Open AccessRemote sensing image registration based on full convolution neural network and k-nearest neighbor ratio algorithm
Author(s) -
Dongzhen Wang,
Ying Chen,
Jipeng Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1873/1/012026
Subject(s) - affine transformation , k nearest neighbors algorithm , computer science , artificial intelligence , convolutional neural network , pattern recognition (psychology) , feature (linguistics) , transformation (genetics) , image registration , image (mathematics) , convolution (computer science) , matching (statistics) , transformation matrix , algorithm , artificial neural network , noise (video) , computer vision , mathematics , linguistics , philosophy , biochemistry , chemistry , statistics , kinematics , physics , classical mechanics , pure mathematics , gene
Aiming at the problem of low accuracy of remote sensing image registration caused by the negative effects of noise and imaging in some traditional algorithms, an effective remote sensing image registration method based on depth feature from coarse to fine is proposed. In the coarse registration stage, the full convolution neural network is used to extract the features of the input image, then the nearest neighbor distance ratio algorithm is used to coarse match the features and finally an approximate transformation matrix is obtained. In the stage of fine registration, firstly, the image features are extracted by the improved convolutional neural network based on shortcut connection, then the affine transform coefficients are obtained by the combination of approximate transform matrix and k-nearest neighbor ratio algorithm. Finally, the image to be registered can be transformed according to the coefficients to achieve the purpose of registration. Experimental results show that, compared with the comparison method, the proposed method can increase the correct matching correspondence, so as to improve the accuracy of registration.