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Aerial orthoimage generation for UAV remote sensing: Review

文献类型：期刊论文

作者Zhang, Jiguang3; Xu, Shilin3,4; Zhao, Yong2; Sun, Jiaxi3,4; Xu, Shibiao1; Zhang, Xiaopeng3
刊名INFORMATION FUSION
出版日期2023
卷号89页码:91-120
关键词Orthoimage generation UAV SfM SLAM 2D mosaic Ortho-rectification
ISSN号1566-2535
DOI10.1016/j.inffus.2022.08.007
通讯作者Xu, Shibiao(shibiaoxu@bupt.edu.cn)
英文摘要With its unique advantages of high flexibility and high efficiency, UAV has become a reasonable substitute for conventional aerial measurement technology. Especially in the low altitude remote sensing image processing, the ortho-rectification and mosaic of aerial images are the key to vision-based UAV orthoimage generation. Therefore, how to select the appropriate methods to rectify and mosaic the aerial images of UAV is significance to research the automatic generation of digital orthoimages. Unfortunately, most of the existing reviews only focus on the general image mosaic techniques, and there are few special reports on the application of UAV orthoimage generation for reference. This paper presents a comprehensive survey on UAV orthoimage generation technologies. We conclude three mainstream frameworks of visual orthoimage generation, which are 2D mosaic framework based, SfM framework based and SLAM framework based methods. According to the above three specific frameworks, we first carried out a detailed description and comparative analysis of related important algorithms, and sorted out the differences, common points and inherent relationships. Considering the wide application of deep learning in UAV remote sensing, we propose some hypotheses on how to introduce deep learning technology into above three orthoimage generation frameworks. After analysis, we provide a more detailed performance quantification comparison of the two most recent potential frameworks (State-of-the-art methods based on SfM and SLAM). It is worth noting that we integrated different test data sources of UVA aerial video sequence with a general SLAM testing platform, and solve the issue that SLAM-based orthoimage generation methods are difficult to evaluate cross-platform. Finally, challenges about visual UAV orthoimage generation and future directions in addressing these challenges are also pointed out.
WOS关键词IMAGES ; SLAM ; VERSATILE ; MODELS ; ROBUST ; SFM
资助项目National Natural Science Foundation of China[U21A20515] ; National Natural Science Foundation of China[61972459] ; National Natural Science Foundation of China[61971418] ; National Natural Science Foundation of China[U2003109] ; National Natural Science Foundation of China[62171321] ; National Natural Science Foundation of China[62071157] ; National Natural Science Foundation of China[62162044] ; Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences[LSU-KFJJ-2021-05] ; Open Research Projects of Zhejiang Lab[2021KE0AB07] ; Open Projects Program of National Laboratory of Pattern Recognition
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000868900700007
出版者ELSEVIER
资助机构National Natural Science Foundation of China ; Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences ; Open Research Projects of Zhejiang Lab ; Open Projects Program of National Laboratory of Pattern Recognition
源URL[http://ir.ia.ac.cn/handle/173211/50269]  
专题模式识别国家重点实验室_三维可视计算
通讯作者Xu, Shibiao
作者单位1.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing, Peoples R China
2.Northwestern Polytech Univ, Xian, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Jiguang,Xu, Shilin,Zhao, Yong,et al. Aerial orthoimage generation for UAV remote sensing: Review[J]. INFORMATION FUSION,2023,89:91-120.
APA Zhang, Jiguang,Xu, Shilin,Zhao, Yong,Sun, Jiaxi,Xu, Shibiao,&Zhang, Xiaopeng.(2023).Aerial orthoimage generation for UAV remote sensing: Review.INFORMATION FUSION,89,91-120.
MLA Zhang, Jiguang,et al."Aerial orthoimage generation for UAV remote sensing: Review".INFORMATION FUSION 89(2023):91-120.

入库方式： OAI收割

来源：自动化研究所

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