摘要
利用尺度空间理论对多分辨率的红外与可见光图像配准算法进行研究,提出利用红外与可见光图像的多尺度特征点及边缘作为配准的特征,利用特征尺度确定用于相似度匹配的子图像大小,使用LTS-Hausdorff(least trimmed square Hausdorff)距离判断子图像的相似性。利用尺度空间理论及多尺度下图像的特征能更加全面的对图像进行描述。在利用多尺度特征获取到匹配对后,再利用随机一致性检测对匹配对进行提纯并获取空间变换的参数,然后使用该参数对红外与可见光图像进行配准与融合。实验结果表明,基于多尺度的图像配准方法,能有效对红外与可见光图像进行配准。
The scale-space theory is used to study the algorithm of infrared and visible images registration. The method of using muhi-scale feature points and edges of infrared and visible images as features in the registration is presented. The method of using characteristic scale to determine the sub-images size for the similarity matching is put forward and a LTS-Hausdorff distance is used to evaluate the similarity of the sub-images. Scale space theory and multi-scale fea- tures extraction algorithm can describe the image more comprehensive. After getting the match pairs, random sample and consensus algorithm is used to delete the false match pairs to gain the correct porameters of space transformation, then the parameters is used to registrate and fuse the infrared and visible images. The experiment results show that the method of image registration based on multi-scale can match infrared images and visible images effectively.
出处
《激光与红外》
CAS
CSCD
北大核心
2013年第3期329-333,共5页
Laser & Infrared
基金
南京航空航天大学基本科研业务费专项科研项目(No.NN2012083
No.NS2010214
No.1011-56XZA11048)资助
