Fuzzy rule-based signal processing and its application to image restoration

Author

Arakawa, Kaoru

Author_Institution

Dept. of Comput. Sci., Meiji Univ., Kawasaki, Japan

Volume

12

Issue

9

fYear

1994

fDate

12/1/1994 12:00:00 AM

Firstpage

1495

Lastpage

1502

Abstract

A novel signal processing technique based on fuzzy rules is proposed for estimating nonstationary signals, such as image signals, contaminated with additive random noises. In this filter, fuzzy rules concerning the relationship between signal characteristics and filter design are utilized to set the filter parameters, taking the local characteristics of the signal into consideration. The fuzzy rules are found to be quite effective, since the rules to set the filter parameters are usually expressed in an ambiguous style. The high performance of this filter is demonstrated in noise reduction of a 1-D test signal and a natural image with various training signals

Keywords

filtering theory; fuzzy logic; image restoration; random noise; 1-D test signal; additive random noises; filter design; filter parameters; fuzzy rules; image restoration; image signals; local signal characteristics; noise reduction; nonstationary signals estimation; signal characteristics; signal processing; training signals; Additive noise; Filtering; Filters; Fuzzy control; Fuzzy sets; Gaussian noise; Image edge detection; Image restoration; Noise reduction; Signal processing;

fLanguage

English

Journal_Title

Selected Areas in Communications, IEEE Journal on

Publisher

ieee

ISSN

0733-8716

Type

jour

DOI

10.1109/49.339917

Filename

339917