基于角点特征和最大互信息的图像配准

摘要

Registration based on mutual information is a typical method in medical image registration. Mutual information is a common similarity measure in image registration, which has excellent robustness and accuracy, but large calculation amount makes it difficult to be applied to clinics. A maximization of mutual information based image registration method is described. Firstly Because of using maximum mutual information to image registration have inferiority, the registration based on local curvature maximum to obtain corner points. Then, the one to one matching points could be obtained through mutual information rough match. Experimental results indicate the proposed algorithm can achieve better accuracy and good robust%基于互信息的配准方法是图像配准领域的重要方法.互信息是图像配准中常用的相似性度量,具有鲁棒、精度高等优点,但基于互信息的配准计算量大,制约了它的实际应用.文章提出一种基于角点和最大互信息配准方法:首先采用间接算法来计算曲率的极大值点,从而能快速准确的提取角点集；接着计算两幅图像角点集间的互信息,最后通过POWELL算法搜索使互信息最大以实现配准.实验表明,该算法计算简单,配准速度快,具有更好的精确性和鲁棒性.