基于边缘结构特征的红外与可见光图像配准算法  

Infrared and Visible Image Registration Algorithm Based on Edge Structure Features

作　　者：徐海洋 赵伟[1] 刘建业[1] XU Haiyang;ZHAO Wei;LIU Jianye(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211100,China)

机构地区：[1]南京航空航天大学自动化学院,江苏南京211100

出　　处：《红外技术》2023年第8期858-862,共5页Infrared Technology

基　　金：国家自然科学基金(61603181);江苏高校优势学科建设工程项目资助。

摘　　要：针对红外与可见光图像难以提取特征点实现配准的问题,提出一种基于边缘结构特征的红外与可见光图像配准算法。首先通过优化的显著性算法增强红外图像的结构特征;其次利用相位一致性提取红外和可见光图像的稳定边缘结构;然后提取边缘结构的ORB(oriented FAST and rotated BRIEF)特征点;最后结合KNN(K-nearest neighbor)算法和余弦相似度对匹配特征点进行筛选,并应用RANSAC(random sample consensus)算法进行提纯。实验表明,该算法能够克服灰度差异的影响,具有较高的配准精度和效率,有助于实现红外与可见光图像的配准。Here,a registration algorithm based on edge structure features is proposed to solve the difficulty of extracting feature points from infrared and visible images.First,the structural features of infrared images are enhanced using an optimized saliency algorithm.Second,we extract the stable edge structures of the infrared and visible images using a phase consistency algorithm.Further,the ORB feature points are extracted from the edge structures.Finally,the KNN algorithm and cosine similarity are combined to filter the matching feature points,and the random sample consensus(RANSAC)algorithm is used for purification.Experimental results show that the algorithm overcomes the influence of grayscale differences between infrared and visible images.In addition,it achieves a high registration accuracy and efficiency,which is conducive to the registration of infrared and visible images.

关 键 词：显著性检测 相位一致性 特征提取 图像配准 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]