Cargando…

Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises

In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise...

Descripción completa

Detalles Bibliográficos
Autores principales: Jin, Qiyu, Grama, Ion, Liu, Quansheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5503236/
https://www.ncbi.nlm.nih.gov/pubmed/28692667
http://dx.doi.org/10.1371/journal.pone.0179051
_version_ 1783249060035035136
author Jin, Qiyu
Grama, Ion
Liu, Quansheng
author_facet Jin, Qiyu
Grama, Ion
Liu, Quansheng
author_sort Jin, Qiyu
collection PubMed
description In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise.
format Online
Article
Text
id pubmed-5503236
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-55032362017-07-25 Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises Jin, Qiyu Grama, Ion Liu, Quansheng PLoS One Research Article In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise. Public Library of Science 2017-07-10 /pmc/articles/PMC5503236/ /pubmed/28692667 http://dx.doi.org/10.1371/journal.pone.0179051 Text en © 2017 Jin et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jin, Qiyu
Grama, Ion
Liu, Quansheng
Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises
title Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises
title_full Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises
title_fullStr Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises
title_full_unstemmed Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises
title_short Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises
title_sort optimal weights mixed filter for removing mixture of gaussian and impulse noises
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5503236/
https://www.ncbi.nlm.nih.gov/pubmed/28692667
http://dx.doi.org/10.1371/journal.pone.0179051
work_keys_str_mv AT jinqiyu optimalweightsmixedfilterforremovingmixtureofgaussianandimpulsenoises
AT gramaion optimalweightsmixedfilterforremovingmixtureofgaussianandimpulsenoises
AT liuquansheng optimalweightsmixedfilterforremovingmixtureofgaussianandimpulsenoises