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The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data.\udAlthough many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging\udtask, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR\udpoint clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms\udof the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient\udof each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to\udcarry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working\udGroup III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to\udfiltering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes\udincluding urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively\udsmall interval. This algorithm can efficiently remove object points while preserves ground points to a great degree

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

FILTERING AIRBORNE LIDAR DATA BY AN IMPROVED MORPHOLOGICAL METHOD BASED ON MULTI-GRADIENT ANALYSIS