UAV image matching based on improving the ORB algorithm
This paper addresses the problem of unstable feature point extraction and pixel-level feature point localization accuracy faced by the ORB algorithm when encountering changes in illumination.To improve the ORB algorithm,a self-adaptive threshold method based on foreground-background contrast is proposed in conjunction with existing sub-pixel localization techniques.In order to avoid the error caused by the need for manual threshold setting in RANSAC algorithm,this paper introduces the MAGSAC++algorithm into the feature matching process for false match elimination.Experimental results show that the improved algorithm can obtain a larger number of matches,has better robustness to changes in illumination,and improves matching accuracy by at least 7%.