Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
| Aerial orthoimage generation for UAV remote sensing: Review | |
Zhang, Jiguang1 ; Xu, Shilin1,3; Zhao, Yong4; Sun, Jiaxi1,3; Xu, Shibiao2; Zhang, Xiaopeng1
| |
| Source Publication | INFORMATION FUSION
 |
| ISSN | 1566-2535 |
| 2023 | |
| Volume | 89Pages:91-120 |
| Corresponding Author | Xu, Shibiao(shibiaoxu@bupt.edu.cn) |
| Abstract | 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. |
| Keyword | Orthoimage generation UAV SfM SLAM 2D mosaic Ortho-rectification |
| DOI | 10.1016/j.inffus.2022.08.007 |
| WOS Keyword | IMAGES ; SLAM ; VERSATILE ; MODELS ; ROBUST ; SFM |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 |
| Funding Organization | 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 |
| WOS Research Area | Computer Science |
| WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods |
| WOS ID | WOS:000868900700007 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://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 Author | Xu, Shibiao |
| Affiliation | 1.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 Affilication | Chinese 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. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment