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《Infrared Technology》 2019-06
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Registration Algorithm for Heterogeneous Remote Sensing Images Based on Geometric Invariance and Local Similarity Features

ZHOU Weishuo;AN Bowen;ZHAO Min;PAN Shengda;College of Information Engineering, Shanghai Maritime University;  
This paper proposes a registration algorithm based on geometric invariance and local similarity features(also known as GISS(geometric invariant self-similarities)), to address the problem of geometric deformation of remote sensing images during image registration. The GISS algorithm first uses the SURF operator and the Euclidean distance to pre-match the heterogeneous remote sensing images with their geometric differences, thereafter rotates the images according to the directional characteristics of the feature points, and finally uses the local self-similarity descriptors and integrates similarity measures to examine the phase of the pre-matched point pairs. The experimental results show that, for remote sensing images with geometric deformations, it has a superior effect on registration, can effectively resolve the problem of geometric deformation between the images, and therefore, ensures better robustness and registration accuracy.
【Fund】: 国家自然科学基金(61302132 41701523 61504078);; 上海市教育发展基金会“晨光计划”(13CG51);; 广西省教育厅基金(YB2014207)资助
【CateGory Index】: TP751
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