CASIA OpenIR  > 模式识别国家重点实验室  > 三维可视计算
Aerial orthoimage generation for UAV remote sensing: Review
Zhang, Jiguang1; Xu, Shilin1,3; Zhao, Yong4; Sun, Jiaxi1,3; Xu, Shibiao2; Zhang, Xiaopeng1
Source PublicationINFORMATION FUSION
ISSN1566-2535
2023
Volume89Pages:91-120
Corresponding AuthorXu, Shibiao(shibiaoxu@bupt.edu.cn)
AbstractWith 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.
KeywordOrthoimage generation UAV SfM SLAM 2D mosaic Ortho-rectification
DOI10.1016/j.inffus.2022.08.007
WOS KeywordIMAGES ; SLAM ; VERSATILE ; MODELS ; ROBUST ; SFM
Indexed BySCI
Language英语
Funding ProjectNational 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
Funding OrganizationNational 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
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000868900700007
PublisherELSEVIER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50270
Collection模式识别国家重点实验室_三维可视计算
Corresponding AuthorXu, Shibiao
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
2.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
4.Northwestern Polytech Univ, Xian, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
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.
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