Fast Georeferenced Aerial Image Stitching With Absolute Rotation Averaging and Planar- Restricted Pose Graph
Zhao, Yong4; Liu, Guochen4; Xu, Shibiao1,2; Bu, Shuhui4; Jiang, Hongkai4; Wan, Gang3
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2021-04-01
卷号59期号:4页码:3502-3517
关键词Simultaneous localization and mapping Image reconstruction Optimization Real-time systems Global Positioning System Robustness Image fusion Aerial images digital orthophoto map (DOM) georeferenced low overlap mosaicing planar
ISSN号0196-2892
DOI10.1109/TGRS.2020.3008517
通讯作者Xu, Shibiao(shibiao.xu@nlpr.ia.ac.cn) ; Bu, Shuhui(bushuhui@nwpu.edu.cn)
英文摘要Accurate digital orthophoto map generation from high-resolution aerial images is important in various applications. Compared with the existing commercial software and the current state-of-the-art mosaicing systems, a novel fast georeferenced orthophoto mosaicing framework is proposed in this study. The framework can adapt to the challenging requirements of high-accuracy orthoimage generations with relatively fast speed, even if the overlap rate is low. We provide appearance and spatial correlation-constrained fast low-overlap neighbor candidate query and matching. On the basis of GPS information, we introduce an absolute position and rotation-averaging strategy for global pose initialization, which is essential for the high convergence and efficiency of nonconvex pose optimization of every image. We also propose a planar-restricted global pose graph optimization method. The optimization is extremely efficient and robust considering that point clouds are parameterized to planes. Finally, we apply a matching graph-based exposure compensation and region reduction algorithm for large-scale and high-resolution image fusion with high efficiency and novel precision. Experimental results demonstrate that our method can achieve the state-of-the-art performance while maintaining high precision and robustness.
资助项目National Key Research and Development Program of China[2018YFB2100601] ; National Natural Science Foundation of China[91860124] ; National Natural Science Foundation of China[91646207] ; National Natural Science Foundation of China[51875459] ; National Natural Science Foundation of China[61620106003] ; National Natural Science Foundation of China[61971418] ; National Natural Science Foundation of China[61771026] ; National Natural Science Foundation of China[61671451] ; National Natural Science Foundation of China[61573284] ; Aeronautical Science Foundation of China[20170253003]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000633493700054
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Aeronautical Science Foundation of China
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/44518]  
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; Bu, Shuhui
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China
3.Aerosp Engn Univ, Sch Aerosp Informat, Beijing 101416, Peoples R China
4.Northwestern Polytech Univ, Coll Aeronaut, Xian 710072, Peoples R China
推荐引用方式
GB/T 7714
Zhao, Yong,Liu, Guochen,Xu, Shibiao,et al. Fast Georeferenced Aerial Image Stitching With Absolute Rotation Averaging and Planar- Restricted Pose Graph[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2021,59(4):3502-3517.
APA Zhao, Yong,Liu, Guochen,Xu, Shibiao,Bu, Shuhui,Jiang, Hongkai,&Wan, Gang.(2021).Fast Georeferenced Aerial Image Stitching With Absolute Rotation Averaging and Planar- Restricted Pose Graph.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,59(4),3502-3517.
MLA Zhao, Yong,et al."Fast Georeferenced Aerial Image Stitching With Absolute Rotation Averaging and Planar- Restricted Pose Graph".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 59.4(2021):3502-3517.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace