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.