Abstract Camera calibration is a vital and important work for machine vision. In the paper, an optimized calibration method for ultra-field dual bands cameras is proposed, which is based on the designed thermal radiation checkerboard. The optimizations are achieved in subpixel location, center location and mapping relationship, respectively. Specifically, the subpixel corner is located by performing the designed variable quadrilateral template on edge gradients and calculating their minimum orthogonal value. Then, the center location is accomplished through Gaussian fitting, in which the bottom point is taken as the potential center in iterations. Moreover, the RBF network is employed to replace the polynomial fitting and fit the mapping relationship between the camera coordinates and sensor coordinates. Thus, the accuracy of the mapping is increased, which contributes to the optimization of the intrinsic and extrinsic parameters. The experiments results show that the average root mean square error of the reprojection is reduced by nearly 50%. The calibrated parameters are accurate and have physical significance in the proposed calibration scheme.

中文翻译：

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基于热辐射棋盘格的超视场双波段相机标定优化方法

摘要 相机标定是机器视觉的一项重要而重要的工作。本文基于所设计的热辐射棋盘格，提出了一种优化的超场双波段相机标定方法。优化分别在亚像素位置、中心位置和映射关系上实现。具体来说，通过在边缘梯度上执行设计的可变四边形模板并计算它们的最小正交值来定位子像素角。然后，通过高斯拟合完成中心位置，其中以底部点为迭代中的潜在中心。此外，采用RBF网络代替多项式拟合，拟合相机坐标和传感器坐标之间的映射关系。因此，提高了映射的准确性，这有助于优化内在和外在参数。实验结果表明，重投影的平均均方根误差降低了近50%。标定的参数是准确的，并且在提出的标定方案中具有物理意义。