Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise
Underwater images typically present poor visibility, color distortion, and noise, which limit the application in several high-level tasks of image analysis. To address these corruptions, a novel method is proposed to reconstruct high-quality underwater images, which is designed by integrating imagin...
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| Format: | Article |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10529991/ |
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| author | Chenggang Dai Mingxing Lin |
| author_facet | Chenggang Dai Mingxing Lin |
| author_sort | Chenggang Dai |
| collection | DOAJ |
| description | Underwater images typically present poor visibility, color distortion, and noise, which limit the application in several high-level tasks of image analysis. To address these corruptions, a novel method is proposed to reconstruct high-quality underwater images, which is designed by integrating imaging model with noise and variational framework. Specifically, an improved underwater imaging model is first introduced by separating noise from real underwater scene. Subsequently, the hazy curves of degraded colors are decomposed to estimate transmission map, and a color loss prior is employed to correct the transmission map. Moreover, a first-order gradient guided filter is proposed to refine the transmission map. An evaluation formula is designed by combining illumination, contrast, and color deviation priors to accurately search for the background region. Finally, a variational model is established to restore underwater images and suppress noise based on the improved imaging model and image priors. Experimental results validate that the proposed method surpasses several outstanding approaches, demonstrating its well effectiveness in improving contrast, correcting color, and suppressing noise. |
| format | Article |
| id | doaj-art-d6d30f5ce67a4febb38809877127ef21 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-d6d30f5ce67a4febb38809877127ef212025-08-20T03:21:27ZengIEEEIEEE Access2169-35362024-01-0112824278244210.1109/ACCESS.2024.340053310529991Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With NoiseChenggang Dai0https://orcid.org/0000-0002-8386-794XMingxing Lin1https://orcid.org/0000-0003-0291-0158School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, Shandong, ChinaSchool of Mechanical Engineering, Shandong University, Jinan, Shandong, ChinaUnderwater images typically present poor visibility, color distortion, and noise, which limit the application in several high-level tasks of image analysis. To address these corruptions, a novel method is proposed to reconstruct high-quality underwater images, which is designed by integrating imaging model with noise and variational framework. Specifically, an improved underwater imaging model is first introduced by separating noise from real underwater scene. Subsequently, the hazy curves of degraded colors are decomposed to estimate transmission map, and a color loss prior is employed to correct the transmission map. Moreover, a first-order gradient guided filter is proposed to refine the transmission map. An evaluation formula is designed by combining illumination, contrast, and color deviation priors to accurately search for the background region. Finally, a variational model is established to restore underwater images and suppress noise based on the improved imaging model and image priors. Experimental results validate that the proposed method surpasses several outstanding approaches, demonstrating its well effectiveness in improving contrast, correcting color, and suppressing noise.https://ieeexplore.ieee.org/document/10529991/Underwater image restorationvariational frameworkimaging model with noise |
| spellingShingle | Chenggang Dai Mingxing Lin Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise IEEE Access Underwater image restoration variational framework imaging model with noise |
| title | Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise |
| title_full | Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise |
| title_fullStr | Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise |
| title_full_unstemmed | Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise |
| title_short | Single Underwater Image Restoration Using Variational Framework Guided by Imaging Model With Noise |
| title_sort | single underwater image restoration using variational framework guided by imaging model with noise |
| topic | Underwater image restoration variational framework imaging model with noise |
| url | https://ieeexplore.ieee.org/document/10529991/ |
| work_keys_str_mv | AT chenggangdai singleunderwaterimagerestorationusingvariationalframeworkguidedbyimagingmodelwithnoise AT mingxinglin singleunderwaterimagerestorationusingvariationalframeworkguidedbyimagingmodelwithnoise |