An adaptive normalized convolution super-resolution algorithm based on edge detection and Keren registration method is proposed. To further improve registration precision of low-resolution image sequences,we combine Keren registration method with edge detection in the algorithm. Firstly,the edge feature of image sequences is extracted by Roberts operator. Then the registration parameters between edge feature images are obtained by Keren improvement registration method which is based on four parameters affine transformation model. The results of simulation experiment show that if the image edge detection is introduced before the Keren algorithm,the registration precision will be increased greatly even though there are noises and large rotation between images sequences. And a higher precision can be obtained by using Roberts operator compared with other traditional operators. Finally,the adaptive normalized convolution super-resolution fusion algorithm is used to reconstruct high-resolution image from low-resolution image sequences. Excellent reconstruction capability of the super-resolution algorithm based on the proposed registration method is demonstrated through an experimental real aliased image sequences.