论文标题
稀疏驱动的数字地形模型提取
Sparsity-driven Digital Terrain Model Extraction
论文作者
论文摘要
我们在这里介绍了自动数字地形模型（DTM）提取方法。提出的稀疏驱动的DTM提取器（SD-DTM）将高分辨率的数字表面模型（DSM）作为输入，并使用变分框架构建高分辨率DTM。为了获得准确的DTM，提出了一种迭代方法，以最大程度地减少目标变异成本函数。 SD-DTM的精度显示在现实世界的DSM数据集中。我们通过说明性地形类型的残留图在视觉和定量图上显示了该方法的效率和有效性。
We here introduce an automatic Digital Terrain Model (DTM) extraction method. The proposed sparsity-driven DTM extractor (SD-DTM) takes a high-resolution Digital Surface Model (DSM) as an input and constructs a high-resolution DTM using the variational framework. To obtain an accurate DTM, an iterative approach is proposed for the minimization of the target variational cost function. Accuracy of the SD-DTM is shown in a real-world DSM data set. We show the efficiency and effectiveness of the approach both visually and quantitatively via residual plots in illustrative terrain types.
