针对光线强度过高或过低情况下的异源图像匹配问题，提出一种基于联合图频谱特征分析的异源图像匹配方 法。首先，采用K 近邻法则计算可见光图像与红外图像中角点的结构关系并构建联合图；接着，基于拉普拉斯分解计算联合图 中邻接矩阵的特征值从而得到邻接矩阵的特征向量，并通过三维重构构建特征函数对；第三，提出一种基于SU SAN -M SER - SU R F最大稳定极值区域检测器，检测特征函数对的极值位置；最后，通过对最大稳定极值区域进行归一化后匹配，可以得到 异源图像的精确匹配结果。实验结果表明，提出的基于联合图频谱特征分析的匹配方法能够解决光强过高或过低情况下的异 源图像匹配问题并取得较优异的匹配率。

Aiming at the problem of multi-sensor image matching when the light intensity is too high or too low, this paper proposes a method of multi-sensor image matching based on joint graph spectrum feature analysis. Firstly, the K-nearest neighbor rule is used to calculate the structural relationship between the corner points in the visible light and infrared images to construct a joint graph. Then, based on Laplacian decomposition, we calculate the eigenvalues of the adjacency matrix in the joint graph to obtain the fea- ture vector of the joint graph, and construct the feature function pair through three-dimensional reconstruction. Thirdly, a maximally stable extremal regions detector based on SUSAN-MSER-SURF is proposed to detect the extreme value position of the feature func- tion pair. Finally, by normalizing the maximum stable extremal regions and matching them, the exact matching results of multi-sen- sor images can be obtained. The experimental results show that the proposed matching method based on the spectral feature analysis of the joint graph can solve the problem of multi-sensor image matching when the light is too high or too low.