%A Tong CHEN,Jian-feng GUO,Xin-zhong HAN,Xue-li XIE,Jian-xiang XI %T Visible and infrared image matching method based on generative adversarial model %0 Journal Article %D 2022 %J Journal of ZheJiang University (Engineering Science) %R 10.3785/j.issn.1008-973X.2022.01.007 %P 63-74 %V 56 %N 1 %U {https://www.zjujournals.com/eng/CN/abstract/article_42616.shtml} %8 2022-01-20 %X

A visible-infrared image matching method based on generative adversarial model was proposed based on the style transfer of generative adversarial network and traditional local feature extraction capability in order to analyze the problems of large modal difference, difficult matching and poor robustness of existing multi-sensor images matching methods. The loss function calculation path was added and a new loss function was constructed according to the idea of style transfer in GAN network in order to improve the transfer effect of the model on the multi-sensor images. The feature information of the transformed homologous images was extracted by using SIFT algorithm. Then the position and scale of the points to be matched were determined. The feature matching and similarity measurement between the two images were indirectly completed according to the matching strategy. Experiments were conducted on the realistic aerial dataset. Results show that the proposed method can effectively deal with multi-modal data and reduce the difficulty of multi-sensor image matching. The method can provide a new solution for multi-sensor images matching.