Image Registration Based on Sparse Position Hypergraph Matching

For improving matching precision, decreasing computational complexity of graph/hypergraph matching and integrating nodes structure information with feature similarity information, image registration algorithm based on sparse position hypergraph matching is proposed in this paper. Firstly, we construct the graph model through extracting features from real images. Secondly, after getting the minimum spanning tree structure which contains the main connections between nodes of graph, sparse position hypergraph is obtained by use of the position angle information of hyper-edge composed of three neighboring nodes at the minimum spanning tree. Thirdly, we utilize the position angle information and features similarity information to build a proximity matrix with inter-graph. At last, an approach of global optimal soft matching is used to achieve matching . It could be clearly indicated by the result that this algorithm is low computational complexity and robust for image matching.