摘要
介绍了一种基于SIFT的红外与可见光图像配准方法。首先用SIFT算法提取特征点并构造特征描述子,在特征点提取过程中采取了基于SUSAN算子的约束策略,其次用基于k-d树的最近邻方法对特征点进行匹配,用RANSAC算法求解变换矩阵,最后对待配准图像做相应参数的坐标变换及双线性插值,从而实现图像配准。实验表明,该方法具有稳定、可靠、快速等特点。
An improved method of IR and Visible Images Registration based on SIFT is proposed. Firstly,the feature points are extracted by SIFT and an constraint strategy based on SUSAN operator is added in the process,then the feature descriptors are created.Secondly,the nearest-neighbor method based on k-d tree is used to find the corresponding matching points and the RANSAC algorithm is used to acquire transformation matrix.Finally,carrying out transformation and bilinear interpolation in the image prepared for registration to realize image registration.Experimental results show that the method is stable,reliable and efficient.
出处
《火力与指挥控制》
CSCD
北大核心
2011年第11期168-171,175,共5页
Fire Control & Command Control
关键词
SIFT
图像配准
SUSAN算子
SIFT（Scale Invariant Features Transform）
image registration
SUSAN operator
