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多模态遥感图像匹配方法综述EI北大核心CSCD
引用本文:眭海刚,刘畅,干哲,江政杰,徐川.多模态遥感图像匹配方法综述EI北大核心CSCD[J].测绘学报,2022,51(9):1848-1861.
作者姓名:眭海刚  刘畅  干哲  江政杰  徐川
作者单位:1. 武汉大学测绘遥感信息工程国家重点实验室, 湖北 武汉 430079;2. 93114 部队, 北京 100089;3. 北京理工大学信息与电子学院, 北京 100081;4. 湖北工业大学计算机学院, 湖北 武汉 430068
基金项目:广西科技重大专项(AA22068072);国家自然科学基金(41771457;41601443)
摘    要:遥感图像匹配是遥感图像处理的关键基础,一直是国内外学者研究的热点。由于多模态图像具有辐射差异、几何差异、尺度差异、视角差异、维度差异等特性,目前尚未出现一种普适性强的通用匹配方法。随着遥感、人工智能、大数据等技术的不断发展和应用领域的持续拓展,图像匹配技术体系也在不断地发展和演化。本文在系统梳理图像匹配技术发展历程的基础上,对多模态遥感图像匹配分类体系进行了归纳总结,从特征驱动和数据驱动两方面论述了多模态图像匹配技术研究的最新进展,并指出其面临的核心困难及未来发展趋势,以期推动多模态图像匹配研究更加深入发展。

关 键 词:图像匹配  多模态  特征描述  深度学习
收稿时间:2022-02-24
修稿时间:2022-07-24

Overview of multi-modal remote sensing image matching methods
SUI Haigang,LIU Chang,GAN Zhe,JIANG Zhengjie,XU Chuan.Overview of multi-modal remote sensing image matching methods[J].Acta Geodaetica et Cartographica Sinica,2022,51(9):1848-1861.
Authors:SUI Haigang  LIU Chang  GAN Zhe  JIANG Zhengjie  XU Chuan
Institution:1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;2. Troops 93114, Beijing 100089, China;3. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China;4. School of Computer Science, Hubei University of Technology, Wuhan 430068, China
Abstract:Remote sensing image matching is the key foundation of remote sensing image processing, which has been a research hotspot for scholars at home and abroad. Due to the characteristics of multi-modal images such as radiation difference, geometric difference, scale difference, viewpoint difference and dimensional difference, a universal matching method with strong universality has not yet appeared. With the continuous development of remote sensing, artificial intelligence, big data, and other technologies and the continuous expansion of application fields, the image matching technology system is also developing and evolving. This paper summarizes the multi-modal remote sensing image matching classification system based on the development history of image matching technology, discusses the latest progress of multi-modal image matching technology from the perspective of feature-driven and data-driven, and points out the core difficulties and future development trend in order to promote the deeper development of multi-modal image matching research.
Keywords:
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