水下
图像复原
计算机科学
人工智能
计算机视觉
失真(音乐)
图像处理
噪音(视频)
图像(数学)
地质学
电信
海洋学
放大器
带宽(计算)
作者
Min Han,Zhiyu Lyu,Tie Qiu,Mingming Xu
出处
期刊:IEEE transactions on systems, man, and cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2020-05-01
卷期号:50 (5): 1820-1832
被引量:120
标识
DOI:10.1109/tsmc.2017.2788902
摘要
Underwater image processing is an intelligence research field that has great potential to help developers better explore the underwater environment. Underwater image processing has been used in a wide variety of fields, such as underwater microscopic detection, terrain scanning, mine detection, telecommunication cables, and autonomous underwater vehicles. However, underwater imagery suffers from strong absorption, scattering, color distortion, and noise from the artificial light sources, causing image blur, haziness, and a bluish or greenish tone. Therefore, the enhancement of underwater imagery can be divided into two methods: 1) underwater image dehazing and 2) underwater image color restoration. This paper presents the reason for underwater image degradation, surveys the state-of-the-art intelligence algorithms like deep learning methods in underwater image dehazing and restoration, demonstrates the performance of underwater image dehazing and color restoration with different methods, introduces an underwater image color evaluation metric, and provides an overview of the major underwater image applications. Finally, we summarize the application of underwater image processing.
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