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Reseach Article

Review of Noise Removal Techniques for Fixed Valued Impulse Noise

by Priyanka Rastogi, Neelesh Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 5
Year of Publication: 2015
Authors: Priyanka Rastogi, Neelesh Gupta
10.5120/ijca2015905308

Priyanka Rastogi, Neelesh Gupta . Review of Noise Removal Techniques for Fixed Valued Impulse Noise. International Journal of Computer Applications. 123, 5 ( August 2015), 7-10. DOI=10.5120/ijca2015905308

@article{ 10.5120/ijca2015905308,
author = { Priyanka Rastogi, Neelesh Gupta },
title = { Review of Noise Removal Techniques for Fixed Valued Impulse Noise },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 5 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number5/21953-2015905308/ },
doi = { 10.5120/ijca2015905308 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:12:11.418022+05:30
%A Priyanka Rastogi
%A Neelesh Gupta
%T Review of Noise Removal Techniques for Fixed Valued Impulse Noise
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 5
%P 7-10
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Noise removal is one of the biggest challenges in the field of image processing. Impulse noise removal is one of the most necessary and important preprocessing step in digital image processing. Several median based techniques are reported in literature for different noise models. Each of them has their advantages and limitations. Most of the filters are good at noise suppression but their performance decreases in terms of edge preservation. In the review paper , various algorithms for removal of fixed valued impulse noise and their performance under different noise conditions and for various fixed valued noise models is discussed. All the techniques have their advantages and limitations. The comparative study helps in identification of most efficient algorithms in terms of edge conservation and noise suppression to restore the original image to the best possible extent given the degraded version. Most of the techniques are suitable for some particular noise models and thus does not perform satisfactorily on other types of noise models.

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Index Terms

Computer Science
Information Sciences

Keywords

Switching median filter Image denoising Impulse noise detection nonlinear filter