Adaptive weighted median filters by using fuzzy techniques

Author

Meguro, Mitsuhiko ; Taguchi, Akira

Author_Institution

Dept. of Electr. & Electron. Eng., Musashi Inst. of Technol., Tokyo, Japan

Volume

2

fYear

1996

fDate

12-15 May 1996

Firstpage

9

Abstract

In this paper, we propose adaptive weighted median (AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by fuzzy rules (fuzzy weighted median: FWM filters). By using the rule-based fuzzy techniques, the better weights are easily derived. Experimental results show AWM filters can suppress nonimpulsive and impulsive noise, while preserving signal details

Keywords

adaptive filters; filtering theory; fuzzy logic; knowledge based systems; median filters; AWM filters; adaptive weighted median filters; fuzzy techniques; fuzzy weighted median filters; impulsive noise; local statistics; nonimpulsive noise; nonlinear function; rule-based fuzzy techniques; signal details; Adaptive filters; Attenuation; Degradation; Image processing; Image recognition; Image restoration; Noise reduction; Nonlinear filters; Signal restoration; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on

Conference_Location

Atlanta, GA

Print_ISBN

0-7803-3073-0

Type

conf

DOI

10.1109/ISCAS.1996.540339

Filename

540339