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| Multi-sensor Image Matching Method Based on Joint Graph Spectral FeatureAnalysis |
| Nanjing Normal University
Hohai University |
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Abstract 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.
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Published: 24 February 2021
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