论文标题
Flakeout:从陆地激光扫描中去除风雪的几何方法
FlakeOut: A Geometric Approach to Remove Wind-Blown Snow from Terrestrial Laser Scans
论文作者
论文摘要
风吹雪颗粒通常会污染雪地覆盖地形的陆地激光扫描(TLS)数据。但是,由于风吹雪和TLS扫描几何形状的空间分布,常见的过滤技术无法过滤风吹积积雪,并从真实表面过滤数据不正确。我们提出Flakeout,这是一种专门用于从TLS数据过滤风片的滤网的过滤器。 Flakeout的一个关键方面是\ num {2.8e-4}的较低假正率 - 比标准过滤技术低的数量级 - 这大大降低了错误删除的真实地面点的数量。这种较低的误报率使得薄片适合需要在光线至中度吹雪状况的雪表面进行定量测量的应用。此外,我们还提供数学和软件工具,以有效估计用于删除数据集中很少发生的错误数据点的过滤器的假阳性率。
Wind-blown snow particles often contaminate Terrestrial Laser Scanning (TLS) data of snow covered terrain. However, common filtering techniques fail to filter wind-blown snow and incorrectly filter data from the true surface due to the spatial distribution of wind-blown snow and the TLS scanning geometry. We present FlakeOut, a filter designed specifically to filter wind-blown snowflakes from TLS data. A key aspect of FlakeOut is a low false positive rate of \num{2.8e-4} -- an order of magnitude lower than standard filtering techniques -- which greatly reduces the number of true ground points that are incorrectly removed. This low false positive rate makes FlakeOut appropriate for applications requiring quantitative measurements of the snow surface in light to moderate blowing snow conditions. Additionally, we provide mathematical and software tools to efficiently estimate the false positive rate of filters applied for the purpose of removing erroneous data points that occur very infrequently in a dataset.