《计算机应用研究》|Application Research of Computers

水下图像增强和修复算法综述

Survey of underwater image enhancement and restoration algorithms

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作者 魏郭依哲,陈思遥,刘玉涛,李秀
机构 清华大学深圳国际研究生院,广东 深圳 518055
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文章编号 1001-3695(2021)09-001-2561-09
DOI 10.19734/j.issn.1001-3695.2020.11.0545
摘要 因受到光线散射和吸收、水体杂质、人工光源等因素影响,水下成像质量较低,很难满足生产作业的需求,而水下图像的增强和复原技术有助于提升水下机器视觉的能力。为帮助研究者掌握水下图像处理领域的研究方法和现有技术,对水下图像增强和复原方法进行综述。首先对水下图像存在的主要退化类型进行分析;分别对水下图像增强、复原的经典方法和最新进展进行总结,系统梳理了水下图像质量评测体系和公开数据集;最后对水下图像处理未来的研究趋势进行了展望。
关键词 水下图像增强; 水下图像复原; 深度学习
基金项目 国家自然科学基金资助项目(41876098)
中国博士后科学基金资助项目(2019M650686)
国家重点研发计划资助项目(2020AAA0108303)
深圳市科创委资助项目(JCY20200109143041798)
本文URL http://www.arocmag.com/article/01-2021-09-001.html
英文标题 Survey of underwater image enhancement and restoration algorithms
作者英文名 Wei Guoyizhe, Chen Siyao, Liu Yutao, Li Xiu
机构英文名 Tsinghua Shenzhen International Graduate School,Shenzhen Guangdong 518055,China
英文摘要 Underwater imaging is affected by light scattering and absorption, water impurities, artificial light source and other factors, which leads to poor imaging quality. The enhancement and restoration of underwater images are of great significance to enhance the machine vision in underwater environment. In order to help researchers quickly grasp the research framework and tools in the field of underwater image processing, this paper reviewed the underwater image enhancement and restoration methods. First, this paper introduced the degradation types of underwater images. Then, it reviewed the classical methods and the latest progress of underwater image enhancement and recovery, and presented a brief overview of underwater image evaluation system and datasets. Finally, it prospected the research direction on underwater image enhancement and restoration.
英文关键词 underwater image enhancement; underwater image restoration; deep learning
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收稿日期 2020/11/29
修回日期 2021/2/18
页码 2561-2569,2589
中图分类号 TP391.41
文献标志码 A