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Article

Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation

1
School of Computer Science, Hubei University of Technology, Wuhan 430068, China
2
Beijing Institute of Space Mechanics & Electricity, Beijing 100076, China
3
Northwest Engineering Corporation Limited, Power China Group, Xi’an 710064, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2022, 14(3), 471; https://doi.org/10.3390/rs14030471
Submission received: 9 December 2021 / Revised: 13 January 2022 / Accepted: 17 January 2022 / Published: 19 January 2022

Abstract

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.
Keywords: geometric quality; internal orientation; sensor orientation; optical satellite images; image reorientation geometric quality; internal orientation; sensor orientation; optical satellite images; image reorientation
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MDPI and ACS Style

Cao, J.; Zhou, N.; Shang, H.; Ye, Z.; Zhang, Z. Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation. Remote Sens. 2022, 14, 471. https://doi.org/10.3390/rs14030471

AMA Style

Cao J, Zhou N, Shang H, Ye Z, Zhang Z. Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation. Remote Sensing. 2022; 14(3):471. https://doi.org/10.3390/rs14030471

Chicago/Turabian Style

Cao, Jinshan, Nan Zhou, Haixing Shang, Zhiwei Ye, and Zhiqi Zhang. 2022. "Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation" Remote Sensing 14, no. 3: 471. https://doi.org/10.3390/rs14030471

APA Style

Cao, J., Zhou, N., Shang, H., Ye, Z., & Zhang, Z. (2022). Internal Geometric Quality Improvement of Optical Remote Sensing Satellite Images with Image Reorientation. Remote Sensing, 14(3), 471. https://doi.org/10.3390/rs14030471

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