基于重叠区域改进SURF的无人机影像快速匹配算法OA

In order to solve the problem of low matching accuracy and efficiency caused by the large amount of image information,large field of view,and complex terrain texture in UAV image matching algorithms,a fast matching algorithm for UAV images based on overlapping region improvement Speeded Up Robust Features(SURF)is proposed.The algorithm is mainly divided into three steps:①Using the overlapping rate of UAV images to calculate the image feature point detection and extraction area,and performing SURF feature point detection and extraction within the region to avoid invalid feature points from affecting matching accuracy and efficiency.②Replacing the original SURF algorithm rectangular template with a concentric ring 8-region template,and introducing image color information to construct a 34 dimensional feature descriptor for the feature matching.③ Using M-estimator Sample Consensus(MSAC)algorithm to eliminate mismatched points and achieving precise image matching.Experimental analysis shows that the proposed algorithm can effectively improve the accuracy of UAV image feature matching and the efficiency of algorithm runtime.