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Automatically extracting DTM from DSM or LiDAR data by distinguishing non-ground points from ground points is an importantissue. Many algorithms for this issue are developed, however, most of them are targeted at processing dense LiDAR data, and lackthe ability of getting DTM from low resolution DSM. This is caused by the decrease of distinction on elevation variation betweensteep terrains and surface objects. In this paper, a method called two-steps semi-global filtering (TSGF) is proposed to extract DTMfrom low resolution DSM. Firstly, the DSM slope map is calculated and smoothed by SGF (semi-global filtering), which is thenbinarized and used as the mask of flat terrains. Secondly, the DSM is segmented with the restriction of the flat terrains mask. Lastly,each segment is filtered with semi-global algorithm in order to remove non-ground points, which will produce the final DTM. Thefirst SGF is based on global distribution characteristic of large slope, which distinguishes steep terrains and flat terrains. The secondSGF is used to filter non-ground points on DSM within flat terrain segments. Therefore, by two steps SGF non-ground points areremoved robustly, while shape of steep terrains is kept. Experiments on DSM generated by ZY3 imagery with resolution of 10-30mdemonstrate the effectiveness of the proposed method

AUTOMATIC EXTRACTION OF DTM FROM LOW RESOLUTION DSM BY TWOSTEPS SEMI-GLOBAL FILTERING