Automatic remote sensing image registration algorithm based on SIFT

YU Ting， LI Xiao-run
（College of Electrical Engineering， Zhejiang University， Hangzhou 310027， China）

Abstract： Aiming at the optical image affine transformation of the automatic registration，a coarse-to-fine remote sensing image automatic registration algorithm was proposed. Firstly，the input images were mapped for a local feature vector sets with translation，scaling and rotation invariant characteristic based on SIFT feature. According to the euclidean distance of the feature vector which is taken as the similarity decision measure，the initial matching feature points and the initial model parameter values of the transformation were determined. Secondly，making the mutual information as similarity measure，more established correspondence feature points were obtained based on the position control of the search strategy. Thirdly，the deeply optimized affine transformation model parameters were obtained by using the control points and the weighted least squares optimization algorithm together. In this way，a more sophisticated image registration was completed，and a root mean square error was used to evaluate the result of the registration. Finally joint histogram was taken as the registration precision evaluation standard to test registration effect. Experimental results demonstrate the effectiveness and accuracy of the proposed method.
Key words： remote sensing image； scale-invariant feature transform（SIFT）； image registration； position control； mutual information；coarse-to-fine