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.

中文翻译：

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水下图像智能去雾与色彩还原综述

水下图像处理是一个很有潜力的智能研究领域，可以帮助开发者更好地探索水下环境。水下图像处理已被广泛应用于各种领域，例如水下显微检测、地形扫描、水雷检测、电信电缆和自主水下航行器。然而，水下图像会受到来自人造光源的强烈吸收、散射、颜色失真和噪声的影响，导致图像模糊、模糊以及偏蓝或偏绿的色调。因此，水下图像的增强可以分为两种方法：1）水下图像去雾和2）水下图像色彩还原。本文介绍了水下图像质量下降的原因，调查了最先进的智能算法，如水下图像去雾和恢复中的深度学习方法，展示了使用不同方法的水下图像去雾和颜色恢复的性能，介绍了水下图像颜色评估指标，并概述了主要的水下图像应用。最后，我们总结了水下图像处理的应用。