A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

[EN] A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on mult...

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Detalhes bibliográficos
Autores: Sánchez, M. G., Vidal, V., Arnal, J., Bataller Mascarell, Jordi
Formato: artículo
Fecha de publicación:2013
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/40550
Acesso em linha:https://riunet.upv.es/handle/10251/40550
Access Level:acceso abierto
Palavra-chave:Parallel computing
Noise removal in images
GPU
CUDA
Multi-core
OpenMP
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
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oai_identifier_str oai:riunet.upv.es:10251/40550
network_acronym_str ES
network_name_str España
repository_id_str
spelling A parallel method for impulsive image noise removal on hybrid CPU/GPU systemsSánchez, M. G.Vidal, V.Arnal, J.Bataller Mascarell, JordiParallel computingNoise removal in imagesGPUCUDAMulti-coreOpenMPCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALLENGUAJES Y SISTEMAS INFORMATICOS[EN] A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.This work was supported by the Spanish Ministry of Science and Innovation [Project TIN2011-26254]. M. G. Sanchez would like to acknowledge DGEST ITCG for the scholarship awarded through the PROMEP program.ElsevierInstituto Universitario Mixto de Tecnología de InformáticaDepartamento de Sistemas Informáticos y ComputaciónEscuela Politécnica Superior de GandiaMinisterio de Ciencia e InnovaciónRepositorio Institucional de la Universitat Politècnica de València Riunet20132013-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/40550reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 TIN2011-26254 COMPUTACION DE ALTAS PRESTACIONES Y SISTEMAS HIBRIDOSopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/405502026-06-13T07:49:27Z
dc.title.none.fl_str_mv A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
title A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
spellingShingle A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
Sánchez, M. G.
Parallel computing
Noise removal in images
GPU
CUDA
Multi-core
OpenMP
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
title_short A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
title_full A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
title_fullStr A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
title_full_unstemmed A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
title_sort A parallel method for impulsive image noise removal on hybrid CPU/GPU systems
dc.creator.none.fl_str_mv Sánchez, M. G.
Vidal, V.
Arnal, J.
Bataller Mascarell, Jordi
author Sánchez, M. G.
author_facet Sánchez, M. G.
Vidal, V.
Arnal, J.
Bataller Mascarell, Jordi
author_role author
author2 Vidal, V.
Arnal, J.
Bataller Mascarell, Jordi
author2_role author
author
author
dc.contributor.none.fl_str_mv Instituto Universitario Mixto de Tecnología de Informática
Departamento de Sistemas Informáticos y Computación
Escuela Politécnica Superior de Gandia
Ministerio de Ciencia e Innovación
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Parallel computing
Noise removal in images
GPU
CUDA
Multi-core
OpenMP
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
topic Parallel computing
Noise removal in images
GPU
CUDA
Multi-core
OpenMP
CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL
LENGUAJES Y SISTEMAS INFORMATICOS
description [EN] A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01
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/10251/40550
url https://riunet.upv.es/handle/10251/40550
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 TIN2011-26254 COMPUTACION DE ALTAS PRESTACIONES Y SISTEMAS HIBRIDOS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/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
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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_ 1869412514413936640
score 15,300719

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