Locally Adaptive Color Correction for Underwater Image Dehazing and Matching

Codruta O. Ancuti, Cosmin Ancuti, Christophe De Vleeschouwer, Rafael Garcia; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017, pp. 1-9

Abstract


Underwater images are known to be strongly deterio- rated by a combination of wavelength-dependent light at- tenuation and scattering. This results in complex color casts that depend both on the scene depth map and on the light spectrum. Color transfer, which is a technique of choice to counterbalance color casts, assumes stationary casts, de- fined by global parameters, and is therefore not directly ap- plicable to the locally variable color casts encountered in underwater scenarios. To fill this gap, this paper introduces an original fusion-based strategy to exploit color transfer while tuning the color correction locally, as a function of the light attenuation level estimated from the red channel. The Dark Channel Prior (DCP) is then used to restore the color compensated image, by inverting the simplified Koschmieder light transmission model, as for outdoor de- hazing. Our technique enhances image contrast in a quite effective manner and also supports accurate transmission map estimation. Our extensive experiments also show that our color correction strongly improves the effectiveness of local keypoints matching.

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[bibtex]
@InProceedings{Ancuti_2017_CVPR_Workshops,
author = {Ancuti, Codruta O. and Ancuti, Cosmin and De Vleeschouwer, Christophe and Garcia, Rafael},
title = {Locally Adaptive Color Correction for Underwater Image Dehazing and Matching},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {July},
year = {2017}
}