An automatic SAR and optical images registration method based on improved SIFT is proposed in this paper, which is a
two-step strategy, from rough to accuracy. The geometry relation of images is first constructed by the geographic
information, and images are arranged based on the elevation datum plane to eliminate rotation and resolution differences.
Then SIFT features extracted by the dominant direction improved SIFT from two images are matched by SSIM as
similar measure according to structure information of the SIFT feature. As rotation difference is eliminated in images of
flat area after rough registration, the number of correct matches and correct matching rate can be increased by altering
the feature orientation assignment. And then, parallax and angle restrictions are introduced to improve the matching
performance by clustering analysis in the angle and parallax domains. Mapping the original matches to the parallax
feature space and rotation feature space in sequence, which are established by the custom defined parallax parameters
and rotation parameters respectively. Cluster analysis is applied in the parallax feature space and rotation feature space,
and the relationship between cluster parameters and matching result is analysed. Owing to the clustering feature, correct
matches are retained. Finally, the perspective transform parameters for the registration are obtained by RANSAC
algorithm with removing the false matches simultaneously. Experiments show that the algorithm proposed in this paper
is effective in the registration of SAR and optical images with large differences.