Fast stitching of UAV images based on improved SURF algorithm

In order to improve the speed of stitching and information extraction of remote sensing images, based on the UAV (Unmanned Aerial Vehicle) image stitching algorithm, this paper proposes a UAV image matching method based on the combination of SURF (Speeded Up Robust Features) and MASC (M-Estimate Sample Consensus) algorithm. the SURF algorithm is fast, and the MASC algorithm can effectively eliminate mismatch points and has high stability. In this paper, the SIFT (Scale-invariant feature transform) algorithm, SURF algorithm, SURF and RANSAC (Random Sample Consensus) algorithm as well as SURF and MASC algorithm are used to stitch the same two images and compare them respectively. The experimental results show that the lowest image matching error rate is only 2.13% and the matching time is 4.772670s when using the combination of SURF and MASC algorithm for image stitching, which has certain advantages.