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

Abstract

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