DEM Generation from LIDAR Data using Morphology Filtering Methods
Yi-Chen Shao
Department of Civil Engineering, China Institute of Technology
No. 245, Academy Rd., Sec. 3, Nan-Kang District, Taipei, Taiwan 115, R.O.C.
E-mail: shaoyc@cc.chit.edu.tw
Liang-Chien Chen
Center for Space and Remote Sensing Research, National Central University
No. 300, Jung-Da Rd., Chung-li, Taiwan 320, R.O.C.
E-mail: lcchen@csrsr.ncu.edu.tw
ABSTRACT
In this paper we propose a scheme for DEM generation from LIDAR data. The scheme includes
four procedures, (1) seeds selecting, (2) control posts searching, (3) elevation reconstruction and
(4) classification. The method is based on grid model with quick and global processing for any
kind of terrain type. The main processing includes the concept of morphology filtering
algorithms. Noise removing is performed by flat structuring element and object segmentation by
H-Dome transformation. After filtering out above-ground object points, ground points can be
used to generate DEM. The test data of 8 sites with 15 samples released from ISPRS
Commission III Working Group 3 are test for the proposed method. The quantitative assessment
of the experimental results is presented and shows promising for practical applications.
1. INTRODUCTION
In the last few years, a number of filtering algorithms have been developed for DEM generation
from LIDAR data (Kraus and Pfeipfer, 1998) (Axelsson, 1999) (Vosselman and Maas, 2001).
These algorithms filter out object points and use ground points to generate DEM. In 2002,
ISPRS Commission III Working Group 3 provided 8 data sites for test of filtering algorithms to
generate DEM. In 2003, the accuracy assessment report was published (Sithole and volsselman,
2003). And in 2004, 15 samples of test data was released (ISPRS, 2004). We modify our method
proposed of Shao and Chen (2003) and test the ISPRS data. We follow the ISPRS report to
make an accuracy assessment of the processing results. The experimental results are promising
for applications.
