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Πεδίο DCΤιμήΓλώσσα
dc.contributor.authorMangeruga, Marino-
dc.contributor.authorCozza, Marco-
dc.contributor.authorBruno, Fabio-
dc.date.accessioned2020-10-15T10:37:53Z-
dc.date.available2020-10-15T10:37:53Z-
dc.date.issued2018-01-16-
dc.identifier.citationJournal of Marine Science and Engineering, 2018 Vol. 6, no. 1en_US
dc.identifier.issn20771312-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/19162-
dc.description.abstractUnderwater images usually suffer from poor visibility, lack of contrast and colour casting, mainly due to light absorption and scattering. In literature, there are many algorithms aimed to enhance the quality of underwater images through different approaches. Our purpose was to identify an algorithm that performs well in different environmental conditions. We have selected some algorithms from the state of the art and we have employed them to enhance a dataset of images produced in various underwater sites, representing different environmental and illumination conditions. These enhanced images have been evaluated through some quantitative metrics. By analysing the results of these metrics, we tried to understand which of the selected algorithms performed better than the others. Another purpose of our research was to establish if a quantitative metric was enough to judge the behaviour of an underwater image enhancement algorithm. We aim to demonstrate that, even if the metrics can provide an indicative estimation of image quality, they could lead to inconsistent or erroneous evaluationsen_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relationAdvanced VR, iMmersive serious games and Augmented REality as tools to raise awareness and access to European underwater CULTURal heritageen_US
dc.relation.ispartofJournal of Marine Science and Engineeringen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectUnderwater image enhancementen_US
dc.subjectDehazingen_US
dc.subjectColour correctionen_US
dc.subjectAutomatic colour equalizationen_US
dc.subjectContrast Limiteden_US
dc.subjectAdaptive Histogram Equalization (CLAHE)en_US
dc.titleEvaluation of Underwater Image Enhancement Algorithms under Different Environmental Conditionsen_US
dc.typeArticleen_US
dc.collaboration3D Research s.r.l.en_US
dc.collaborationUniversity of Calabriaen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.journalsOpen Accessen_US
dc.countryItalyen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3390/jmse6010010en_US
dc.relation.issue1en_US
dc.relation.volume6en_US
cut.common.academicyear2018-2019en_US
item.openairetypearticle-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextWith Fulltext-
crisitem.journal.journalissn2077-1312-
crisitem.journal.publisherMDPI-
crisitem.project.grantnoH2020 RIA CULT-COOP-08-2016-
crisitem.project.fundingProgramH2020-
crisitem.project.openAireinfo:eu-repo/grantAgreement/EC/H2020/727153-
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