弱光照条件下水下图像处理方法研究进展综述

doi:10.3778/j.issn.1002-8331.2503-0281

摘要/Abstract

摘要： 由于复杂水下光学环境影响，水下机器人所获图像普遍存在弱光照引发的对比度衰减、细节模糊及色彩失真等退化现象，严重制约海洋环境的分析。为了深入分析国内外学者在弱光照条件下水下图像处理的研究进展，对近年来相关文献进行了分析总结。分析了水下弱光照条件成因并提出所需处理的主要问题，并根据各类算法的原理特点将水下图像处理方法进行分类；从弱光照条件下水下图像的主要问题切入，详细分析和归纳各类算法的主要特征与不足；通过设计实验在弱光条件下，将传统算法和基于深度学习的水下图像处理方法进行对比分析。最后，总结了一些弱光照条件下水下图像处理领域尚未解决的问题，并对未来研究方向进行了展望。

关键词: 弱光照条件, 水下图像, 图像处理, 深度学习

Abstract: Due to the influence of complex underwater optical environment, the images obtained by underwater vehicles generally have degradation phenomena such as contrast attenuation, detail blur and color distortion caused by weak illumination, which seriously restricts the analysis of ocean environment. In order to deeply analyze the research progress of domestic and foreign scholars on underwater image processing under weak light conditions, the relevant literature in recent years is analyzed and summarized. Firstly, the causes of underwater weak light conditions are analyzed and the main problems to be solved are proposed. Then, the underwater image processing methods are classified according to the principles and characteristics of various algorithms. Secondly, starting from the main problems of underwater images under weak illumination conditions, the main characteristics and shortcomings of various algorithms are analyzed and summarized in detail. Then, the traditional algorithm and the underwater image processing method based on deep learning are compared and analyzed by designing experiments under low light conditions. Finally, some unsolved problems in the field of underwater image processing under weak illumination conditions are summarized, and the future research and development are prospected.

Key words: under low light condition, underwater image, image processing, deep learning

张天驰, 刘强. 弱光照条件下水下图像处理方法研究进展综述[J]. 计算机工程与应用, 2025, 61(21): 30-44.

ZHANG Tianchi, LIU Qiang. Survey of Underwater Image Processing Methods Under Weak Light Conditions[J]. Computer Engineering and Applications, 2025, 61(21): 30-44.

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