传统基于谱图的图像匹配算法大多利用特征点集中点的位置关系进行匹配，并未充分利用特征点周围的灰度信息，为此，文中提出了一种基于谱特征的图像匹配算法，该算法利用线图谱来反映特征点周围灰度的变化，对特征点周围的邻域点进行分层，并对每层中的点构造线图，通过线图谱获取特征点的谱特征; 理论分析表明，该谱特征具有旋转不变性、亮度线性变化不变性及对噪声的较高鲁棒性． 最后，利用匈牙利算法求解匹配问题，输出匹配结果． 实验结果表明，文中算法具有较高的匹配精度，在待匹配图像间存在较大形变时，也可以获得较好的匹配结果．

The traditional image matching algorithm based on spectral graph usually matches the points with the position relationship of feature points，and the gray information around feature points is not fully utilized． In order to solve this problem，this paper proposes an image matching algorithm based on spectral features． This algorithm uses the spectrum of line graph to reflect the changes of the gray level around feature points，stratifies the neighbors of each feature point，and then constructs a line graph for the points of each layer． Thus，the spectral features of feature points are obtained from the spectrum of line graph． Theoretical analysis demonstrates that the spectral features are of rotation invariance，linear brightness variation invariance and strong robustness to noise． Finally，the Hungarian algorithm is used to solve the matching problem and output the matching results． Experimental results show that the proposed algorithm has a high matching accuracy，and it can also achieve better matching results under a
larger deformation between the two images to be matched．