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dc.contributor.authorEMBERTON, S
dc.contributor.authorChittka, L
dc.contributor.authorCavallaro, A
dc.date.accessioned2017-09-15T09:28:36Z
dc.date.available2017-09-15T09:28:36Z
dc.date.issued2017-08
dc.date.submitted2017-09-01T10:18:01.958Z
dc.identifier.citationEmberton, S., Chittka, L. and Cavallaro, A. (2017). Underwater image and video dehazing with pure haze region segmentation. [online] Computer Vision and Image Understanding. Available at: http://www.sciencedirect.com/science/article/pii/S1077314217301418?via%3Dihub [Accessed 15 Sep. 2017].en_US
dc.identifier.issn1077-3142
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/25704
dc.description.abstractUnderwater scenes captured by cameras are plagued with poor contrast and a spectral distortion, which are the result of the scattering and absorptive properties of water. In this paper we present a novel dehazing method that improves visibility in images and videos by detecting and segmenting image regions that contain only water. The colour of these regions, which we refer to as pure haze regions, is similar to the haze that is removed during the dehazing process. Moreover, we propose a semantic white balancing approach for illuminant estimation that uses the dominant colour of the water to address the spectral distortion present in underwater scenes. To validate the results of our method and compare them to those obtained with state-of-the-art approaches, we perform extensive subjective evaluation tests using images captured in a variety of water types and underwater videos captured onboard an underwater vehicle.en_US
dc.description.sponsorshipS. Emberton was supported by the UK EPSRC Doctoral Training Centre EP/G03723X/1. Portions of the research in this paper use the PKU-EAQA dataset collected under the sponsorship of the National Natural Science Foundation of China.en_US
dc.languageEnglish
dc.publisherElsevieren_US
dc.relation.ispartofComputer Vision and Image Understanding
dc.relation.isreplacedby123456789/32415
dc.relation.isreplacedbyhttp://qmro.qmul.ac.uk/xmlui/handle/123456789/32415
dc.rightsThis is a pre-copyedited, author-produced version of an article accepted for publication in Computer Vision and Image Understanding following peer review. The version of record is available http://www.sciencedirect.com/science/article/pii/S1077314217301418?via%3Dihub
dc.subjectDehazingen_US
dc.subjectImage processingen_US
dc.subjectSegmentationen_US
dc.subjectUnderwateren_US
dc.subjectWhite balancingen_US
dc.subjectVideo processingen_US
dc.titleUnderwater image and video dehazing with pure haze region segmentationen_US
dc.typeArticleen_US
dc.rights.holderhttps://doi.org/10.1016/j.cviu.2017.08.003
dc.identifier.doi10.1016/j.cviu.2017.08.003
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Biological and Chemical Sciences - Staff
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Electronic Engineering and Computer Science - Computer Science - Research Students
pubs.organisational-group/Queen Mary University of London/Faculty Reporting - Research Students
pubs.organisational-group/Queen Mary University of London/Faculty Reporting - Research Students/Faculty of Science & Engineering PGRs
pubs.publication-statusPublished online
pubs.publisher-urlhttps://www.elsevier.com/


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