Image registration is of crucial importance in image fusion such as pan-sharpening. Mutual information (MI)-based methods have been widely used and demonstrated effectiveness in registering multi-spectral or multi-modal images. However, MI-based methods may fail to converge in searching registration parameters, resulting mis-registration. In this paper, we propose an outlier robust method to improve the robustness of MI-based registration for multiple rigid transformed images. In particular, we first generate registration parameter matrices using a MI-based approach, then we decompose each parameter matrix into a low-rank matrix of inlier registration parameters and a sparse matrix corresponding to outlier parameter errors. Results of registering multi-spectral images with random rigid transformations show significant improvement and robustness of our method.