Open AccessVisible and infrared missile-borne image registration based on improved SIFT and joint features
Author(s) -
Song Xue,
Xiaorong Zhang,
Hang Zhang,
Chen Ning Yang
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 - 10.1088/1742-6596/2010/1/012103
Subject(s) - image registration , scale invariant feature transform , artificial intelligence , missile , computer vision , computer science , matching (statistics) , point set registration , infrared , point (geometry) , image (mathematics) , mathematics , optics , engineering , statistics , physics , geometry , aerospace engineering
For the acquired visible and infrared missile-borne images, in order to provide accurate and reliable image data for the subsequent processing of images to achieve complementary information, we carried out visible and infrared missile-borne image registration research. Firstly, the shape context is used to extract the rough edge features of the image. Then we improve the SIFT gradient definition to overcome the difference in image gray value, and combine with the coherent point drift algorithm to increase the number of correct matching points to achieve global image registration. Experimental results show that, compared with the existing registration methods, the proposed method has a good visual effect of registration, greatly improves the correct registration points and registration accuracy, and can better solve the problem of visible infrared missile-borne image registration.