Research Article
A Decision based Unsymmetrical Trimmed Variants for the Removal of High Density Salt and Pepper Noise
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 42 - Issue 15 |
| Published: March 2012 |
| Authors: K. Vasanth, V. Jawahar Senthilkumar, Rajesh. V |
10.5120/5773-8166
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K. Vasanth, V. Jawahar Senthilkumar, Rajesh. V . A Decision based Unsymmetrical Trimmed Variants for the Removal of High Density Salt and Pepper Noise. International Journal of Computer Applications. 42, 15 (March 2012), 53-66. DOI=10.5120/5773-8166
@article{ 10.5120/5773-8166,
author = { K. Vasanth,V. Jawahar Senthilkumar,Rajesh. V },
title = { A Decision based Unsymmetrical Trimmed Variants for the Removal of High Density Salt and Pepper Noise },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 42 },
number = { 15 },
pages = { 53-66 },
doi = { 10.5120/5773-8166 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A K. Vasanth
%A V. Jawahar Senthilkumar
%A Rajesh. V
%T A Decision based Unsymmetrical Trimmed Variants for the Removal of High Density Salt and Pepper Noise%T
%J International Journal of Computer Applications
%V 42
%N 15
%P 53-66
%R 10.5120/5773-8166
%I Foundation of Computer Science (FCS), NY, USA
Abstract
A Decision based scheme using a improved mesh based snake like sorting is proposed for the restoration of gray scale images that are heavily corrupted by salt and pepper noise. The proposed algorithm uses modified mean or median for image restoration. The processed pixel is examined for 0 or 255; if checked pixel is equal to 0 or 255, then it is considered as noisy pixel else not noisy. The noisy pixel is replaced by median of unsymmetrical trimmed output, if the current window has at least three noisy pixels or mean of first and last values of the un-symmetrical trimmed output. The uncorrupted pixel is left unchanged. The proposed algorithm shows excellent noise suppression capability with good edge preservation in heavy noisy conditions both qualitative and quantitatively. The proposed algorithm was applied on various grayscale images and found to have excellent PSNR and high IEF , low MSE and consumes less time even at very high noise densities with edge preservation.
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