Edge-preserving color image denoising through tensor voting

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dc.contributor.author Moreno, Rodrigo
dc.contributor.author García, Miguel Ángel
dc.contributor.author Puig, Domenec
dc.contributor.author Juli, Carme
dc.contributor.other UAM. Departamento de Tecnología Electrónica y de las Comunicaciones es_ES
dc.date.accessioned 2015-07-20T08:49:59Z
dc.date.available 2015-07-20T08:49:59Z
dc.date.issued 2011-11
dc.identifier.citation Computer Vision and Image Understanding 115.11 (2011): 1536-1551 en_US
dc.identifier.issn 1077-3142 (print) en_US
dc.identifier.issn 1090-235X (online) en_US
dc.identifier.uri http://hdl.handle.net/10486/667453
dc.description This is the author’s version of a work that was accepted for publication in Computer Vision and Image Understanding. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Vision and Image Understanding, 115, 11 (2011) DOI: 10.1016/j.cviu.2011.07.005 en_US
dc.description.abstract This paper presents a new method for edge-preserving color image denoising based on the tensor voting framework, a robust perceptual grouping technique used to extract salient information from noisy data. The tensor voting framework is adapted to encode color information through tensors in order to propagate them in a neighborhood by using a specific voting process. This voting process is specifically designed for edge-preserving color image denoising by taking into account perceptual color differences, region uniformity and edginess according to a set of intuitive perceptual criteria. Perceptual color differences are estimated by means of an optimized version of the CIEDE2000 formula, while uniformity and edginess are estimated by means of saliency maps obtained from the tensor voting process. Measurements of removed noise, edge preservation and undesirable introduced artifacts, additionally to visual inspection, show that the proposed method has a better performance than the state-of-the-art image denoising algorithms for images contaminated with CCD camera noise. en_US
dc.description.sponsorship This research has been partially supported by the Spanish Ministry of Science and Technology under project DPI2007-66556-C03-03, by the Commissioner for Universities and Research of the Department of Innovation, Universities and Companies of the Catalonian Government and by the European Social Fund. en_US
dc.format.extent 40 pág. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher Elsevier B.V. en_US
dc.relation.ispartof Computer Vision and Image Understanding en_US
dc.rights © 2011 Elsevier B.V. All rights reserved en_US
dc.subject.other CIEDE2000 en_US
dc.subject.other CIELAB en_US
dc.subject.other Edge preservation en_US
dc.subject.other Image denoising en_US
dc.subject.other Perceptual grouping en_US
dc.subject.other Tensor voting en_US
dc.title Edge-preserving color image denoising through tensor voting en_US
dc.type article en_US
dc.type conferenceObject en
dc.subject.eciencia Informática es_ES
dc.subject.eciencia Telecomunicaciones es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.cviu.2011.07.005
dc.identifier.doi 10.1016/j.cviu.2011.07.005
dc.identifier.publicationfirstpage 1536
dc.identifier.publicationissue 11
dc.identifier.publicationlastpage 1551
dc.identifier.publicationvolume 115
dc.relation.eventdate September 2-4, 2009 en_US
dc.relation.eventnumber 13
dc.relation.eventplace Münster (Germany) en_US
dc.relation.eventtitle 13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 en_US
dc.type.version info:eu-repo/semantics/acceptedVersion en
dc.contributor.group Tratamiento e Interpretación de Vídeo (ING EPS-006) es_ES
dc.rights.cc Reconocimiento – NoComercial – SinObraDerivada es_ES
dc.rights.accessRights openAccess en


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