Features preserving filters using fuzzy Kohonen clustering network in detection of impulse noise

Author

Singh, Kh Manglem ; Bora, P.K. ; Mahanta, Anil

Author_Institution

Dept. of Electron. & Commun. Eng., Indian Inst. of Technol., Guwahati, India

Volume

1

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

420

Abstract

It is always advisable to apply filtering only on corrupted pixels of images leaving untouched the uncorrupted ones to preserve image features and to avoid blurring effects. We present an algorithm which can detect the corrupted pixels in texture images. It uses a fuzzy Kohonen clustering network that integrates with the fuzzy c-means (FCM) model utilizing the updating strategies of the first and the learning rate of the second

Keywords

feature extraction; fuzzy set theory; image texture; impulse noise; learning (artificial intelligence); median filters; pattern clustering; self-organising feature maps; corrupted pixels; feature-preserving filters; filtering; fuzzy Kohonen clustering network; fuzzy c-means model; image features; impulse noise detection; learning rate; multilevel median filter; texture images; updating; Clustering algorithms; Filtering algorithms; Filters; Fuzzy logic; Image processing; Image storage; Information filtering; Intelligent networks; Noise reduction; Pixel;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2001. Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology

Print_ISBN

0-7803-7101-1

Type

conf

DOI

10.1109/TENCON.2001.949627

Filename

949627