Automatic Red-Channel underwater image restoration

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dc.contributor.authorGaldran, Adrian
dc.contributor.authorPardo, David
dc.contributor.authorPicon, Artzai
dc.contributor.authorAlvarez-Gila, Aitor
dc.contributor.institutionTecnalia Research & Innovation
dc.contributor.institutionCOMPUTER_VISION
dc.contributor.institutionVISUAL
dc.date.issued2015-01
dc.descriptionPublisher Copyright: © 2014 Elsevier Inc.
dc.description.abstractUnderwater images typically exhibit color distortion and low contrast as a result of the exponential decay that light suffers as it travels. Moreover, colors associated to different wavelengths have different attenuation rates, being the red wavelength the one that attenuates the fastest. To restore underwater images, we propose a Red Channel method, where colors associated to short wavelengths are recovered, as expected for underwater images, leading to a recovery of the lost contrast. The Red Channel method can be interpreted as a variant of the Dark Channel method used for images degraded by the atmosphere when exposed to haze. Experimental results show that our technique handles gracefully artificially illuminated areas, and achieves a natural color correction and superior or equivalent visibility improvement when compared to other state-of-the-art methods.en
dc.description.statusPeer reviewed
dc.format.extent14
dc.format.extent1251933
dc.identifier.citationGaldran , A , Pardo , D , Picon , A & Alvarez-Gila , A 2015 , ' Automatic Red-Channel underwater image restoration ' , unknown , vol. unknown , pp. 132-145 . https://doi.org/10.1016/j.jvcir.2014.11.006
dc.identifier.doi10.1016/j.jvcir.2014.11.006
dc.identifier.otherresearchoutputwizard: 11556/314
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=84918778399&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofunknown
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordsUnderwater image restoration
dc.subject.keywordsColor correction
dc.subject.keywordsImage dehazing
dc.subject.keywordsContrast enhancement
dc.subject.keywordsVisibility recovery
dc.subject.keywordsDark Channel
dc.subject.keywordsArtificial lighting
dc.subject.keywordsAttenuation
dc.subject.keywordsUnderwater image degradation
dc.subject.keywordsUnderwater image restoration
dc.subject.keywordsColor correction
dc.subject.keywordsImage dehazing
dc.subject.keywordsContrast enhancement
dc.subject.keywordsVisibility recovery
dc.subject.keywordsDark Channel
dc.subject.keywordsArtificial lighting
dc.subject.keywordsAttenuation
dc.subject.keywordsUnderwater image degradation
dc.subject.keywordsSignal Processing
dc.subject.keywordsMedia Technology
dc.subject.keywordsComputer Vision and Pattern Recognition
dc.subject.keywordsElectrical and Electronic Engineering
dc.subject.keywordsFunding Info
dc.subject.keywordsDavid Pardo was partially funded by the Project of the Spanish Ministry of Economy and Competitiveness with reference MTM2013-40824-P, the BCAM "Severo Ochoa" accreditation of excellence SEV-2013-0323, the CYTED 2011 Project 712RT0449, and the Basque Government Consolidated Research Group Grant IT649-13 on "Mathematical Modeling, Simulation, and Industrial Applications (M2SI)".
dc.subject.keywordsDavid Pardo was partially funded by the Project of the Spanish Ministry of Economy and Competitiveness with reference MTM2013-40824-P, the BCAM "Severo Ochoa" accreditation of excellence SEV-2013-0323, the CYTED 2011 Project 712RT0449, and the Basque Government Consolidated Research Group Grant IT649-13 on "Mathematical Modeling, Simulation, and Industrial Applications (M2SI)".
dc.titleAutomatic Red-Channel underwater image restorationen
dc.typejournal article
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