在对建筑物变化立体检测时,考虑建筑物外形复杂、点云数据量大且分布不均,导致获取的建筑点云图存在较大噪声的问题,应用无人机激光雷达,设计一种新的建筑物变化立体检测方法。通过无人机激光雷达技术采集建筑物的点云数据,引入多尺度概念,建立多级虚拟网格,确定网格间距与网格规格,通过双向滤波算法,按照网格尺度大小逐层展开滤波处理,实现数据预处理。通过配准处理,获取重建数据中的匹配点对,计算对应点的三维空间距离,通过距离阈值和判定准则判断点云数据是否发生变化,实现建筑物变化立体检测。实验结果表明,所提方法可以精准、全面地检测建筑物变化,准确率高达90%,且检测耗时少。

In the detection of building changes in three dimensions, considering the complex shape of buildings, the large volume and uneven distribution of point cloud data, a significant noise issue is encountered in the acquired building point cloud images. By applying drone-based LiDAR technology, a novel method for detecting building changes in three dimensions is designed. The point cloud data of buildings are collected through drone-based LiDAR technology, and the concept of multi-scale is introduced. A multilevel virtual grid is established to determine the grid spacing and grid specifications. A bidirectional filtering algorithm is employed to perform filtering processing layer by layer according to the grid scale size, achieving data preprocessing. Through registration processing, matching point pairs are obtained from the reconstructed data, and the three-dimensional spatial distance of corresponding points is calculated. By using distance thresholds and judgment criteria, it is determined whether the point cloud data has changed, thereby realizing the detection of building changes in three dimensions. Experimental results demonstrate that the proposed method can accurately and comprehensively detect building changes, with an accuracy rate as high as 90%, and with minimal detection time.

TN958;V279

国家自然科学基金资助项目(42071447)