A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning

IF 6 3区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Emerging Topics in Computational Intelligence Pub Date : 2026-08-01 Epub Date: 2026-03-30 DOI:10.1109/TETCI.2026.3668671

Xiaofeng Cong;Yu Zhao;Jie Gui;Junming Hou;Dacheng Tao

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引用次数: 0

Abstract

Underwater image enhancement (UIE) presents a significant challenge within computer vision research. Despite the development of numerous UIE algorithms, a thorough and systematic review is still absent. To foster future advancements, we provide a detailed overview of the UIE task from several perspectives. Firstly, we introduce the physical models, data construction processes, evaluation metrics, and loss functions. Secondly, we categorize and discuss recent algorithms based on their contributions, considering six aspects: network architecture, learning strategy, learning stage, auxiliary tasks, domain perspective, and disentanglement fusion. Thirdly, due to the varying experimental setups in the existing literature, a comprehensive and unbiased comparison is currently unavailable. To address this, we perform both quantitative and qualitative evaluations of state-of-the-art algorithms across multiple benchmark datasets. Lastly, we identify key areas for future research in UIE.

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基于深度学习的水下图像增强研究综述

水下图像增强（UIE）是计算机视觉研究中的一个重大挑战。尽管开发了许多UIE算法，但仍然缺乏彻底和系统的审查。为了促进未来的发展，我们从几个角度对UIE任务进行了详细的概述。首先，我们介绍了物理模型、数据构建过程、评价指标和损失函数。其次，我们从网络架构、学习策略、学习阶段、辅助任务、领域视角和解纠缠融合六个方面对最近的算法进行了分类和讨论。第三，由于现有文献中的实验设置不同，目前无法进行全面和公正的比较。为了解决这个问题，我们在多个基准数据集上对最先进的算法进行了定量和定性评估。最后，我们确定了UIE未来研究的关键领域。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Emerging Topics in Computational Intelligence Mathematics-Control and Optimization

CiteScore

10.30

自引率

7.50%

发文量

147

期刊介绍： The IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) publishes original articles on emerging aspects of computational intelligence, including theory, applications, and surveys. TETCI is an electronics only publication. TETCI publishes six issues per year. Authors are encouraged to submit manuscripts in any emerging topic in computational intelligence, especially nature-inspired computing topics not covered by other IEEE Computational Intelligence Society journals. A few such illustrative examples are glial cell networks, computational neuroscience, Brain Computer Interface, ambient intelligence, non-fuzzy computing with words, artificial life, cultural learning, artificial endocrine networks, social reasoning, artificial hormone networks, computational intelligence for the IoT and Smart-X technologies.