Heterogenous Image Matching Fusion Based on Cumulative Structural Similarity

To solve the problem of the limited capability of multimodal image feature descriptors constructed by gradient information and the phase consistency principle, a method of cumulative structure feature descriptor construction with rotation invariance is proposed in this paper. Firstly, we extract the direction of multi-scale and multi-direction feature point edges using the Log-Gabor odd-symmetric filter and calculate the amplitude of pixel edges based on the phase consistency principle. Then, the main direction of the key points is determined based on the edge direction feature map, and the coordinates are established according to the main direction to ensure that the feature point descriptor has rotation invariance. Finally, the Log-Gabor odd-symmetric filter calculates the cumulative structural response in the maximum direction and constructs a highly identifiable descriptor with rotation invariance. We select several representative heterogeneous images as test data and compare the matching performance of the proposed algorithm with several excellent descriptors. The results indicate that the descriptor constructed in this paper is more robust than other descriptors for heterosource images with rotation changes.