水下退化图像恢复技术:研究现状与未来趋势OA
Underwater image restoration technology:Current research status and future trends
高质量的水下视觉图像输入先验信息对于水下机器人完成多种作业任务至关重要.文中首先分析水下图像退化成因,从原理上解释常见的图像退化类型,并引出了退化恢复的两种途径:水下图像增强和水下相机标定.其次,系统梳理了水下图像增强方法的研究现状、现有水下数据集以及水下图像质量评价体系.随后,总结了水下相机标定方法及其优点与不足.最后,对水下退化恢复技术的未来研究趋势进行综述,涉及增强算法的鲁棒性和泛化能力、多传感器融合与高级视觉任务集成等领域.
High-quality underwater visual image input prior information is crucial for underwater robots to accomplish various operational tasks.This paper first analyzes the causes of underwater image degradation,explaining different types of common image degradation from theoretical principles,and introduces two approaches to degradation recovery:underwater image enhancement and underwater camera calibration.Secondly,it systematically reviews the current research status of underwater image enhancement methods,existing underwater datasets,and underwater image quality evaluation systems.Subsequently,it summarizes underwater camera calibration methods,along with their advantages and limitations.Finally,the paper presents future research trends in underwater degradation recovery technology,including the robustness and generalization capability of enhancement algorithms,multi-sensor fusion,and integration with high-level vision tasks.
查富生;吕品;郭伟;王鹏飞;孙立宁
哈尔滨工业大学/机器人技术与系统国家重点实验室,黑龙江 哈尔滨 150001哈尔滨工业大学/机器人技术与系统国家重点实验室,黑龙江 哈尔滨 150001哈尔滨工业大学/机器人技术与系统国家重点实验室,黑龙江 哈尔滨 150001哈尔滨工业大学/机器人技术与系统国家重点实验室,黑龙江 哈尔滨 150001哈尔滨工业大学/机器人技术与系统国家重点实验室,黑龙江 哈尔滨 150001
海洋科学
水下机器人水下图像增强水下相机标定深度学习
underwater robotunderwater image enhancementunderwater camera calibrationdeep learning
《中山大学学报(自然科学版)(中英文)》 2026 (1)
1-12,12
国家重点研发计划(2022YFB4601800)
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