数码相机的非线性光学畸变补偿，主要有用于摄影测量领域的像方畸变模型和用于计算机视觉领域的物方畸变模型两种方式。针对两种畸变模型难以通用的问题，提出了一种像方和物方的畸变模型相互转换方法。利用已知畸变模型系数及内方位元素生成原始像点与理论像点的对应关系，构成虚拟观测值。再利用虚拟观测值对内方位元素及待转换畸变模型系数进行整体最小二乘平差解算。最后，利用三维控制场检校结果对转换结果进行精度评价。实验结果表明，当相机检校总体中误差小于0.3 pixel时，两种畸变模型转换前后像点畸变量差值小于0.5 pixel，可以满足对子像素转换精度的要求。

There are two kinds of nonlinear optical distortion compensation methods for digital cameras. One is the image distortion model used in the photogrammetry, and the other is the object distortion model used in the computer vision. Aiming at the problem that the two kinds of distortion models are difficult to achieve generality, we propose a method for transformation of image distortion and objects distortion. First, the transfer relationship between the original image point and the theoretical image point, generated from the known distortion model coefficients and the intrinsic parameters, is used as the virtual measurements. Then, the intrinsic parameters and distortion model coefficients are computed according to the virtual measurements by the least square method. Finally, the three-dimensional (3D) control field calibration result is used to evaluate the precision of the conversion results. The experimental results show that when the camera calibration root mean square error is less than 0.3 pixel, the mutual conversion error of the two types of distortion models is less than 0.5 pixel, which can meet the conversion precision of the sub-pixel.