Colour image denoising by eigenvector analysis of neighbourhood colour samples

[EN] Colour image smoothing is a challenging task because it is necessary to appropriately distinguish between noise and original structures, and to smooth noise conveniently. In addition, this processing must take into account the correlation among the image colour channels. In this paper, we intro...

Full description

Bibliographic Details
Authors: Latorre-Carmona, Pedro, Miñana, Juan-José, Morillas, Samuel|||0000-0001-9262-6139
Format: article
Publication Date:2020
Country:España
Institution:Universitat Politècnica de València (UPV)
Repository:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Language:English
OAI Identifier:oai:riunet.upv.es:10251/166837
Online Access:https://riunet.upv.es/handle/10251/166837
Access Level:Open access
Keyword:Colour image filter
Colour image smoothing
Eigenvectors
Gaussian noise
Principal components
Vector filter
MATEMATICA APLICADA
id ES_97e4c25dc70cfe7c32c15708363582eb
oai_identifier_str oai:riunet.upv.es:10251/166837
network_acronym_str ES
network_name_str España
repository_id_str
spelling Colour image denoising by eigenvector analysis of neighbourhood colour samplesLatorre-Carmona, PedroMiñana, Juan-JoséMorillas, Samuel|||0000-0001-9262-6139Colour image filterColour image smoothingEigenvectorsGaussian noisePrincipal componentsVector filterMATEMATICA APLICADA[EN] Colour image smoothing is a challenging task because it is necessary to appropriately distinguish between noise and original structures, and to smooth noise conveniently. In addition, this processing must take into account the correlation among the image colour channels. In this paper, we introduce a novel colour image denoising method where each image pixel is processed according to an eigenvector analysis of a data matrix built from the pixel neighbourhood colour values. The aim of this eigenvector analysis is threefold: (i) to manage the local correlation among the colour image channels, (ii) to distinguish between flat and edge/textured regions and (iii) to determine the amount of needed smoothing. Comparisons with classical and recent methods show that the proposed approach is competitive and able to provide significative improvements.Springer-VerlagDepartamento de Matemática AplicadaInstituto Universitario de Matemática Pura y AplicadaEscuela Técnica Superior de Ingeniería InformáticaRepositorio Institucional de la Universitat Politècnica de València Riunet20202020-04-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/166837reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1668372026-06-13T07:49:27Z
dc.title.none.fl_str_mv Colour image denoising by eigenvector analysis of neighbourhood colour samples
title Colour image denoising by eigenvector analysis of neighbourhood colour samples
spellingShingle Colour image denoising by eigenvector analysis of neighbourhood colour samples
Latorre-Carmona, Pedro
Colour image filter
Colour image smoothing
Eigenvectors
Gaussian noise
Principal components
Vector filter
MATEMATICA APLICADA
title_short Colour image denoising by eigenvector analysis of neighbourhood colour samples
title_full Colour image denoising by eigenvector analysis of neighbourhood colour samples
title_fullStr Colour image denoising by eigenvector analysis of neighbourhood colour samples
title_full_unstemmed Colour image denoising by eigenvector analysis of neighbourhood colour samples
title_sort Colour image denoising by eigenvector analysis of neighbourhood colour samples
dc.creator.none.fl_str_mv Latorre-Carmona, Pedro
Miñana, Juan-José
Morillas, Samuel|||0000-0001-9262-6139
author Latorre-Carmona, Pedro
author_facet Latorre-Carmona, Pedro
Miñana, Juan-José
Morillas, Samuel|||0000-0001-9262-6139
author_role author
author2 Miñana, Juan-José
Morillas, Samuel|||0000-0001-9262-6139
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Matemática Aplicada
Instituto Universitario de Matemática Pura y Aplicada
Escuela Técnica Superior de Ingeniería Informática
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Colour image filter
Colour image smoothing
Eigenvectors
Gaussian noise
Principal components
Vector filter
MATEMATICA APLICADA
topic Colour image filter
Colour image smoothing
Eigenvectors
Gaussian noise
Principal components
Vector filter
MATEMATICA APLICADA
description [EN] Colour image smoothing is a challenging task because it is necessary to appropriately distinguish between noise and original structures, and to smooth noise conveniently. In addition, this processing must take into account the correlation among the image colour channels. In this paper, we introduce a novel colour image denoising method where each image pixel is processed according to an eigenvector analysis of a data matrix built from the pixel neighbourhood colour values. The aim of this eigenvector analysis is threefold: (i) to manage the local correlation among the colour image channels, (ii) to distinguish between flat and edge/textured regions and (iii) to determine the amount of needed smoothing. Comparisons with classical and recent methods show that the proposed approach is competitive and able to provide significative improvements.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-04-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/166837
url https://riunet.upv.es/handle/10251/166837
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
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
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
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer-Verlag
publisher.none.fl_str_mv Springer-Verlag
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869414116892868608
score 15,198674

Similar Items