Multi-Modal Image Registration Based on Local Self-Similarity and Bidirectional Matching

The registration of images from infrared sensors and visible color sensors is a quite difficult problem due to their different phenomena. In this paper, we propose a new method to register visible and infrared images. The proposed approach consists of three main steps. In the first step, SURF (Speeded-Up Robust Features) algorithm is applied for local feature extraction. In the second step, LSS (local self-similarity descriptor) is computed for each extracted feature. Finally, a cross matching process followed by a consistency check in the projective transformation model is performed for feature correspondence and mismatch elimination. Experimental results show the proposed method achieves better accuracy for registering visible and infrared images as compared to state-of-the-art approaches.