Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density

Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arith...

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Detalles Bibliográficos
Autores: González-Hidalgo, Manuel, Massanet, Sebastia, Mir, Arnau, Ruiz-Aguilera, Daniel
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Conselleria de Salut i Consum del Govern de les Illes Balears
Repositorio:Docusalut
Idioma:inglés
OAI Identifier:oai:docusalut.com:20.500.13003/10664
Acceso en línea:https://hdl.handle.net/20.500.13003/10664
Access Level:acceso abierto
Palabra clave:image processing
noise removal
impulsive noise
weighted arithmetic mean
fuzzy mathematical morphology
open-close filter
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spelling Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise DensityGonzález-Hidalgo, ManuelMassanet, SebastiaMir, ArnauRuiz-Aguilera, Danielimage processingnoise removalimpulsive noiseweighted arithmetic meanfuzzy mathematical morphologyopen-close filterMany computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any noise density from 5% to 98%. A statistical analysis based on some objective restoration measures supports that this filter surpasses several state-of-the-art filters for most of the noise levels considered in the comparison experiments.MDPI20212021-01-0120212021-01-01research articlehttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.13003/10664reponame:Docusalutinstname:Conselleria de Salut i Consum del Govern de les Illes BalearsInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:docusalut.com:20.500.13003/106642026-06-22T12:44:07Z
dc.title.none.fl_str_mv Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
title Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
spellingShingle Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
González-Hidalgo, Manuel
image processing
noise removal
impulsive noise
weighted arithmetic mean
fuzzy mathematical morphology
open-close filter
title_short Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
title_full Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
title_fullStr Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
title_full_unstemmed Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
title_sort Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density
dc.creator.none.fl_str_mv González-Hidalgo, Manuel
Massanet, Sebastia
Mir, Arnau
Ruiz-Aguilera, Daniel
author González-Hidalgo, Manuel
author_facet González-Hidalgo, Manuel
Massanet, Sebastia
Mir, Arnau
Ruiz-Aguilera, Daniel
author_role author
author2 Massanet, Sebastia
Mir, Arnau
Ruiz-Aguilera, Daniel
author2_role author
author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv image processing
noise removal
impulsive noise
weighted arithmetic mean
fuzzy mathematical morphology
open-close filter
topic image processing
noise removal
impulsive noise
weighted arithmetic mean
fuzzy mathematical morphology
open-close filter
description Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any noise density from 5% to 98%. A statistical analysis based on some objective restoration measures supports that this filter surpasses several state-of-the-art filters for most of the noise levels considered in the comparison experiments.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01
2021
2021-01-01
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.13003/10664
url https://hdl.handle.net/20.500.13003/10664
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Docusalut
instname:Conselleria de Salut i Consum del Govern de les Illes Balears
instname_str Conselleria de Salut i Consum del Govern de les Illes Balears
reponame_str Docusalut
collection Docusalut
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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