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涉水视觉
Water-Related Vision

查看参考文献183篇

李学龙 1,2  
文摘 地球表面有约71%的面积被江河湖海等水体覆盖,陆地上的成像也会受到云雪雨雾等水体影响,但是,当前常见的机器视觉科研工作和应用系统基本只围绕空气和真空介质中的视觉任务展开,涉及不同形态水体的视觉工作没有得到系统的研究.涉水视觉(water-related vision)作为涉水光学技术在视觉领域的具象化体现,重点研究光与水的物质相互作用及跨介质传播过程中,涉水视觉影像信号智能处理与分析方面的科学问题,以及先进智能涉水视觉装备研制方面的工程技术问题.本文从“为什么大海是蓝色的?”这一具有普适意义的问题出发,系统介绍了水对光的吸收、散射、衰减作用机理,对涉水视觉任务造成的影响,以及现有的涉水图像处理与解析方法.本文基于水体光学特性及成像退化机理,介绍了团队在探索涉水成像和图像解析等涉水视觉关键技术及装备方面的成果,先后研制了全海深超高清相机“海瞳”、全海深3D相机、全海深高清摄像机等,形成了从色彩、强度、偏振、光谱等全方位、体系化的水下观测解析装备研制能力,填补了我国全海深光学视觉技术的空白,推动了我国涉水视觉领域技术的升级,应用价值和社会效益显著.
其他语种文摘 Approximately 71% of the Earth's surface is encompassed by aqueous elements, such as rivers, lakes, and seas. Concurrently, terrestrial imaging contends with the influence of water in the forms of clouds, snow, rain, and fog. Notwithstanding, contemporary machine vision research and application systems predominantly concentrate on visual tasks within aerial and vacuum environments, leaving a dearth of systematic investigation into visual tasks within various aquatic contexts. Water-related vision, emblematic of water-based optical technology in the realm of vision, is committed to dissecting the scientific intricacies of light-water interactions and their inter-medium propagation. It also entails intelligent processing and analysis of visual image signals within aquatic settings. This discipline concurrently addresses engineering and technical intricacies intrinsic to the progression of advanced, intelligent water-related vision apparatus. Embarking from the fundamentally significant scientific query,“ What is the reason for the ocean's blue color?” this paper proffers an exhaustive survey encapsulating the repercussions of seawater's light absorption, scattering, and attenuation mechanisms upon underwater visual tasks. Furthermore, the current methodologies for the processing and refinement of subaquatic images are systematically examined. Exploiting the optical attributes of water and factors contributing to image degradation, this manuscript underscores our team's milestones in pioneering indispensable technologies for underwater imaging and image analysis. Substantial headway has been achieved in devising underwater observation and analytical apparatus, encompassing the full-ocean-depth ultra-high-definition camera“ Haitong,” the full-ocean-depth 3D camera, and the full-ocean-depth high-definition video camera. These innovations have distinctly established a comprehensive and methodical proficiency in optical detection within submerged contexts, encompassing variables of color, intensity, polarization, and spectral analysis. This collective endeavor effectively bridges the gap in China's full-ocean-depth optical detection technology, propelling the progress of exploration and technological innovation within the domain of water-related vision, which offers remarkable application value and societal advantages.
来源 电子学报 ,2024,52(4):1041-1082 【核心库】
DOI 10.12263/DZXB.20230698
关键词 涉水视觉 ; 涉水光学 ; 多模态认知计算 ; 机器视觉 ; 图像视频信号处理 ; 地外海洋
地址

1. 西北工业大学光电与智能研究院, 陕西, 西安, 710072  

2. 西北工业大学, 智能交互与应用工业和信息化部重点实验室, 陕西, 西安, 710072

语种 中文
文献类型 研究性论文
ISSN 0372-2112
学科 自动化技术、计算机技术
基金 国家重点研发计划 ;  国家自然科学基金
文献收藏号 CSCD:7745157

参考文献 共 183 共10页

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引证文献 1

1 陶洋 ULCF-Net:跨尺度结构与色彩融合的水下低照度图像增强算法 激光与光电子学进展,2025,62(2):0237011
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