A mathematical morphology-based multi-level filter of LiDAR data for generating DTMs

Light detecting and ranging (LiDAR) technology has become an effective way to generate high-resolution digital terrain models (DTMs). To generate DTMs, point measurements from non-ground features, such as buildings, vegetation and vehicles, have to be identified and removed while preserving the terrain points. This paper proposes an efficient mathematical morphology-based multi-level filter to generate DTMs from airborne LiDAR data. Preliminary non-ground points are first identified with the characteristics of the multi-echo airborne LiDAR data. The localized mathematical morphology opening operations are then immediately applied to the remaining points. By gradually increasing the window size of the filter and using a dynamic critical gradient threshold, the non-ground points are removed, while the ground points are preserved. Eight samples were chosen from eight sites provided with the ISPRS Commission III, Working Group 3, to evaluate the accuracy of our algorithm. Both the qualitative and quantitative experiment analyses show that our morphology-based multi-level filter method achieves promising results, not only in flat urban areas but also in rural areas, especially in preserving complex terrain details, while non-ground spatial objects are removed.