Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13439
DC FieldValueLanguage
dc.contributor.authorMangeruga, Marino-
dc.contributor.authorBruno, Fabio-
dc.contributor.authorCozza, Marco-
dc.contributor.authorAgrafiotis, Panagiotis-
dc.contributor.authorSkarlatos, Dimitrios-
dc.date.accessioned2019-04-04T21:18:07Z-
dc.date.available2019-04-04T21:18:07Z-
dc.date.issued2018-10-01-
dc.identifier.citationRemote Sensing, 2018, vol. 10, no. 10en_US
dc.identifier.issn20724292-
dc.description.abstractImages obtained in an underwater environment are often affected by colour casting and suffer from poor visibility and lack of contrast. In the literature, there are many enhancement algorithms that improve different aspects of the underwater imagery. Each paper, when presenting a new algorithm or method, usually compares the proposed technique with some alternatives present in the current state of the art. There are no studies on the reliability of benchmarking methods, as the comparisons are based on various subjective and objective metrics. This paper would pave the way towards the definition of an effective methodology for the performance evaluation of the underwater image enhancement techniques. Moreover, this work could orientate the underwater community towards choosing which method can lead to the best results for a given task in different underwater conditions. In particular, we selected five well-known methods from the state of the art and used them to enhance a dataset of images produced in various underwater sites with different conditions of depth, turbidity, and lighting. These enhanced images were evaluated by means of three different approaches: objective metrics often adopted in the related literature, a panel of experts in the underwater field, and an evaluation based on the results of 3D reconstructions.en_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.ispartofRemote Sensingen_US
dc.rights© by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) licenseen_US
dc.subject3D reconstructionen_US
dc.subjectAutomatic colour equalizationen_US
dc.subjectBenchmarken_US
dc.subjectCLAHEen_US
dc.subjectColour correctionen_US
dc.subjectDehazingen_US
dc.subjectLaben_US
dc.subjectNon-local dehazingen_US
dc.subjectScreened poisson equationen_US
dc.subjectUnderwater image enhancementen_US
dc.titleGuidelines for underwater image enhancement based on benchmarking of different methodsen_US
dc.typeArticleen_US
dc.collaborationUniversity of Calabriaen_US
dc.collaboration3D Research s.r.l.en_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.journalsOpen Accessen_US
dc.countryItalyen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3390/rs10101652en_US
dc.relation.issue10en_US
dc.relation.volume10en_US
cut.common.academicyear2018-2019en_US
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.languageiso639-1en-
crisitem.journal.journalissn2072-4292-
crisitem.journal.publisherMDPI-
crisitem.project.grantnoH2020 RIA CULT-COOP-08-2016-
crisitem.project.fundingProgramH2020-
crisitem.project.openAireinfo:eu-repo/grantAgreement/EC/H2020/727153-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-4474-5007-
crisitem.author.orcid0000-0002-2732-4780-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
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