由于制造与装配误差难以完全消除，因此数码摄像机的光学系统存在不同程度的非线性畸变，严重影响利用其影像进行实时拼接的精度。通过比对分析一种经典的数码相机畸变模型与Brown模型的适应性，提出将简化的Brown模型作为数码摄像机的畸变模型。同时，基于单像空间后方交会，按照最小二乘平差方法求解摄像机光学系统的非线性畸变差参数。最后，通过三维控制场对三种型号的摄像机进行了检校试验。结果表明，所用的畸变模型明显优于经典畸变模型，使数码摄像机的整体检校精度小于0.5 pixel。而且检校结果稳定可靠，有效地补偿了光学系统的畸变差，有利于恢复图像内部的相对几何关系。

Due to the difficulties in eliminating manufacturing and assembly errors, different degrees of nonlinear distortions occur in the optical system of digital video cameras, which seriously affects the accuracy of real-time image stitching. Through the comparison of a traditional distortion model of digital camera and the Brown model, we propose to utilize the simplified Brown model as the distortion model of digital video cameras. At the meantime, least squares adjustment is applied to solve the nonlinear distortion parameters based on single-photo space resection. Finally, three types of digital video cameras are calibrated by three- dimensional control field. Experimental results show that the calibration accuracy of a video camera via the proposed distortion model is distinctively higher than the classic distortionmodel, which is less than 0.5 pixel. Moreover, the calibrated parameters are stable and faithful, which effectively amends the distortion and helps to recover the relative geometric relationship inside an image.