ON A LOSSY IMAGE COMPRESSION/RECONSTRUCTION METHOD BASED ON FUZZY RELATIONAL EQUATIONS

Authors

  • Hajime Nobuhara Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
  • Kaoru Hirota Kaoru Hirota, Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
  • Kazuhiko Kawamoto Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
  • Shin-ichi Yoshida Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
Abstract:

The pioneer work of image compression/reconstruction based onfuzzy relational equations (ICF) and the related works are introduced. TheICF regards an original image as a fuzzy relation by embedding the brightnesslevel into [0,1]. The compression/reconstruction of ICF correspond to thecomposition/solving inverse problem formulated on fuzzy relational equations.Optimizations of ICF can be consequently deduced based on fuzzy relationalcalculus, i.e., computation time reduction/improvement of reconstructed imagequality are correspond to a fast solving method/finding an approximatesolution of fuzzy relational equations, respectively. Through the experimentsusing test images extracted from Standard Image DataBAse (SIDBA), theeffectiveness of the ICF and its optimizations are shown.

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Journal title

volume 1  issue 1

pages  33- 42

publication date 2004-04-22

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