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A rough-to-fine satellite image registration method that can realize robust alignment with sub-pixel accuracy is described. The registration procedure is composed of several steps. Firstly, a globally rough registration using single-template normalized crosscorrelation is realized to get an overlapped area. Secondly, multiple sub-images are randomly generated in the roughly overlapped area, and templates are selected according to empirical entropy. In the third step, a locally rough-to-fine registration is performed in order to get tie-points, and during this step, an optimal matching accuracy degree is achieved by means of "gradient descent" searching method. The last part is the estimation of mapping function and image transformation. Experimental results on satellite optical images validate the efficiency and accuracy of the proposed algorithm.