目的 镜头畸变影响着3维重建、几何量测等工作的质量。根据图像中的灭点几何约束条件，提出一种根据灭点进行弱径向畸变自动校正方法。方法 为避免包含畸变中心参数的非线性模型优化结果的不稳定性，在求解径向畸变系数之后进一步对畸变中心进行优化。首先根据灭点几何约束条件建立关于灭点与径向畸变系数的非线性模型，使用Levenberg-Marquardt（LM）算法估计灭点坐标与径向畸变参数，然后根据质量评价准则对畸变中心和径向畸变系数进一步迭代优化；最后，通过真实图像对该方法的可行性进行分析验证。结果 采用不同的数据对径向畸变进行了有效地校正，并采用校正后的数据进行了相机标定，标定结果相对于传统基于非量测校正方法有明显的提高。 结论 充分利用图像中的灭点属性，提出一种新的镜头径向畸变校正方法。实验结果表明，该方法能够有效地对径向畸变进行校正，并克服了传统基于非量测畸变校正方法的不稳定性。

Objective Lens distortion,which is a fundamental problem in photogrammetry and computer vision, has serious effects on the three-dimensional reconstruction and on the geometric image measurements. Method In this paper,an automatic correction of weak radial distortions based on vanishing points from a single image is presented. In order to reduce the effects caused by the nonlinear model included in the distortion center,the distortion center is further optimized after the radial distortion is estimated. A nonlinear model of vanishing points and radial distortion,which can be estimated by the Levenberg-Marquardt (LM) algorithms,is established based on the geometric constraint of vanishing points;then,the distortion center and radial distortion is optimized by an iterative method based on a suitable quality measurement. At last,the presented method is tested and verified. Result The radial distortions using different data are all effectively corrected. Compared with the traditional methods based on non-metric distortion correction,the results of camera calibration after correction are significantly improved. Conclusion The results of our experiments indicate that the approach can effectively correct radial lens distortion,while effectively overcome the instability of the traditional methods based on non-metric distortion correction.