一种基于平面特征的点云质量优化方法

A method for optimizing point cloud quality based on plane features

倾斜摄影测量技术目前被广泛应用于大规模城市级三维实景建模中,但对于建筑物的精细建模,倾斜摄影测量的测量精度还不能满足要求,密集重建生成的密集点云数据质量还需进一步提升。大部分城市建筑为规则建筑,本文提出一种基于平面特征的点云质量优化方法,用于提升采用倾斜摄影测量密集重建点云的数据质量,并与地面三维激光点云据进行对比。结果表明,该方法可以优化提升密集重建点云的数据质量。

Oblique photogrammetry technology is currently widely used in large-scale level urban 3D real scene modeling.However,for precise modeling of buildings,the measurement accuracy of oblique photogrammetry cannot meet the requirements,and the quality of dense reconstruction point clouds needs to be further improved.Most urban buildings are regular buildings.This article proposes a point cloud quality optimization method based on planar features to improve the data quality of dense reconstructed point clouds using oblique photogrammetry.The comparison with ground 3D laser point clouds shows that this method can optimize and improve the data quality of dense reconstructed point clouds.