Document Type : Research Paper


1 Kaoru Hirota, Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 226-8502, Japan

2 Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, 226-8502, Japan


The pioneer work of image compression/reconstruction based on
fuzzy relational equations (ICF) and the related works are introduced. The
ICF regards an original image as a fuzzy relation by embedding the brightness
level into [0,1]. The compression/reconstruction of ICF correspond to the
composition/solving inverse problem formulated on fuzzy relational equations.
Optimizations of ICF can be consequently deduced based on fuzzy relational
calculus, i.e., computation time reduction/improvement of reconstructed image
quality are correspond to a fast solving method/finding an approximate
solution of fuzzy relational equations, respectively. Through the experiments
using test images extracted from Standard Image DataBAse (SIDBA), the
effectiveness of the ICF and its optimizations are shown.


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