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1.中国科学院 长春光学精密机械与物理研究所 航空光学成像与测量重点实验室, 吉林 长春 130033
2.中国电力工程顾问集团 东北电力设计院有限公司,吉林 长春 130021
[ "徐 芳(1987-),女,山东日照人,助理研究员,2018年于中国科学院大学获得博士学位,主要从事航空航天成像处理、目标检测与识别等方面的研究。E-mail: xufang59@126.com" ]
收稿日期:2020-08-25,
修回日期:2020-10-17,
纸质出版日期:2021-04-15
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徐芳,刘晶红,孙辉等.光学遥感图像海面船舶目标检测技术进展[J].光学精密工程,2021,29(04):916-931.
XU Fang,LIU Jing-hong,SUN Hui,et al.Research progress on vessel detection using optical remote sensing image[J].Optics and Precision Engineering,2021,29(04):916-931.
徐芳,刘晶红,孙辉等.光学遥感图像海面船舶目标检测技术进展[J].光学精密工程,2021,29(04):916-931. DOI: 10.37188/OPE.2020.0419.
XU Fang,LIU Jing-hong,SUN Hui,et al.Research progress on vessel detection using optical remote sensing image[J].Optics and Precision Engineering,2021,29(04):916-931. DOI: 10.37188/OPE.2020.0419.
海面船舶目标检测一直是遥感图像处理、模式识别与计算机视觉等领域的研究热点,船舶作为海上运输载体和重要军事目标,对其进行自动检测在军用与民用领域有着广阔的应用前景和重要现实意义。本文梳理了用于海面船舶目标检测的光学成像卫星的发展情况,分析了光学遥感成像船舶目标的物理特性和特征,归纳了国内外该领域海面船舶检测技术研究现状,围绕构建相关目标检测模型和架构的相关理论与关键技术进行了分析、比较和总结,探讨了当前光学遥感图像船舶目标检测方法面临的问题与挑战以及未来的发展趋势。
Vessel detection has always been a popular research topic in fields such as remote sensing image processing, pattern recognition, and computer vision. As vessels are maritime transport carriers and important military objects, vessel detection plays an important role in a spectrum of related military and civil fields. It has broad application prospects and high practical significance. This paper provides an overview of the existing literature on vessel detection using optical satellite imagery. The development of optical satellites for vessel detection on the sea surface is reviewed. The physical characteristics of vessels in optical remote sensing imaging are analyzed. The global research status of vessel detection technology using optical remote sensing imaging is summarized. The related theories and key technologies pertaining to the target detection model and architecture are analyzed and compared in detail. The problems and challenges of vessel detection methods using optical remote sensing images are discussed. Aiming at the urgent demand for good performance and robustness of the algorithm in practical applications, some crucial problems that need to be solved are proposed. The development trend of future research on vessel detection using optical remote sensing images is discussed.
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