Automatic Red-Channel underwater image restoration
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2015-01
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Abstract
Underwater images typically exhibit color distortion and low contrast as a result of the exponential decay that light suffers as it travels. Moreover, colors associated to different wavelengths have different attenuation rates, being the red wavelength the one that attenuates the fastest. To restore underwater images, we propose a Red Channel method, where colors associated to short wavelengths are recovered, as expected for underwater images, leading to a recovery of the lost contrast. The Red Channel method can be interpreted as a variant of the Dark Channel method used for images degraded by the atmosphere when exposed to haze. Experimental results show that our technique handles gracefully artificially illuminated areas, and achieves a natural color correction and superior or equivalent visibility improvement when compared to other state-of-the-art methods.
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Publisher Copyright: © 2014 Elsevier Inc.
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Underwater image restoration , Color correction , Image dehazing , Contrast enhancement , Visibility recovery , Dark Channel , Artificial lighting , Attenuation , Underwater image degradation , Underwater image restoration , Color correction , Image dehazing , Contrast enhancement , Visibility recovery , Dark Channel , Artificial lighting , Attenuation , Underwater image degradation , Signal Processing , Media Technology , Computer Vision and Pattern Recognition , Electrical and Electronic Engineering , Funding Info , David Pardo was partially funded by the Project of the Spanish Ministry of Economy and Competitiveness with reference MTM2013-40824-P, the BCAM "Severo Ochoa" accreditation of excellence SEV-2013-0323, the CYTED 2011 Project 712RT0449, and the Basque Government Consolidated Research Group Grant IT649-13 on "Mathematical Modeling, Simulation, and Industrial Applications (M2SI)". , David Pardo was partially funded by the Project of the Spanish Ministry of Economy and Competitiveness with reference MTM2013-40824-P, the BCAM "Severo Ochoa" accreditation of excellence SEV-2013-0323, the CYTED 2011 Project 712RT0449, and the Basque Government Consolidated Research Group Grant IT649-13 on "Mathematical Modeling, Simulation, and Industrial Applications (M2SI)".
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Galdran , A , Pardo , D , Picon , A & Alvarez-Gila , A 2015 , ' Automatic Red-Channel underwater image restoration ' , unknown , vol. unknown , pp. 132-145 . https://doi.org/10.1016/j.jvcir.2014.11.006