Paper Info
Title
A novel underwater image restoration method based on decomposition network and physical imaging model
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.
Year
DOI
Venue
2022
10.1002/int.22806
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
DocType
Volume
decomposition architecture, image restoration, underwater imaging model
Journal
37
Issue
ISSN
Citations 
9
0884-8173
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Yanfang Cui100.34
Yujuan Sun201.01
Muwei Jian323530.97
Xiaofeng Zhang4379.53
Tao Yao561.89
Xin Gao672.82
Yiru Li700.34
Yan Zhang800.34