Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap
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 solut...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/22/3739 |
| _version_ | 1797547921033396224 |
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| author | Yong Zhao Yuqi Cheng Xishan Zhang Shibiao Xu Shuhui Bu Hongkai Jiang Pengcheng Han Ke Li Gang Wan |
| author_facet | Yong Zhao Yuqi Cheng Xishan Zhang Shibiao Xu Shuhui Bu Hongkai Jiang Pengcheng Han Ke Li Gang Wan |
| author_sort | Yong Zhao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T14:51:58Z |
| format | Article |
| id | doaj.art-9223693a0026419d9e7e1e2972bac5e9 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T14:51:58Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-9223693a0026419d9e7e1e2972bac5e92023-11-20T20:54:47ZengMDPI AGRemote Sensing2072-42922020-11-011222373910.3390/rs12223739Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low OverlapYong Zhao0Yuqi Cheng1Xishan Zhang2Shibiao Xu3Shuhui Bu4Hongkai Jiang5Pengcheng Han6Ke Li7Gang Wan8Institute of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaInstitute of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaInstitute of Mechanical Technology, Xi’an 710043, ChinaInstitute of Automation, Chinese Academy of Sciences, Beijing 100190, ChinaInstitute of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaInstitute of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaInstitute of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaZhengzhou Institute of Surveying and Mapping, Zhengzhou 450052, ChinaInstitute of Aeronautics, Aerospace Engineering University, Beijing 101416, ChinaOrthophoto 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.https://www.mdpi.com/2072-4292/12/22/3739aerial imagesDOMlow overlapmosaicinggeoreferencedorthophoto |
| spellingShingle | Yong Zhao Yuqi Cheng Xishan Zhang Shibiao Xu Shuhui Bu Hongkai Jiang Pengcheng Han Ke Li Gang Wan Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap Remote Sensing aerial images DOM low overlap mosaicing georeferenced orthophoto |
| title | Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap |
| title_full | Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap |
| title_fullStr | Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap |
| title_full_unstemmed | Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap |
| title_short | Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap |
| title_sort | real time orthophoto mosaicing on mobile devices for sequential aerial images with low overlap |
| topic | aerial images DOM low overlap mosaicing georeferenced orthophoto |
| url | https://www.mdpi.com/2072-4292/12/22/3739 |
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