Accurate matching method of multimodal image based on phase congruency and local mutual information

Chunyang Zhao; Huaici Zhao; Gang Zhao

doi:10.1117/12.2070198

24 November 2014 Accurate matching method of multimodal image based on phase congruency and local mutual information

Chunyang Zhao, Huaici Zhao, Gang Zhao

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93010N (2014) https://doi.org/10.1117/12.2070198
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

Multimodal image matching is difficult because of the contrast and intensity difference of the images. For solving this problem, a new matching method based on the phase congruency, histograms of oriented gradients and local normalized mutual information was proposed. The proposed method first extract feature points and edge map based on monogenic signal and phase congruency method which is insensitivity to variations in illumination and contrast. Then, the Monogenic Phase Congruency Edge Descriptor based on edge orientation histogram was generated by gathering the edge information of orientations from edge map around the feature point. For increasing the matched point-pair number, the Multi Candidate Point Matching Method by selecting multi better candidate matching points for each feature point was presented. Finally, the location accuracy was refined using local normalized mutual information method. The experimental results indicated that the proposed method could achieve higher performance in heterogonous image matching, the average matching correct rate up to 88%, is about 3 times of SURF matching method.

Citation Download Citation

Chunyang Zhao, Huaici Zhao, and Gang Zhao "Accurate matching method of multimodal image based on phase congruency and local mutual information", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010N (24 November 2014); https://doi.org/10.1117/12.2070198

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