Enhanced variational image dehazing

Simple item page
dc.contributor.authorGaldran, Adrian
dc.contributor.authorVazquez-Corral, Javier
dc.contributor.authorPardo, David
dc.contributor.authorBertalmío, Marcelo
dc.contributor.institutionTecnalia Research & Innovation
dc.date.issued2015-07-28
dc.descriptionPublisher Copyright: © 2015 Society for Industrial and Applied Mathematics.
dc.description.abstractImages obtained under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and conventional methods are unable to overcome this problem. In this work, we extend a well-known perception-inspired variational framework for single image dehazing. Two main improvements are proposed. First, we replace the value used by the framework for the gray-world hypothesis by an estimation of the mean of the clean image. Second, we add a set of new terms to the energy functional for maximizing the interchannel contrast. Experimental results show that the proposed enhanced variational image dehazing (EVID) method outperforms other state-of-the-art methods both qualitatively and quantitatively. In particular, when the illuminant is uneven, our EVID method is the only one that recovers realistic colors, avoiding the appearance of strong chromatic artifacts.en
dc.description.statusPeer reviewed
dc.format.extent28
dc.identifier.citationGaldran , A , Vazquez-Corral , J , Pardo , D & Bertalmío , M 2015 , ' Enhanced variational image dehazing ' , SIAM Journal on Imaging Sciences , vol. 8 , no. 3 , pp. 1519-1546 . https://doi.org/10.1137/15M1008889
dc.identifier.doi10.1137/15M1008889
dc.identifier.issn1936-4954
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=84943535634&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofSIAM Journal on Imaging Sciences
dc.relation.projectIDHorizon 2020 Framework Programme, H2020, 644202
dc.relation.projectIDSeventh Framework Programme, FP7, 306337
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordsContrast enhancement
dc.subject.keywordsImage dehazing
dc.subject.keywordsPerceptual color correction
dc.subject.keywordsVariational image processing
dc.subject.keywordsVisibility enhancement
dc.subject.keywordsGeneral Mathematics
dc.subject.keywordsApplied Mathematics
dc.titleEnhanced variational image dehazingen
dc.typejournal article
Files