特征点匹配和互信息融合下连续形变图像配准  

Registration of Continuous Deformation Images under Feature Point Matching and Mutual Information Fusion

作　　者：陆杨[1] 杨茂云[2] LU Yang;YANG Mao-yun(School of Information and Electrical Engineering,Xuzhou University of Technology,Xuzhou Jiangsu 221018,China;School of Wisdom Education,Jiangsu Normal University,Xuzhou Jiangsu 221116,China)

机构地区：[1]徐州工程学院信息工程学院,江苏徐州221018 [2]江苏师范大学智慧教育学院,江苏徐州221116

出　　处：《计算机仿真》2023年第8期182-185,共4页Computer Simulation

摘　　要：图像配准中易受到外界干扰发生变形或者部分特征缺失,为此提出融合特征点匹配和互信息的连续形变图像配准方法。提取连续形变图像特征,对提取到的特征实施匹配处理,结合互信息算法统计两图像之间的相似程度,得出最佳配准指标,即像素灰度值为最大值,结合特征点匹配结果以及互信息算法生成图像配准刚性指标,实现连续形变图像配准。实验结果表明,所提方法配准后图像信息完整,配准效果较好,且匹配耗时较短,说明其能够降低图像配准中干扰因素的影响,有效提升图像配准质量。At present,image registration is easy to be deformed by external interference.Therefore,a method to register continuous deformation images based on feature point matching and mutual information was proposed.Firstly,we extracted the features of continuous deformation images and then matched these features.Secondly,we calculated the similarity between the two images by using the mutual information algorithm,thus obtaining the best registration index,that is,the pixel gray value is the maximum value.Finally,the registration result was combined with the mutual information algorithm to generate a rigidity index of image registration.Thus,the continuous deformation image registration was achieved.Experimental results show that the proposed method has complete image information after registration,and shorter matching time,indicating that it can reduce the influence of interference factors and effectively improve the quality of image registration.

关 键 词：特征点匹配 互信息 图像配准 自动尺度选择方法 相似度 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]