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Underwater image and video dehazing with pure haze region segmentation

Emberton, Simon; Chittka, Lars; Cavallaro, Andrea


Lars Chittka

Andrea Cavallaro


© 2017 The Authors 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.

Journal Article Type Article
Publication Date Mar 1, 2018
Journal Computer Vision and Image Understanding
Print ISSN 1077-3142
Electronic ISSN 1090-235X
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 168
Pages 145-156
APA6 Citation Emberton, S., Chittka, L., & Cavallaro, A. (2018). Underwater image and video dehazing with pure haze region segmentation. Computer Vision and Image Understanding, 168, 145-156.
Keywords dehazing, image processing, segmentation, underwater, white balancing, video processing
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