Quality assessment of image matchers for DSM generation -- a comparative study based on UAV images
This work provides a comparative analysis of image matchers for DSM generation, which is incremental but useful for practitioners in photogrammetry and remote sensing seeking to choose appropriate tools.
The study evaluated five commercial and public software packages for generating digital surface models (DSMs) from UAV imagery, comparing them against LiDAR and manual measurements to assess their accuracy and reliability.
Recently developed automatic dense image matching algorithms are now being implemented for DSM/DTM production, with their pixel-level surface generation capability offering the prospect of partially alleviating the need for manual and semi-automatic stereoscopic measurements. In this paper, five commercial/public software packages for 3D surface generation are evaluated, using 5cm GSD imagery recorded from a UAV. Generated surface models are assessed against point clouds generated from mobile LiDAR and manual stereoscopic measurements. The software packages considered are APS, MICMAC, SURE, Pix4UAV and an SGM implementation from DLR.