IEEE Access · 2019 · 294 citations · 103 references
EngineeringOcean EngineeringOcean AcousticsRestoration TheoryUnderwater AcousticsImage EnhancementImage QualityImage Quality AssessmentImage RestorationUnderwater PerceptionComparative EvaluationDigital Image EnhancementImage Restoration Quality AssessmentLight AbsorptionQuality DegradationUnderwater Image EnhancementUnderwater Image ProcessingUnderwater Image Restoration
Underwater images are crucial for ocean exploration but suffer severe degradation from light absorption and scattering, and although recent image enhancement advances exist, their specific applicability to underwater imaging remains unaddressed. This paper reviews image enhancement and restoration techniques that tackle typical underwater impairments, including extreme degradations and distortions. The authors analyze the causes of underwater quality loss via the image formation model, compare IFM‑free and IFM‑based restoration methods, and conduct experimental evaluations using subjective and objective metrics, with code freely available at the provided GitHub repository. The review highlights key shortcomings of existing methods, offers recommendations, and underscores challenges and opportunities for future research in underwater image enhancement and restoration.
Underwater images play a key role in ocean exploration but often suffer from severe quality degradation due to light absorption and scattering in water medium. Although major breakthroughs have been made recently in the general area of image enhancement and restoration, the applicability of new methods for improving the quality of underwater images has not specifically been captured. In this paper, we review the image enhancement and restoration methods that tackle typical underwater image impairments, including some extreme degradations and distortions. First, we introduce the key causes of quality reduction in underwater images, in terms of the underwater image formation model (IFM). Then, we review underwater restoration methods, considering both the IFM-free and the IFM-based approaches. Next, we present an experimental-based comparative evaluation of the state-of-the-art IFM-free and IFM-based methods, considering also the prior-based parameter estimation algorithms of the IFM-based methods, using both subjective and objective analyses (the used code is freely available at https://github.com/wangyanckxx/Single-Underwater-Image-Enhancement-and-Color-Restoration). Starting from this paper, we pinpoint the key shortcomings of existing methods, drawing recommendations for future research in this area. Our review of underwater image enhancement and restoration provides researchers with the necessary background to appreciate challenges and opportunities in this important field.
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