dc.contributor.author | EMBERTON, S | |
dc.contributor.author | Chittka, L | |
dc.contributor.author | Cavallaro, A | |
dc.date.accessioned | 2017-09-15T09:28:36Z | |
dc.date.available | 2017-09-15T09:28:36Z | |
dc.date.issued | 2017-08 | |
dc.date.submitted | 2017-09-01T10:18:01.958Z | |
dc.identifier.citation | Emberton, 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.issn | 1077-3142 | |
dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/25704 | |
dc.description.abstract | Underwater 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.sponsorship | S. 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.language | English | |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | Computer Vision and Image Understanding | |
dc.relation.isreplacedby | 123456789/32415 | |
dc.relation.isreplacedby | http://qmro.qmul.ac.uk/xmlui/handle/123456789/32415 | |
dc.rights | This 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.subject | Dehazing | en_US |
dc.subject | Image processing | en_US |
dc.subject | Segmentation | en_US |
dc.subject | Underwater | en_US |
dc.subject | White balancing | en_US |
dc.subject | Video processing | en_US |
dc.title | Underwater image and video dehazing with pure haze region segmentation | en_US |
dc.type | Article | en_US |
dc.rights.holder | https://doi.org/10.1016/j.cviu.2017.08.003 | |
dc.identifier.doi | 10.1016/j.cviu.2017.08.003 | |
pubs.publication-status | Published online | |
pubs.publisher-url | https://www.elsevier.com/ | |