Neural Networks Applied for impulse Noise Reduction from Digital Images
Autor(a) principal: | |
---|---|
Data de Publicação: | 2012 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | INFOCOMP: Jornal de Ciência da Computação |
Texto Completo: | https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358 |
Resumo: | This paper proposes the use of a new method for detecting and removing impulse noise from digital images based on the combination of two Artificial Neural Networks (ANN). The training algorithm of the ANNs is based on the technique of backpropagation. The first ANN is used to the detection of impulse noise, known as salt and pepper, and the second ANN is used to replace it by an estimated value. The proposed method is compared with other methods on literature in terms of visual judgment and also using a quantitative measure of PSNR - Peak Signal To Noise Ratio. The numerical and visual results obtained demonstrate the feasibility of the proposed method, which can be used as part of a tool for treatment of images. |
id |
UFLA-5_6a12ef0885afba077e0d232e5403b235 |
---|---|
oai_identifier_str |
oai:infocomp.dcc.ufla.br:article/358 |
network_acronym_str |
UFLA-5 |
network_name_str |
INFOCOMP: Jornal de Ciência da Computação |
repository_id_str |
|
spelling |
Neural Networks Applied for impulse Noise Reduction from Digital ImagesArtificial Neural NetworksImpulse noiseImpulse DetectorImpulse estimatorDigital imagesThis paper proposes the use of a new method for detecting and removing impulse noise from digital images based on the combination of two Artificial Neural Networks (ANN). The training algorithm of the ANNs is based on the technique of backpropagation. The first ANN is used to the detection of impulse noise, known as salt and pepper, and the second ANN is used to replace it by an estimated value. The proposed method is compared with other methods on literature in terms of visual judgment and also using a quantitative measure of PSNR - Peak Signal To Noise Ratio. The numerical and visual results obtained demonstrate the feasibility of the proposed method, which can be used as part of a tool for treatment of images.Editora da UFLA2012-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358INFOCOMP Journal of Computer Science; Vol. 11 No. 3-4 (2012): September-December, 2012; 7-141982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358/342Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessSoares, Pablo Luiz BragaSilva, José Patrocínio da2015-07-29T14:06:51Zoai:infocomp.dcc.ufla.br:article/358Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:34.067800INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true |
dc.title.none.fl_str_mv |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
title |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
spellingShingle |
Neural Networks Applied for impulse Noise Reduction from Digital Images Soares, Pablo Luiz Braga Artificial Neural Networks Impulse noise Impulse Detector Impulse estimator Digital images |
title_short |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
title_full |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
title_fullStr |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
title_full_unstemmed |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
title_sort |
Neural Networks Applied for impulse Noise Reduction from Digital Images |
author |
Soares, Pablo Luiz Braga |
author_facet |
Soares, Pablo Luiz Braga Silva, José Patrocínio da |
author_role |
author |
author2 |
Silva, José Patrocínio da |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Soares, Pablo Luiz Braga Silva, José Patrocínio da |
dc.subject.por.fl_str_mv |
Artificial Neural Networks Impulse noise Impulse Detector Impulse estimator Digital images |
topic |
Artificial Neural Networks Impulse noise Impulse Detector Impulse estimator Digital images |
description |
This paper proposes the use of a new method for detecting and removing impulse noise from digital images based on the combination of two Artificial Neural Networks (ANN). The training algorithm of the ANNs is based on the technique of backpropagation. The first ANN is used to the detection of impulse noise, known as salt and pepper, and the second ANN is used to replace it by an estimated value. The proposed method is compared with other methods on literature in terms of visual judgment and also using a quantitative measure of PSNR - Peak Signal To Noise Ratio. The numerical and visual results obtained demonstrate the feasibility of the proposed method, which can be used as part of a tool for treatment of images. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358 |
url |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/358/342 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 INFOCOMP Journal of Computer Science info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 INFOCOMP Journal of Computer Science |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Editora da UFLA |
publisher.none.fl_str_mv |
Editora da UFLA |
dc.source.none.fl_str_mv |
INFOCOMP Journal of Computer Science; Vol. 11 No. 3-4 (2012): September-December, 2012; 7-14 1982-3363 1807-4545 reponame:INFOCOMP: Jornal de Ciência da Computação instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
INFOCOMP: Jornal de Ciência da Computação |
collection |
INFOCOMP: Jornal de Ciência da Computação |
repository.name.fl_str_mv |
INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
infocomp@dcc.ufla.br||apfreire@dcc.ufla.br |
_version_ |
1799874741409939456 |