Aggregation functions to combine RGB color channels in stereo matching

In this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching algorithm by aggregating the similarities of the RGB channels which are calculat...

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Autores: Galar Idoate, Mikel, Jurío Munárriz, Aránzazu, López Molina, Carlos, Sanz Delgado, José Antonio, Paternain Dallo, Daniel, Bustince Sola, Humberto
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2013
País:España
Institución:Universidad San Jorge (USJ)
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/21074
Acceso en línea:https://hdl.handle.net/2454/21074
Access Level:acceso abierto
Palabra clave:Image processing
Machine vision
Vision, color and visual optics
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spelling Aggregation functions to combine RGB color channels in stereo matchingGalar Idoate, MikelJurío Munárriz, AránzazuLópez Molina, CarlosSanz Delgado, José AntonioPaternain Dallo, DanielBustince Sola, HumbertoImage processingMachine visionVision, color and visual opticsIn this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching algorithm by aggregating the similarities of the RGB channels which are calculated independently. We compare the accuracy of different stereo matching algorithms and aggregation functions. We show experimentally that the best function depends on the stereo matching algorithm considered, but the dual of the geometric mean excels as the most robust aggregation.This paper has been partially supported by the National Science Foundation of Spain, Reference TIN2010-15055, TIN2011-29520 and the Research Services of the Universidad Publica de Navarra.Optical Society of AmericaAutomática y ComputaciónAutomatika eta KonputazioaUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2454/21074reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarrainstname:Universidad San Jorge (USJ)Inglésinfo:eu-repo/grantAgreement/MICINN//TIN2010-15055info:eu-repo/grantAgreement/MICINN//TIN2011-29520© 2012 Optical Society of America. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modifications of the content of this paper are prohibited.info:eu-repo/semantics/openAccessoai:academica-e.unavarra.es:2454/210742026-06-17T12:41:47Z
dc.title.none.fl_str_mv Aggregation functions to combine RGB color channels in stereo matching
title Aggregation functions to combine RGB color channels in stereo matching
spellingShingle Aggregation functions to combine RGB color channels in stereo matching
Galar Idoate, Mikel
Image processing
Machine vision
Vision, color and visual optics
title_short Aggregation functions to combine RGB color channels in stereo matching
title_full Aggregation functions to combine RGB color channels in stereo matching
title_fullStr Aggregation functions to combine RGB color channels in stereo matching
title_full_unstemmed Aggregation functions to combine RGB color channels in stereo matching
title_sort Aggregation functions to combine RGB color channels in stereo matching
dc.creator.none.fl_str_mv Galar Idoate, Mikel
Jurío Munárriz, Aránzazu
López Molina, Carlos
Sanz Delgado, José Antonio
Paternain Dallo, Daniel
Bustince Sola, Humberto
author Galar Idoate, Mikel
author_facet Galar Idoate, Mikel
Jurío Munárriz, Aránzazu
López Molina, Carlos
Sanz Delgado, José Antonio
Paternain Dallo, Daniel
Bustince Sola, Humberto
author_role author
author2 Jurío Munárriz, Aránzazu
López Molina, Carlos
Sanz Delgado, José Antonio
Paternain Dallo, Daniel
Bustince Sola, Humberto
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Automática y Computación
Automatika eta Konputazioa
Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
dc.subject.none.fl_str_mv Image processing
Machine vision
Vision, color and visual optics
topic Image processing
Machine vision
Vision, color and visual optics
description In this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching algorithm by aggregating the similarities of the RGB channels which are calculated independently. We compare the accuracy of different stereo matching algorithms and aggregation functions. We show experimentally that the best function depends on the stereo matching algorithm considered, but the dual of the geometric mean excels as the most robust aggregation.
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2454/21074
url https://hdl.handle.net/2454/21074
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MICINN//TIN2010-15055
info:eu-repo/grantAgreement/MICINN//TIN2011-29520
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Optical Society of America
publisher.none.fl_str_mv Optical Society of America
dc.source.none.fl_str_mv reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname:Universidad San Jorge (USJ)
instname_str Universidad San Jorge (USJ)
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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