Ren Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Ren Liu has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Chaofeng Ren
College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
1 shared publication - Jiyi Chen
Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of P.R. China Beijing China
1 shared publication - Junfeng Xie
Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, China
1 shared publication - Lirong Liu
Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of P. R. China, Beijing, China
1 shared publication - Xinming Tang
The Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China
1 shared publication
Latest Publications
- Open Access
Coarse-to-Fine Image Matching-Based Footprint Camera Calibration of the GF-7 Satellite
The GF-7 satellite is China’s first high-resolution stereo mapping satellite that reaches sub-meter resolution, equipped with new-type payloads, such as an area array footprint camera that can achieve synchronization acquisition of laser spots. When the satellite is in space, the variation of camera parameters may occur due to launch vibration and environmental changes, and on-orbit geometric calibration thereby must be made. Coupled with the data from the GF-7 satellite, this paper constructs a geometric imaging model of the area array footprint camera based on the two-dimensional direction angle, and proposes a coarse-to-fine “LPM-SIFT + Phase correlation” matching strategy for the automatic extraction of calibration control points. The single-image calibration experiment shows that the on-orbit geometric calibration model of the footprint camera constructed in this paper is correct and effective. The matching method proposed is used to register the footprint images with the DOM (Digital Orthophoto Map) reference data to obtain dense control points. Compared with the calibration result using a small number of manually collected control points, the root mean square error (RMSE) of the residual of the control points is improved from half a pixel to 1/3, and the RMSE of the same orbit checkpoints in the image space is improved from 1 pixel to 0.7. It can be concluded that using the coarse-to-fine image matching method proposed in this paper to extract control points can significantly improve the on-orbit calibration accuracy of the footprint camera on the GF-7 satellite.
Open AccessCoarse-to-Fine Image Matching-Based Footprint Camera Calibration of the GF-7 Satellite
The GF-7 satellite is China’s first high-resolution stereo mapping satellite that reaches sub-meter resolution, equipped with new-type payloads, such as an area array footprint camera that can achieve synchronization acquisition of laser spots. When the satellite is in space, the variation of camera parameters may occur due to launch vibration and environmental changes, and on-orbit geometric calibration thereby must be made. Coupled with the data from the GF-7 satellite, this paper constructs a geometric imaging model of the area array footprint camera based on the two-dimensional direction angle, and proposes a coarse-to-fine “LPM-SIFT + Phase correlation” matching strategy for the automatic extraction of calibration control points. The single-image calibration experiment shows that the on-orbit geometric calibration model of the footprint camera constructed in this paper is correct and effective. The matching method proposed is used to register the footprint images with the DOM (Digital Orthophoto Map) reference data to obtain dense control points. Compared with the calibration result using a small number of manually collected control points, the root mean square error (RMSE) of the residual of the control points is improved from half a pixel to 1/3, and the RMSE of the same orbit checkpoints in the image space is improved from 1 pixel to 0.7. It can be concluded that using the coarse-to-fine image matching method proposed in this paper to extract control points can significantly improve the on-orbit calibration accuracy of the footprint camera on the GF-7 satellite.