Learning-Based Dark and Blurred Underwater Image Restoration

Underwater image processing is a difficult subtopic in the field of computer vision due to the complex underwater environment. Since the light is absorbed and scattered, underwater images have many distortions such as underexposure, blurriness, and color cast. The poor quality hinders subsequent pro...

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Main Authors: Yifeng Xu, Huigang Wang, Garth Douglas Cooper, Shaowei Rong, Weitao Sun
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/6549410
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author Yifeng Xu
Huigang Wang
Garth Douglas Cooper
Shaowei Rong
Weitao Sun
author_facet Yifeng Xu
Huigang Wang
Garth Douglas Cooper
Shaowei Rong
Weitao Sun
author_sort Yifeng Xu
collection DOAJ
description Underwater image processing is a difficult subtopic in the field of computer vision due to the complex underwater environment. Since the light is absorbed and scattered, underwater images have many distortions such as underexposure, blurriness, and color cast. The poor quality hinders subsequent processing such as image classification, object detection, or segmentation. In this paper, we propose a method to collect underwater image pairs by placing two tanks in front of the camera. Due to the high-quality training data, the proposed restoration algorithm based on deep learning achieves inspiring results for underwater images taken in a low-light environment. The proposed method solves two of the most challenging problems for underwater image: darkness and fuzziness. The experimental results show that the proposed method surpasses most other methods.
format Article
id doaj-art-341c9533f091478aa8c94eba30247059
institution Kabale University
issn 1076-2787
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language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-341c9533f091478aa8c94eba302470592025-02-03T06:05:12ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/65494106549410Learning-Based Dark and Blurred Underwater Image RestorationYifeng Xu0Huigang Wang1Garth Douglas Cooper2Shaowei Rong3Weitao Sun4School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaUnderwater image processing is a difficult subtopic in the field of computer vision due to the complex underwater environment. Since the light is absorbed and scattered, underwater images have many distortions such as underexposure, blurriness, and color cast. The poor quality hinders subsequent processing such as image classification, object detection, or segmentation. In this paper, we propose a method to collect underwater image pairs by placing two tanks in front of the camera. Due to the high-quality training data, the proposed restoration algorithm based on deep learning achieves inspiring results for underwater images taken in a low-light environment. The proposed method solves two of the most challenging problems for underwater image: darkness and fuzziness. The experimental results show that the proposed method surpasses most other methods.http://dx.doi.org/10.1155/2020/6549410
spellingShingle Yifeng Xu
Huigang Wang
Garth Douglas Cooper
Shaowei Rong
Weitao Sun
Learning-Based Dark and Blurred Underwater Image Restoration
Complexity
title Learning-Based Dark and Blurred Underwater Image Restoration
title_full Learning-Based Dark and Blurred Underwater Image Restoration
title_fullStr Learning-Based Dark and Blurred Underwater Image Restoration
title_full_unstemmed Learning-Based Dark and Blurred Underwater Image Restoration
title_short Learning-Based Dark and Blurred Underwater Image Restoration
title_sort learning based dark and blurred underwater image restoration
url http://dx.doi.org/10.1155/2020/6549410
work_keys_str_mv AT yifengxu learningbaseddarkandblurredunderwaterimagerestoration
AT huigangwang learningbaseddarkandblurredunderwaterimagerestoration
AT garthdouglascooper learningbaseddarkandblurredunderwaterimagerestoration
AT shaoweirong learningbaseddarkandblurredunderwaterimagerestoration
AT weitaosun learningbaseddarkandblurredunderwaterimagerestoration