Aiming at the problems such as false matching points and large volume remote sensing image registration, a high-resolution remote sensing images registration algorithm based on coarse and fine registration is proposed. Firstly, the high scale space feature points were extracted after down sampling the images to execute the coarse registration. Secondly, the initial set of feature points was extracted using the Scale Invariant Feature Transform (SIFT) algorithm for each block after using image blocking strategy. Furthermore, feature points were used to obtain the Delaunay triangulation, and then calculated the similarity between blocks of both images to select pairs of triangles which the similarity greater than threshold. Finally, the fine registration was achieved by precise feature points. The proposed algorithm can reduce the number of feature points, and it can eliminate more false matching points to increase the correct feature point matching rate. The experimental results indicate that the proposed method is effective.