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随着海洋资源开发工作的不断推进，水下图像增强、目标检测与目标跟踪等计算机视觉技术在海洋探测中的应用日益广泛，已成为水下视觉感知研究领域的热点。本文首先总结了水下目标检测与跟踪方面存在的困难，分析了水下视觉感知任务之间的协同关系，然后从水下图像增强、水下目标检测和水下目标跟踪三个方面对近年来的主要研究方法、技术框架进行了系统梳理和综述，并且着重介绍了基于提示学习的水下图像增强、轻量化水下目标检测和基于提示学习的水下目标跟踪等方面的研究进展。最后展望未来，总结分析了基于计算机视觉的水下图像与目标处理将面临的若干挑战，即水下数据集的建设、多任务间的协同、大模型的应用以及在实际环境的部署和应用等。
Abstract：With the continuous advancement of marine resource development, computer vision technologies have been increasingly applied in marine exploration. Underwater image enhancement, object detection, and target tracking have become hotspots in the research field of underwater visual perception. This paper begins by summarizing the difficulties in underwater target detection and tracking, and analyzes the collaborative relationship among underwater visual perception tasks. It then systematically reviews the main research methods and technical frameworks in recent years from three aspects: underwater image enhancement, underwater target detection, and underwater target tracking. Special attention is given to the research progress in underwater image enhancement based on prompt learning, lightweight underwater target detection, and underwater target tracking based on prompt learning. Finally, this paper discusses future challenges for underwater image and target processing based on computer vision, including the construction of underwater datasets, collaboration among multiple tasks, the application of large models, deployment and application in real-world environments.
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基本信息:
中图分类号:TP391.41;P74
引用信息:
[1]张明华,杨凌霄,张子其,等.基于计算机视觉的水下目标检测与跟踪：现状与展望[J].海洋信息技术与应用,2026,41(01):1-20.
2025-06-23
2025
2025-08-20
2025
1
2026-02-12
2026-02-12