关键词: 改进哈里斯鹰算法, 八叉树结构法, 最小二乘支持向量机, 点云孔洞修补

Abstract: Aiming at the problem that there will be more holes in the UAV matching point cloud after ground point filtering,this paper proposes to use the improved Harris Hawks optimization algorithm to optimize the least squares support vector machine to repair the ground point cloud hole. Firstly,the eight-pronged tree structure method is used to extract ground feature points from the filtered point cloud data. Secondly,the Harris Eagle algorithm is improved by using nonlinear convergence factor and adaptive escape probability strategy,and it is used for parameter optimization of hole repair model of least squares support vector machine. Experimental results show that compared with the conventional least squares support vector machine,the hole repair accuracy of the combined model is improved by 34.3%,and its stability is also enhanced,which has a certain timeliness and reality.

Key words: improved Harris Hawks optimization algorithm, octagonal tree structure method, least squares support vector machine, point cloud hole repair