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Integration of multi-sensor data for landscape modeling using a region-based approach

机译:使用基于区域的方法集成多传感器数据以进行景观建模

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The increased availability of multi-sensor data, and elevation information in particular, leads to the need of advanced processing methods. In the context of landscape modeling tasks, we concentrate on one central component, the extraction of terrain surface from a Digital Surface Model (DSM). In contrast to conventional mathematical grey value morphology approaches (filtering methods) or to stochastical procedures, we propose an alternative methodology for this task by applying a region-based and multi-scale approach. It consists of segmentation and follow-up fuzzy logic classification based on several features derived from elevation and multi-spectral image data. The satisfying results obtained with a multi-sensor as well as with other datasets show the applicability of the approach.
机译:多传感器数据(尤其是海拔信息)可用性的提高,导致需要先进的处理方法。在景观建模任务的上下文中,我们集中于一个中心组件,即从数字表面模型(DSM)中提取地形表面。与传统的数学灰度值形态学方法(滤波方法)或随机程序相反,我们通过应用基于区域的多尺度方法,为该任务提出了一种替代方法。它由基于高程和多光谱图像数据的多个特征的分割和后续模糊逻辑分类组成。通过多传感器以及其他数据集获得的令人满意的结果表明了该方法的适用性。

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