A notable limitation of the local self-similarity descriptor (LSS) is that it is considered unsuitable for multimodal image registration. In order to address this issue, a novel self-similarity descriptor is proposed and effectively applied for multi-modal image registration. First, the phase congruency algorithm is used to extract the maximum moment of the multimodal image. Second, Harris keypoints are extracted from the edge images obtained from the maximum moment information. Third, a binary image is produced based on the edge image, and a binary self-similar descriptor is constructed based on the binary image. Finally, descriptor similarity calculations and keypoint matching are performed for multimodal images. Comparative experiments demonstrate that the proposed binary self-similar descriptor serve as a replacement for the traditional self-similar descriptor, and it effectively improve the compatibility and efficiency of the self-similar descriptor for multimodal images.