The invention discloses a
heterologous image accurate matching method, which comprises the following steps: firstly, respectively matching an
infrared grayscale image and a negative image thereof witha visible light
grayscale image, namely two to-be-matched image groups; secondly, for each image of the to-be-matched image group, extracting key points with invariable scales, and calculating LPQ feature vectors of neighborhoods of the key points; thirdly, performing weighted fusion on the SIFT feature, the
shape context feature based on the
angular point and the LPQ feature of each image in theto-be-matched image group, and performing initial matching on the images through a nearest neighbor
ratio method; fourthly, removing mismatching points; and finally, integrating the matching resultsof the
infrared grayscale image and the negative image thereof with the visible light grayscale image into a final matching result. According to the method, the context descriptor is designed to obtain
global information of the image, meanwhile, in order to further improve the matching performance, the LPQ descriptor is utilized to obtain image fuzzy invariant texture features, and finally, the method can obtain a
heterologous image accurate matching result.