FUZZY RELATION CALCULUS IN THE COMPRESSION AND DECOMPRESSION OF FUZZY RELATIONS-Reference-Cited by-同舟云学术

FUZZY RELATION CALCULUS IN THE COMPRESSION AND DECOMPRESSION OF FUZZY RELATIONS

Published:2002-10 Issue:04 Volume:02 Page:617-631
ISSN:0219-4678
Container-title:International Journal of Image and Graphics
language:en
Short-container-title:Int. J. Image Grap.

Author:

LOIA VINCENZO¹,PEDRYCZ WITOLD²,SESSA SALVATORE³

Affiliation:

1. Università di Salerno, Dipartimento di Matematica ed Informatica, via S. Allende, 84081 Baronissi, Salerno, Italy

2. University of Alberta, Department of Electrical and Computer Engineering, Edmonton, AB, Canada T6G 2G7, Canada

3. Università di Napoli "Federico II", Dipartimento di Costruzioni e Metodi Matematici in Architettura, via Monteoliveto 3, 80134 Napoli, Italy

Abstract

We firstly review some fundamentals of fuzzy relation calculus and, by recalling some known results, we improve the mathematical contents of our previous papers by using the properties of a triangular norm over [0,1]. We make wide use of the theory of fuzzy relation equations for getting lossy compression and decompression of images interpreted as two-argument fuzzy matrices.The same scope is achieved by decomposing a fuzzy matrix using the concept of Schein rank. We illustrate two algorithms with a few examples.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0219467802000871

Reference11 articles.

1. When is a fuzzy relation decomposable in two fuzzy sets

2. On the Schein rank of matrices over linear lattices

3. Basic fuzzy logic and BL-algebras

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