Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation
When the in-orbit geometric calibration of optical satellite cameras is not performed in a precise or timely manner, optical remote sensing satellite images (ORSSIs) are produced with inaccurate camera parameters. The internal orientation (IO) biases of ORSSIs caused by inaccurate camera parameters...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/3/471 |
| _version_ | 1797485173846048768 |
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| author | Jinshan Cao Nan Zhou Haixing Shang Zhiwei Ye Zhiqi Zhang |
| author_facet | Jinshan Cao Nan Zhou Haixing Shang Zhiwei Ye Zhiqi Zhang |
| author_sort | Jinshan Cao |
| collection | DOAJ |
| description | When the in-orbit geometric calibration of optical satellite cameras is not performed in a precise or timely manner, optical remote sensing satellite images (ORSSIs) are produced with inaccurate camera parameters. The internal orientation (IO) biases of ORSSIs caused by inaccurate camera parameters show a discontinuous distorted characteristic and cannot be compensated by a simple orientation model. The internal geometric quality of ORSSIs will, therefore, be worse than expected. In this study, from the ORSSI users’ perspective, a feasible internal geometric quality improvement method is presented for ORSSIs with image reorientation. In the presented method, a sensor orientation model, an external orientation (EO) model, and an IO model are successively established. Then, the EO and IO model parameters are estimated with ground control points. Finally, the original image is reoriented with the estimated IO model parameters. Ten HaiYang-1C coastal zone imager (CZI) images, a ZiYuan-3 02 nadir image, a GaoFen-1B panchromatic image, and a GaoFen-1D panchromatic image, were tested. The experimental results showed that the IO biases of ORSSIs caused by inaccurate camera parameters could be effectively eliminated with the presented method. The IO accuracies of all the tested images were improved to better than 1.0 pixel. |
| first_indexed | 2024-03-09T23:15:00Z |
| format | Article |
| id | doaj.art-baabed22ac7f4271845b2493701864d9 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T23:15:00Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-baabed22ac7f4271845b2493701864d92023-11-23T17:38:13ZengMDPI AGRemote Sensing2072-42922022-01-0114347110.3390/rs14030471Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image ReorientationJinshan Cao0Nan Zhou1Haixing Shang2Zhiwei Ye3Zhiqi Zhang4School of Computer Science, Hubei University of Technology, Wuhan 430068, ChinaBeijing Institute of Space Mechanics & Electricity, Beijing 100076, ChinaNorthwest Engineering Corporation Limited, Power China Group, Xi’an 710064, ChinaSchool of Computer Science, Hubei University of Technology, Wuhan 430068, ChinaSchool of Computer Science, Hubei University of Technology, Wuhan 430068, ChinaWhen the in-orbit geometric calibration of optical satellite cameras is not performed in a precise or timely manner, optical remote sensing satellite images (ORSSIs) are produced with inaccurate camera parameters. The internal orientation (IO) biases of ORSSIs caused by inaccurate camera parameters show a discontinuous distorted characteristic and cannot be compensated by a simple orientation model. The internal geometric quality of ORSSIs will, therefore, be worse than expected. In this study, from the ORSSI users’ perspective, a feasible internal geometric quality improvement method is presented for ORSSIs with image reorientation. In the presented method, a sensor orientation model, an external orientation (EO) model, and an IO model are successively established. Then, the EO and IO model parameters are estimated with ground control points. Finally, the original image is reoriented with the estimated IO model parameters. Ten HaiYang-1C coastal zone imager (CZI) images, a ZiYuan-3 02 nadir image, a GaoFen-1B panchromatic image, and a GaoFen-1D panchromatic image, were tested. The experimental results showed that the IO biases of ORSSIs caused by inaccurate camera parameters could be effectively eliminated with the presented method. The IO accuracies of all the tested images were improved to better than 1.0 pixel.https://www.mdpi.com/2072-4292/14/3/471geometric qualityinternal orientationsensor orientationoptical satellite imagesimage reorientation |
| spellingShingle | Jinshan Cao Nan Zhou Haixing Shang Zhiwei Ye Zhiqi Zhang Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation Remote Sensing geometric quality internal orientation sensor orientation optical satellite images image reorientation |
| title | Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation |
| title_full | Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation |
| title_fullStr | Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation |
| title_full_unstemmed | Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation |
| title_short | Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation |
| title_sort | internal geometric quality improvement of optical remote sensing satellite images with image reorientation |
| topic | geometric quality internal orientation sensor orientation optical satellite images image reorientation |
| url | https://www.mdpi.com/2072-4292/14/3/471 |
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