Research on UAV Image Splicing Technology Based on Improved SIFT Algorithm
Xiaoqing Chen, Hanyu Lu, Daode He, Yongyi Yuan · 2024
Aiming at the problems of high cost of capturing drone aerial images and poor image matching quality in the process of tobacco planting area statistics, an improved SIFT algorithm based on drone images is proposed. Firstly, the least squares method is used to extract feature points, and then the RANSAC algorithm is used to remove erroneous matching points for secondary filtering. Simulation results show that the least squares method used in this article for feature point extraction optimization algorithm has a good effect on removing redundant points, and the RANSAC algorithm used for removing erroneous matching points has high matching stability and good optimization effect. This provides certain technical support for the subsequent measurement of tobacco area and statistics of tobacco plant quantity in mountainous areas.