On-orbit calibration of space camera lens distortion using a single image

• Published in: Optics and lasers in engineering Vol. 177; p. 108140
• Main Authors: Zhang, Gaopeng, Wang, Feng, Zhang, Guangdong, Zhang, Zhe, Du, Hubing, Zhao, Zixin, Wang, Changqing, Cao, Jianzhong, Zhao, Jingwei, Li, Yanjie, Lu, Rong
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-06-2024
• Subjects: Camera calibration; Lens distortion; Machine vision; Space camera; Vanishing points; Camera calibration; Machine vision; Space camera; 150.0155; Lens distortion; Vanishing points; 150.1488
• ISSN: 0143-8166; 1873-0302
• DOI: 10.1016/j.optlaseng.2024.108140

•We present an on-orbit calibration of space camera lens distortion with the vanishing points obtained from a single image of the solar panel.•We propose a parallel-line-extraction method based on collinear constraints to obtain the parallel lines, and train the optimal vanishing point using the common point constraint method. Using the optimal vanishing point, we establish the optimization function of lens distortion based on vanishing point consistency.•We establish the optimization function of lens distortion based on vanishing point consistency and propose an improved genetic algorithm (IGA) to solve the optimization function.•Simulation and real physical experiments demonstrate that the proposed method is flexible and accurate with good anti-noise interference capacity. The method proposed in this paper makes more realistic sense for a number of important space tasks.
Since space cameras need to withstand the harsh mechanical and thermal conditions in the space environment for a long time, it is necessary to calibrate them in orbit. However, existing calibration methods have various disadvantages, making them impossible to use in orbit. To address this problem, we present an on-orbit calibration of space camera lens distortion with the vanishing points obtained from a single image of the solar panel. First, we propose a parallel-line-extraction method based on collinear constraints to obtain the parallel lines. Then, we train the optimal vanishing point using the common point constraint method. Using the optimal vanishing point, we establish the optimization function of lens distortion based on vanishing point consistency. Finally, we present an improved genetic algorithm to solve the optimization function. Simulations and experiments show that the proposed method is flexible and robust.