Fast Aerial Image Stitching Algorithm for UAV Based on Improved SURF
Xinkai Zhu, Zhibin Li, Chongshang Sun, Jiawei Chang, Wei Li · 2023
In order to address the realtime performance and robustness issues in UAV aerial image stitching, an improved SURF-based algorithm is proposed. This algorithm enhances the stitching process for UAV aerial images by first employing the Speeded-Up Robust Features SURF algorithm for rapid and robust feature point detection and localization. Subsequently, binary BRISK descriptors are used for feature description. In the feature matching phase, an initial coarse matching is performed using the Nearest-Neighbor Distance Ratio NNDR algorithm to filter out correct match pairs. Then, precise matching is achieved through the application of the PROSAC algorithm. Finally, a weighted fusion algorithm is employed for seamless image stitching. Experimental results demonstrate significant improvements in both matching efficiency and accuracy achieved by this algorithm. It serves as a robust and highly accurate solution with excellent stitching outcomes for UAV aerial image stitching.