A novel underwater image restoration method based on decomposition network and physical imaging model

International Journal of Intelligent SystemsVolume 37, Issue 9 p. 5672-5690 RESEARCH ARTICLE A novel underwater image restoration method based on decomposition network and physical imaging model Yanfang Cui, Yanfang Cui orcid.org/0000-0001-9142-6549 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorYujuan Sun, Corresponding Author Yujuan Sun [email protected] orcid.org/0000-0001-5127-3402 School of Information and Electrical Engineering, Ludong University, Yantai, China Correspondence Yujuan Sun, School of Information and Electrical Engineering, Ludong University, Hongqi Road 186, Yantai 264025, China. Email: [email protected]Search for more papers by this authorMuwei Jian, Muwei Jian orcid.org/0000-0002-4249-2264 School of Information Science and Engineering, Linyi University, Linyi, China School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, ChinaSearch for more papers by this authorXiaofeng Zhang, Xiaofeng Zhang orcid.org/0000-0001-8978-1058 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorTao Yao, Tao Yao orcid.org/0000-0003-2660-1050 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorXin Gao, Xin Gao orcid.org/0000-0003-2715-7633 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorYiru Li, Yiru Li orcid.org/0000-0002-0424-0357 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorYan Zhang, Yan Zhang orcid.org/0000-0003-1553-3443 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this author Yanfang Cui, Yanfang Cui orcid.org/0000-0001-9142-6549 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorYujuan Sun, Corresponding Author Yujuan Sun [email protected] orcid.org/0000-0001-5127-3402 School of Information and Electrical Engineering, Ludong University, Yantai, China Correspondence Yujuan Sun, School of Information and Electrical Engineering, Ludong University, Hongqi Road 186, Yantai 264025, China. Email: [email protected]Search for more papers by this authorMuwei Jian, Muwei Jian orcid.org/0000-0002-4249-2264 School of Information Science and Engineering, Linyi University, Linyi, China School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, ChinaSearch for more papers by this authorXiaofeng Zhang, Xiaofeng Zhang orcid.org/0000-0001-8978-1058 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorTao Yao, Tao Yao orcid.org/0000-0003-2660-1050 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorXin Gao, Xin Gao orcid.org/0000-0003-2715-7633 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorYiru Li, Yiru Li orcid.org/0000-0002-0424-0357 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this authorYan Zhang, Yan Zhang orcid.org/0000-0003-1553-3443 School of Information and Electrical Engineering, Ludong University, Yantai, ChinaSearch for more papers by this author First published: 29 December 2021 https://doi.org/10.1002/int.22806Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Underwater image restoration is one of the significant research in marine engineering and aquatic robotics. However, due to the propagation characteristics of light and the serious turbidity in underwater, the captured images often have chromatic aberration and scattering blur, which brings great challenges to the restoration of the raw image. In this paper, a revised underwater imaging model is proposed first, which reanalyzes the generation of background light from the atmosphere to the underwater and provides important support for underwater color correction. And then a network framework via the revised model is designed, which can decompose the captured image into different components corresponding to the revised model. The proposed network consists of a decomposition architecture with residual blocks that learns a complete separation of clear image and transmittance features. These two features are used along with the raw image to predict the background light. Finally, combining three constraints of the imaging model, the proposed framework can converge rapidly along the desired direction. By comparison with the performance of the state-of-the-art algorithms, the designed network shows excellent visibility and is capable of removing water on both synthetic and real-world images in different water types. Volume37, Issue9September 2022Pages 5672-5690 RelatedInformation