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Reseach Article

Impulse Noise Removal using Type-2 Fuzzy Set

Published on May 2012 by Rashmi Kumari, S. K. Aggarwal
National Conference on Advancement of Technologies – Information Systems and Computer Networks
Foundation of Computer Science USA
ISCON - Number 3
May 2012
Authors: Rashmi Kumari, S. K. Aggarwal
8b49e2c6-8ccb-46a1-86d8-839bd559b9ef

Rashmi Kumari, S. K. Aggarwal . Impulse Noise Removal using Type-2 Fuzzy Set. National Conference on Advancement of Technologies – Information Systems and Computer Networks. ISCON, 3 (May 2012), 23-26.

@article{
author = { Rashmi Kumari, S. K. Aggarwal },
title = { Impulse Noise Removal using Type-2 Fuzzy Set },
journal = { National Conference on Advancement of Technologies – Information Systems and Computer Networks },
issue_date = { May 2012 },
volume = { ISCON },
number = { 3 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 23-26 },
numpages = 4,
url = { /proceedings/iscon/number3/6475-1022/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advancement of Technologies – Information Systems and Computer Networks
%A Rashmi Kumari
%A S. K. Aggarwal
%T Impulse Noise Removal using Type-2 Fuzzy Set
%J National Conference on Advancement of Technologies – Information Systems and Computer Networks
%@ 0975-8887
%V ISCON
%N 3
%P 23-26
%D 2012
%I International Journal of Computer Applications
Abstract

Filtering is the fundamental pre-processing step for digital images. In this paper we present a novel Type-2 fuzzy filter to remove impulse noise. Type-2 fuzzy sets deals the uncertainty in a better way than Type-1 fuzzy set. It gives an interval irrespective of a crisp value in Type-1 fuzzy set. First the impulse noise is detected and then removed by using S-shaped fuzzy membership function. The performance is compared with other existing filters on the basis of PSNR values calculated for original and restored images.

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Index Terms

Computer Science
Information Sciences

Keywords

Type-2 Fuzzy Logic System Impulse Noise Removal Image Processing