Heterogeneous image matching method based on deep learning
user-5d3e648c530c70f916110a1f(2018)
Abstract
The invention relates to a heterogeneous image matching method based on deep learning. A heterogeneous image block data set is made; image preprocessing is carried out; an image block feature map is obtained; a feature vector is obtained based on the feature map; feature map fusion and normalization are carried out; an image matching network is trained; and a matching probability is predicted. Therefore, a problem of over-fitting of heterogeneous image block matching in the prior art is solved; the performance of the network is improved substantially; the training efficiency of the network isenhanced; and the robustness of the network is enhanced. The heterogeneous image matching method can be applied to fields of heterogeneous image registration, image tracking, multi-view reconstructionand the like.
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Key words
Image registration,Feature vector,Robustness (computer science),Deep learning,Normalization (statistics),Block (data storage),Preprocessor,Pattern recognition,Computer science,Artificial intelligence,Image matching
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