Image Registration with Minimum Spanning Tree Algorithm

Registration is a fundamental task in image processing and quite a few registration techniques have been developed in various fields. In this paper we propose a novel graphrepresentation method for image registration with Rényi entropy as the dissimilarity metric between images. The image matching is performed by minimizing the length of the minimum spanning tree (MST) which spans the graph generated from the overlapped images. Our method also takes advantage of the minimum k-point spanning tree (k-MST) approach to robustify the registration against spurious discrepancies in the images. The proposed algorithm is tested in two applications: registering magnetic resonance (MR) images, and registering an electro-optical image with a terrain height map. In both cases the algorithm is shown to be accurate and robust.