A Two-Stage Registration Method for Visible Light and SAR Images Based on Structural Information
To address the problems of low registration accuracy and nonlinear radiometric differences in the alignment of visible light and Synthetic Aperture Radar(SAR)images,a novel two-stage registration algorithm for visible light and SAR imagery based on structural information is proposed.In the coarse reg-istration stage,the improved maximal self-dissimilarity detector(MSD)is used to detect feature points in visible light and SAR images;then,based on the local self-similarity(LSS),the maximum self-similarity index map(MSSIM)is constructed;finally,the correct matched point pairs are identified using the nea-rest neighbor to second nearest neighbor distance ratio combined with a rapid consensus sampling approach to estimate the transformation model.In the fine matching stage,the pixelwise structural feature repre-sentations of visible light and SAR images are established respectively;then,in visible light images,the template windows centered on feature points are selected,and the transformation model is used to estimate the corresponding search areas in SAR images;finally,Euclidean distance is employed as a similarity measure for template matching,and the Fast Fourier Transform(FFT)is utilized to accelerate the tem-plate matching process.The experimental results on nine pairs of real visible light and SAR images show that the proposed method has significant advantages in the registration of visible light and SAR images,compared with the other methods,such as RIFT,HAPCG,OSS,LNIFT,and ASS methods.The num-ber of correct matches(NCM)has been increased by 7.95,10.86,29.32,14.75,and 9.84 times,respec-tively,and the positioning accuracy has been improved by 0.44,0.42,0.35,0.41,and 0.40 pixels.
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