DocumentCode
2851100
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
Volume
1
fYear
2000
fDate
2000
Firstpage
481
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location
Vancouver, BC
ISSN
1522-4880
Print_ISBN
0-7803-6297-7
Type
conf
DOI
10.1109/ICIP.2000.901000
Filename
901000
Link To Document