Digital surface model (DSM) generation is one of the fundamental issues in photogrammetry and the mapping industry. This paper provides a comprehensive assessment of state‐of‐the‐art image matchers using nine open‐source and commercial software packages on aerial and unmanned aerial vehicle (UAV) images and five software packages on spaceborne images. Two datasets provide an update on DSM generation software for both airborne and spaceborne data: a 5 × 5 UAV image block with high‐precision models; and a WorldView‐1 stereopair with lidar reference data. To understand the performance of the image matchers, accuracy analysis is additionally performed on five selected ground objects. The tested image matchers adopting hierarchical semi‐global matching fitted the reference DSM better, thus yielding better accuracy.

中文翻译：

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使用机载和星载图像评估密集图像匹配器以生成数字表面模型的更新

数字表面模型（DSM）的生成是摄影测量和制图行业中的基本问题之一。本文使用在航空和无人飞行器（UAV）图像上的9个开源和商业软件包以及在星载图像上的5个软件包对最新的图像匹配器进行了全面评估。两个数据集提供了机载和星载数据的DSM生成软件的更新：具有高精度模型的5×5 UAV图像块；以及带有激光雷达参考数据的WorldView-1立体对。为了了解图像匹配器的性能，还对五个选定的地面对象进行了精度分析。经过测试的采用分层半全局匹配的图像匹配器可以更好地拟合参考DSM，从而产生更高的准确性。