Hybrid filtering of Lidar Data based on the Echoes

The airborne laser scanning (ALS) has become the most effective way to acquire 3D information of the earth´s surface. However, data post-processing lags far behind hardware especially the filtering algorithm. At present, most algorithms for DEM generation are based on the mutation of the elevation, and every method has its own defects. All of the existing filter algorithms are based on a priori information, so that the accuracy of the filtering is affected by the terrain fluctuation. In this paper, a new algorithm called Hybrid Filtering of Lidar Data based on the Echoes was proposed. First, we make an analysis of echo characteristic of airborne Lidar data, and propose classification schemas based on the characteristic of echo characteristic. Then we use the Pseudo Grid for segmentation and index. Furthermore, using the existing filtering algorithm to distinguish the seed point is terrain point or not. At last, we filter the cooked data. In theory, because of removing part of object point the accuracy and the efficiency must be significantly increased. Experiments show that it is effectively to eliminate most of vegetation and building points, that means, the method proposed in this paper not only can reduce the amount of computing data, but also improve the effect of filtering algorithm for eliminating the building and vegetation.