摘要
为提高超图匹配的正确匹配率并降低其计算复杂度,提出了一种基于稀疏方位超图匹配的图像配准算法。提取图像的结构特征点为图节点,采用最小生成树算法获取节点间的主要连接关系,并用包含邻近的节点与边的三元组结构定义超边,计算超边的方位角度信息,由此构建稀疏方位超图;利用方位信息构建亲近矩阵,并采用全局最优匹配方法实现匹配。实验表明,对于实际图像的配准,该算法既具有较低的计算复杂度,又有良好的匹配效果。
To improve matching ratio and decrease computational complexity of graph/hypergraph matching,an image registration algorithm based on sparse position hypergraph matching is proposed in this paper.Firstly,the graph model is constructed through extracting features from real images.Secondly,after getting the minimum spanning tree structure which contains the main connections among nodes of graph,sparse position hypergraph is obtained by using the position angle information of hyper-edge composed of three neighboring nodes in the minimum spanning tree.Thirdly,a inter-graph point proximity matrix is built by the position angle information.At last,an approach of global optimal soft matching is used to achieve matching.It can be clearly indicated that this algorithm has low computational complexity and is robust for image matching.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2010年第12期1865-1870,共6页
Journal of Optoelectronics·Laser
基金
国家自然科学基金资助项目(60905016
60805013)
"十一五"国防预研基金资助项目
关键词
稀疏方位超图
最小生成树
图像配准
sparse position hypergraph
minimum spanning tree
image registration
