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用于减轻机载激光雷达数据对建筑物边界正则化的遮挡影响的加权迭代CD样条法

Weighted Iterative CD-Spline for Mitigating Occlusion Effects on Building Boundary Regularization Using Airborne LiDAR Data.

作者信息

Dos Santos Renato César, Habib Ayman F, Galo Mauricio

机构信息

Department of Cartography, São Paulo State University (UNESP), Presidente Prudente, São Paulo 19060-900, Brazil.

Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907-2050, USA.

出版信息

Sensors (Basel). 2022 Aug 26;22(17):6440. doi: 10.3390/s22176440.

DOI:10.3390/s22176440
PMID:36080902
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9460831/
Abstract

Building occlusions usually decreases the accuracy of boundary regularization. Thus, it is essential that modeling methods address this problem, aiming to minimize its effects. In this context, we propose a weighted iterative changeable degree spline (WICDS) approach. The idea is to use a weight function for initial building boundary points, assigning a lower weight to the points in the occlusion region. As a contribution, the proposed method allows the minimization of errors caused by the occlusions, resulting in a more accurate contour modeling. The conducted experiments are performed using both simulated and real data. In general, the results indicate the potential of the WICDS approach to model a building boundary with occlusions, including curved boundary segments. In terms of and , the proposed approach presents values around 99% and 0.19 m, respectively. Compared with the previous iterative changeable degree spline (ICDS), the WICDS resulted in an improvement of around 6.5% for completeness, 4% for , and 0.24 m for the metric.

摘要

建筑物遮挡通常会降低边界正则化的准确性。因此,建模方法必须解决这个问题,旨在将其影响降至最低。在此背景下,我们提出一种加权迭代可变度样条(WICDS)方法。其思路是对建筑物初始边界点使用权重函数,为遮挡区域内的点赋予较低权重。作为一项贡献,所提出的方法能够将遮挡引起的误差最小化,从而实现更精确的轮廓建模。所进行的实验使用了模拟数据和真实数据。总体而言,结果表明WICDS方法在对有遮挡的建筑物边界(包括弯曲边界段)进行建模方面具有潜力。在完整性和[此处原文缺失一个指标名称]方面,所提出的方法分别呈现出约99%和0.19米的值。与先前的迭代可变度样条(ICDS)相比,WICDS在完整性方面提高了约6.5%,在[此处原文缺失一个指标名称]方面提高了4%,在[此处原文缺失一个指标名称]指标上提高了0.24米。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b46/9460831/7e2597c29bf7/sensors-22-06440-g015.jpg
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本文引用的文献

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