校准
计算机科学
直线(几何图形)
遥感
计算机视觉
人工智能
作者
Guoqin Yuan,Zheng Lina,Ding Yalin,Zhang Hongwen,Xuefei Zhang,Liu Xueji,Sun Jianjun
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2021-07-27
卷期号:70: 1-9
被引量:2
标识
DOI:10.1109/tim.2021.3090157
摘要
With the advantages of ultrahigh resolution and acquisition rate, line scan cameras are increasingly being deployed for precision measurement. In order to achieve high precision, the intrinsic parameters must be calibrated properly. However, the existing calibration models that only calibrate the principle points and the distortion in 1-D direction and ignore the other directions result in limited adaptability and accuracy, which are especially serious for multiline cameras. To conquer this challenge, this article proposes a precise calibration method that is qualified for both multiline cameras and single-line cameras. Through the analysis of the relative position relationship between the pixel array and principle point, a method for calibrating the principle points and the distortion in 2-D direction is proposed and a flexible calibration device is designed based on a theodolite. The calibration quality is improved by the novel calibration method that effectively establishes the correspondence relationship between the rays and pixels by recording the incident angle of the collimated beam and its image, respectively. Moreover, a robust optimization algorithm is proposed to enhance the stability of parameter estimation. The proposed method is verified by Monte-Carlo simulation, real experimental data, and flight. The results show that the 2-D calibration model can improve the calibration accuracy of the multiline cameras by 45 pixels at most, and its reprojection measurement uncertainty is as low as 0.1 pixels. The comparative results of the experiments demonstrate that the proposed method has the advantages of high accuracy, low cost, and easy implementation.
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