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Removal Of Random-Valued Impulse Noise using Adaptive Centre Weighted Median Filters And Detail Preservation Method

Published on March 2012 by Shilpa Joshi, R.K.Kulkarni, Jayashree Khanapuri
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET2012 - Number 4
March 2012
Authors: Shilpa Joshi, R.K.Kulkarni, Jayashree Khanapuri
c72e21a3-872a-4fd3-bcbe-b7392b01515a

Shilpa Joshi, R.K.Kulkarni, Jayashree Khanapuri . Removal Of Random-Valued Impulse Noise using Adaptive Centre Weighted Median Filters And Detail Preservation Method. International Conference and Workshop on Emerging Trends in Technology. ICWET2012, 4 (March 2012), 15-18.

@article{
author = { Shilpa Joshi, R.K.Kulkarni, Jayashree Khanapuri },
title = { Removal Of Random-Valued Impulse Noise using Adaptive Centre Weighted Median Filters And Detail Preservation Method },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { March 2012 },
volume = { ICWET2012 },
number = { 4 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 15-18 },
numpages = 4,
url = { /proceedings/icwet2012/number4/5337-1028/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A Shilpa Joshi
%A R.K.Kulkarni
%A Jayashree Khanapuri
%T Removal Of Random-Valued Impulse Noise using Adaptive Centre Weighted Median Filters And Detail Preservation Method
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET2012
%N 4
%P 15-18
%D 2012
%I International Journal of Computer Applications
Abstract

This paper proposes a two-stage iterative method for removing random-valued impulse noise. In the first phase, we use the adaptive center-weighted median filter to identify pixels which are likely to be corrupted by noise (noise candidates). In the second phase, these noise candidates are restored using a detail-preserving regularization method which allows edges and noise-free pixels to be preserved. In the this paper these two phases are applied alternatively. Simulation results indicate that the proposed method is significantly better than those using just nonlinear filters or detail preservation method only.

References
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Index Terms

Computer Science
Information Sciences

Keywords

impulse noise high density noise median filter non linear filter Adaptive centre weighted median