An image matching approach which integrates Maximally Stable Extremal Regions (MSER, Maximally Stable Extremal Regions) and Scale Invariant Feature Transformation (SIFT, Scale Invariant Feature Transformation) complementary invariant feature automatically is proposed for the tilt Remote Sensing image registration. Firstly, the images are coarsely matched by applying currently recognized as the best affine invariant MSER features, and the large deformation images are corrected initially. Then the images are fine matched by the matching ability of the SIFT descriptor joint the moments based on the coarse matching. The remote sensing image matching accuracy is improved through the above two steps, especially, the more pronounced effect on the large tilt images. Finally, the UAV(Unmanned Aerial Vehicle) image experiments show that this algorithm is more effective than SIFT algorithm in the affine invariant and matching the correct rate.