Remote Sensing Image Registration Method Based on U-net Segmentation and HEIV Model

Abstract

Image registration is required for the aerial remote sensing images when it is utilized for land mapping and change detection.In order to achieve high-precision matching of target regions,a remote sensing image registration method is proposed.To suit for the small sample data sets,the images are segmented by U-net.Considering the errors of different regional features,Heteroscedastic Errors-in-Variables(HEIV) model is applied to the registration parameter estimation to improve the registration accuracy of the target region.Experimental results show that compared with the Harris corner-based registration method,the global average registration accuracy of the proposed method is improved by 41.39%,and compared with the Scale-Invariant Feature Transform(SIFT) feature-based registration method,the average registration accuracy of the regions of interest is increased by 16.67%.