A robust automated image matching strategy based on an improved SIFT feature extraction algorithm was proposed according to the characteristics of SIFT algorithm and lunar images. Firstly, the extraction equilibrium of key points was improved by automatically adjusting the coefficient of controlling contrast in the SIFT algorithm.Then, the coarse matching was carried out by using the ratio of the minimum and the second minimum Euclidean distance between the description vectors of SIFT as a threshold and the part incorrect matching of the coarse matching set was removed by principal direction angle difference histogram of matches. Finally, the initial parameters of perspective transformation model were determined by using modified RANSAC method, automatically calculated random sampling numbers, and parameters of error tolerance. Moreover, the model and the error tolerance were used to calibrate the matching pairs in the matching set and to select the correct matching pairs. The experimental results prove that the proposed method is stable and reliable under some variations for view points, illumination, rotation, scale and out of focus and it can select the matching threshold of images automatically without manual intervention.