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Image registration method by using corner and edge contents is proposed. In this method, the algorithm runs as a coarse-to-fine strategy to find a precise alignment between images in a rigid planar motion. In a coarse stage, landmarks in both images are detected by Harris corner detection. Rough alignment is geometrically found by matching a group of corners, instead of one-on-one, across two images. Next in a refining stage, Radon transform is applied to compute the precision of registration in a subpixel accuracy. Our algorithm is compared with the FFT-based method on both simulated and real world images. With the same accuracy level with FFT-based method, the results show superiorities in both degree of freedom and computational complexity. Finally, super-resolution imaging is introduced to demonstrate the capability of the proposed registration method on real world application.