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Aiming at the problems of brightness, scale, and image overlap in unmanned aerial vehicle remote sensing images, BBF optimization algorithm is used to design a registration method for unmanned aerial vehicle remote sensing images. According to the principle of unmanned aerial vehicle remote sensing imaging, obtain unmanned aerial vehicle remote sensing images as registration objects, and complete the preprocessing of initial remote sensing images through image fusion, correction, and other steps. Extract the SIFT feature points and contour features of the drone remote sensing image, and use the BBF optimization algorithm to search for feature matching between the current image and the reference image to complete the feature matching of the image. Finally, the registration results of UAV remote sensing images are obtained through three steps: rough matching, fine matching, and eliminating erroneous matching points. Through the effectiveness testing experiment, it is concluded that compared with traditional registration methods, the optimized design method improves the accuracy of feature matching points by 5.15%, and reduces the missed matching rate by 3.75%.