    Article  Google Scholar 

  2. K. Culik II and J. Kari, Inference Algorithms for WFA and Image Compression. Chapter of [Fis95] (1995) 243–258.

    Google Scholar 

  3. Y. Fisher (ed.), Fractal Image Compression. Springer-Verlag Berlin, Heidelberg, New York (1995).

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  4. Y. Fisher, Fractal Encoding with HV Partitions. Chapter of [Fis95] (1995) 119–136.

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  5. The Independent JPEG Group, JPEG software release 6b. ftp://ftp.uu.net/graphics/jpeg/jpegsrc.v6b.tar.gz (1998).

  6. A. Rosenfeld and L. S. Davis, Image Segmentation and Image Models. Proceedings of the IEEE, 67, 5(1979) 764–772.

    Article  Google Scholar 

  7. A. Rao, V. D. Pandit and R. U. Udupa, Efficient Decoding Algorithms for Weighed Finite Automata. Department of Computer Science, S. J. College of Engineering, Myosore (1996).

    Google Scholar 

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

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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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