Common-feature-track-matching approach for multi-epoch UAV photogrammetry co-registration
文献类型：期刊论文
| 作者 | Li, Xinlong2,3; Ding, Mingtao2,3,4; Li, Zhenhong2,3,4; Cui, Peng1,5 |
| 刊名 | ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
 |
| 出版日期 | 2024-12-01 |
| 卷号 | 218页码:392-407 |
| 关键词 | Feature matching Multi-epoch UAV photogrammetry Pose estimation Co-registration |
| ISSN号 | 0924-2716 |
| DOI | 10.1016/j.isprsjprs.2024.10.025 |
| 产权排序 | 4 |
| 英文摘要 | Automatic co-registration of multi-epoch Unmanned Aerial Vehicle (UAV) image sets remains challenging due to the radiometric differences in complex dynamic scenes. Specifically, illumination changes and vegetation variations usually lead to insufficient and spatially unevenly distributed common tie points (CTPs), resulting in under-fitting of co-registration near the areas without CTPs. In this paper, we propose a novel Common-Feature- Track-Matching (CFTM) approach for UAV image sets co-registration, to alleviate the shortage of CTPs in complex dynamic scenes. Instead of matching features between multi-epoch images, we first search correspondences between multi-epoch feature tracks (i.e., groups of features corresponding to the same 3D points), which avoids the removal of matches due to unreliable estimation of the relative pose between inter-epoch image pairs. Then, the CTPs are triangulated from the successfully matched track pairs. Since an even distribution of CTPs is crucial for robust co-registration, a block-based strategy is designed, as well as enabling parallel computation. Finally, an iterative optimization algorithm is developed to gradually select the best CTPs to refine the poses of multi-epoch images. We assess the performance of our method on two challenging datasets. The results show that CFTM can automatically acquire adequate and evenly distributed CTPs in complex dynamic scenes, achieving a high co-registration accuracy approximately four times higher than the state-of-the-art in challenging scenario. Our code is available at https://github.com/lixinlong1998/CoSfM. |
| WOS关键词 | STRUCTURE-FROM-MOTION ; IMAGES ; SFM ; COMMUNICATION |
| 资助项目 | National Natural Science Foundation of China[41941019] ; National Natural Science Foundation of China[42374027] ; National Key Research and Development Program of China[2021YFC3000400] ; Application and Demonstration of Comprehensive Governance and Scale Industrialization in the Sichuan-Tibet Region under the High-resolution Satellite Project ; Shaanxi Province Science and Technology Innovation Team[2021TD-51] ; Shaanxi Province Geoscience Big Data and Geohazard Prevention Innovation Team ; Fundamental Research Funds for the Central Universities[300102262203] ; Fundamental Research Funds for the Central Universities[300102262902] ; Opening Fund of Key Laboratory of Smart Earth[KF2023YB04-01] |
| WOS研究方向 | Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001358309700001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program of China ; Application and Demonstration of Comprehensive Governance and Scale Industrialization in the Sichuan-Tibet Region under the High-resolution Satellite Project ; Shaanxi Province Science and Technology Innovation Team ; Shaanxi Province Geoscience Big Data and Geohazard Prevention Innovation Team ; Fundamental Research Funds for the Central Universities ; Opening Fund of Key Laboratory of Smart Earth |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/210704]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Ding, Mingtao; Li, Zhenhong |
| 作者单位 | 1.Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Earth Surface Proc, Chengdu 610041, Peoples R China 2.Changan Univ, Coll Geol Engn & Geomat, Xian 710054, Peoples R China 3.Changan Univ, Big Data Ctr Geosci & Satellites, Xian 710054, Peoples R China 4.Minist Educ, Key Lab Western Chinas Mineral Resource & Geol Eng, Xian 710054, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Xinlong,Ding, Mingtao,Li, Zhenhong,et al. Common-feature-track-matching approach for multi-epoch UAV photogrammetry co-registration[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2024,218:392-407. |
| APA | Li, Xinlong,Ding, Mingtao,Li, Zhenhong,&Cui, Peng.(2024).Common-feature-track-matching approach for multi-epoch UAV photogrammetry co-registration.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,218,392-407. |
| MLA | Li, Xinlong,et al."Common-feature-track-matching approach for multi-epoch UAV photogrammetry co-registration".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 218(2024):392-407. |
入库方式： OAI收割
来源：地理科学与资源研究所
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