In order to quickly obtain a wide range of pavement images with sufficient clarity, a stitching algorithm for aerial pavement images is proposed, which can quickly and accurately process the images to obtain the stitched images of the pavement surface so as to provide convenience for the application of unmanned aerial vehicle aerial photography in the field of pavement transportation. When pavement images are stitched, the images contain large similar areas, resulting in a low registration accuracy, a large amount of image information, and a long stitching time. In order to solve this problem, this paper proposes to determine the overlapping area of adjacent images before feature point extraction. Scale-invariant feature transform feature points combined with sparse representation matching method in the overlapping area to register adjacent images. Then, wavelet transform method is used fuse the images to improve the stitching effect. Experimental results prove that the proposed method can effectively process aerial pavement images and obtain better pavement stitching images.