An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
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 meth...
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doaj-c4d38379e8ec4c10a7c0e879d61c73c92021-03-30T00:29:34ZengIEEEIEEE Access2169-35362019-01-01714023314025110.1109/ACCESS.2019.29321308782094An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater ImagingYan Wang0https://orcid.org/0000-0002-4953-2660Wei Song1https://orcid.org/0000-0002-0604-5563Giancarlo Fortino2https://orcid.org/0000-0002-4039-891XLi-Zhe Qi3Wenqiang Zhang4Antonio Liotta5https://orcid.org/0000-0002-2773-4421Academy for Engineering and Technology, Fudan University, Shanghai, ChinaCollege of Information Technology, Shanghai Ocean University, Shanghai, ChinaDepartment of Informatics, Modeling, Electronics and Systems, University of Calabria, Rende, ItalyAcademy for Engineering and Technology, Fudan University, Shanghai, ChinaShanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, ChinaSchool of Computing, Edinburgh Napier University, Edinburgh, U.K.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.https://ieeexplore.ieee.org/document/8782094/Underwater image formation modelsingle underwater image enhancementsingle underwater image restorationbackground light estimationtransmission map estimation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yan Wang Wei Song Giancarlo Fortino Li-Zhe Qi Wenqiang Zhang Antonio Liotta |
spellingShingle |
Yan Wang Wei Song Giancarlo Fortino Li-Zhe Qi Wenqiang Zhang Antonio Liotta An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging IEEE Access Underwater image formation model single underwater image enhancement single underwater image restoration background light estimation transmission map estimation |
author_facet |
Yan Wang Wei Song Giancarlo Fortino Li-Zhe Qi Wenqiang Zhang Antonio Liotta |
author_sort |
Yan Wang |
title |
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging |
title_short |
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging |
title_full |
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging |
title_fullStr |
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging |
title_full_unstemmed |
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging |
title_sort |
experimental-based review of image enhancement and image restoration methods for underwater imaging |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
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. |
topic |
Underwater image formation model single underwater image enhancement single underwater image restoration background light estimation transmission map estimation |
url |
https://ieeexplore.ieee.org/document/8782094/ |
work_keys_str_mv |
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