Iterative multi-scale filter based on morphological opening by reconstruction for LiDAR urban data

Aimed at the maximum window size problem of LiDAR morphological method on unknown region, a morphological filter of iterative multi-scale opening by reconstruction (IMORF) was proposed on the basis of traditional morphological filtering algorithms. Multi-scale opening by reconstruction (MORF) was utilized to get maximum window size automatically, which can help user settle the suitable window size problem of unknown region. MORF was used iteratively to settle the classification error of the low objects that were nearby high and large objects. The experimental results for ISPRS urban data show that IMORF can classify terrain and off-terrain points effectively, and the mean of TypeⅠ, Type Ⅱand total error are 3.10%, 6.05% and 4.11% respectively. Compared with other traditional filtering methods,the mean of Type ⅠError and Total Error of IMORF are minimum with Type ⅡError increased not obviously.