基于干线对的红外与可见光最优图像配准算法

提出了一种基于干线对的红外与可见光图像配准算法.该算法分4步:首先分别从基准图像和待配准图像中提取干线对,即对图像中满足特定条件的直线进行配对;然后按照一些准则寻找这两幅图像中的干线对所有可能的匹配情况,并组成一个集合;接着从该集合中寻找这样一个子集,在保证每个干线对最多出现在它的一个元素中的前提下,使得该子集所有元素的相似性测度之和最大且由它确定的配准误差最小,该文采用分支定限法解决了这一优化问题;最后由最优子集中的所有元素得到同名像点集,运用仿射变换模型,实现图像的配准.大量实验表明,文中提出的方法对红外与可见光遥感图像之间的配准是有效的.

An Optimal Algorithm for IR/Visual Image Registration Based on Main-Line-Pairs

An optimal algorithm for IR/visual image registration based on Main-Line-Pairs(MLPs)is presented.It is divided into four steps:we firstly extract all MLPs,which consist of two lines which satisfy certain conditions,from the based and sensed images,respectively;and then according to some criteria construct as much putative matching pairs between MLPs from the two images as possible to form a matching set;thirdly,exploit a branch-and-bound method to find a subset to maximize its total similarity measure and to minimize its registration error under the condition that each MLP from the two images at most belongs to only one element of the subset;finally,use all control points which are acquired from the optimal subset and affine transformation model to register the two images.The experiment results tested by IR/visual images are shown that the proposed algorithm for registration is accurate and effective.