Title :
Image registration with minimum spanning tree algorithm
Author :
Ma, Bing ; Hero, Alfred ; Gorman, Joe ; Michel, Olivier
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
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 graph-representation method for image registration with Renyi entropy as the dissimilarity metric between the 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
Keywords :
biomedical MRI; brain; entropy; geophysical signal processing; graph theory; image matching; image registration; medical image processing; minimisation; terrain mapping; topography (Earth); trees (mathematics); MR images; Renyi entropy; dissimilarity metric; electro-optical image; graph-representation method; image matching; image processing; image registration; k-MST; length minimization; magnetic resonance images; minimum k-point spanning tree; minimum spanning tree algorithm; overlapped images; spurious discrepancies; terrain height map; Entropy; Image processing; Image registration; Joints; Magnetic resonance; Probability distribution; Rain; Robustness; Testing; Tree graphs;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.901000