Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations
Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for...
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MDPI AG
2018-06-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/6/1770 |
| _version_ | 1828137975707336704 |
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| author | Rongyong Huang Shunyi Zheng Kun Hu |
| author_facet | Rongyong Huang Shunyi Zheng Kun Hu |
| author_sort | Rongyong Huang |
| collection | DOAJ |
| description | Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4–1/2 (0.17–0.27 m) and 1/8–1/4 (0.10–0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data. |
| first_indexed | 2024-04-11T18:28:34Z |
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| id | doaj.art-46fb3ea5f4fa4d9c9b52566a3722d990 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:28:34Z |
| publishDate | 2018-06-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-46fb3ea5f4fa4d9c9b52566a3722d9902022-12-22T04:09:32ZengMDPI AGSensors1424-82202018-06-01186177010.3390/s18061770s18061770Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity EquationsRongyong Huang0Shunyi Zheng1Kun Hu2Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Guangxi University, Nanning 530004, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaInstitute of Electronics, Chinese Academy of Sciences, Beijing 100190, ChinaRegistration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4–1/2 (0.17–0.27 m) and 1/8–1/4 (0.10–0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.http://www.mdpi.com/1424-8220/18/6/1770registrationaerial ImageLiDARpoint cloudcollinearity equation |
| spellingShingle | Rongyong Huang Shunyi Zheng Kun Hu Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations Sensors registration aerial Image LiDAR point cloud collinearity equation |
| title | Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations |
| title_full | Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations |
| title_fullStr | Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations |
| title_full_unstemmed | Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations |
| title_short | Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations |
| title_sort | registration of aerial optical images with lidar data using the closest point principle and collinearity equations |
| topic | registration aerial Image LiDAR point cloud collinearity equation |
| url | http://www.mdpi.com/1424-8220/18/6/1770 |
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