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Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap

文献类型：期刊论文

作者Zhao, Yong5; Cheng, Yuqi5; Zhang, Xishan1; Xu, Shibiao2; Bu, Shuhui5; Jiang, Hongkai5; Han, Pengcheng5; Li, Ke3; Wan, Gang4
刊名REMOTE SENSING
出版日期2020-11-01
卷号12期号:22页码:15
关键词aerial images DOM low overlap mosaicing georeferenced orthophoto
DOI10.3390/rs12223739
通讯作者Xu, Shibiao(shibiao.xu@nlpr.ia.ac.cn)
英文摘要Orthophoto generation is a popular topic in aerial photogrammetry and 3D reconstruction. It is generally computationally expensive with large memory consumption. Inspired by the simultaneous localization and mapping (SLAM) workflow, this paper presents an online sequential orthophoto mosaicing solution for large baseline high-resolution aerial images with high efficiency and novel precision. An appearance and spatial correlation-constrained fast low-overlap neighbor candidate query and matching strategy is used for efficient and robust global matching. Instead of estimating 3D positions of sparse mappoints, which is outlier sensitive, we propose to describe the ground reconstruction with multiple stitching planes, where parameters are reduced for fast nonconvex graph optimization. GPS information is also fused along with six degrees of freedom (6-DOF) pose estimation, which not only provides georeferenced coordinates, but also converges property and robustness. An incremental orthophoto is generated by fusing the latest images with adaptive weighted multiband algorithm, and all results are tiled with level of detail (LoD) support for efficient rendering and further disk cache for reducing memory usages. Public datasets are evaluated by comparing state-of-the-art software. Results show that our system outputs orthophoto with novel efficiency, quality, and robustness in real-time. An android commercial application is developed for online stitching with DJIdrones, considering the excellent performance of our algorithm.
资助项目National Key R&D Program of China[2018YFB2100602] ; National Natural Science Foundation of China[61620106003] ; National Natural Science Foundation of China[91646207] ; National Natural Science Foundation of China[61971418] ; National Natural Science Foundation of China[61671451] ; National Natural Science Foundation of China[61573284]
WOS研究方向Remote Sensing
语种英语
出版者MDPI
WOS记录号WOS:000594558800001
资助机构National Key R&D Program of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/41653]  
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.Inst Mech Technol, Xian 710043, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Zhengzhou Inst Surveying & Mapping, Zhengzhou 450052, Peoples R China
4.Aerosp Engn Univ, Inst Aeronaut, Beijing 101416, Peoples R China
5.Northwestern Polytech Univ, Inst Aeronaut, Xian 710072, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Yong,Cheng, Yuqi,Zhang, Xishan,et al. Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap[J]. REMOTE SENSING,2020,12(22):15.
APA Zhao, Yong.,Cheng, Yuqi.,Zhang, Xishan.,Xu, Shibiao.,Bu, Shuhui.,...&Wan, Gang.(2020).Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap.REMOTE SENSING,12(22),15.
MLA Zhao, Yong,et al."Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap".REMOTE SENSING 12.22(2020):15.

入库方式： OAI收割

来源：自动化研究所

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