15 November 2007 Filter algorithm for airborne LIDAR data
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Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 67870J (2007) https://doi.org/10.1117/12.748474
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
Airborne laser scanning data has become an accepted data source for highly automated acquisition of digital surface models(DSM) as well as for the generation of digital terrain models(DTM). To generate a high quality DTM using LIDAR data, 3D off-terrain points have to be separated from terrain points. Even though most LIDAR system can measure "last-return" data points, these "last-return" point often measure ground clutter like shrubbery, cars, buildings, and the canopy of dense foliage. Consequently, raw LIDAR points must be post-processed to remove these undesirable returns. The degree to which this post processing is successful is critical in determining whether LIDAR is cost effective for large-scale mapping application. Various techniques have been proposed to extract the ground surface from airborne LIDAR data. The basic problem is the separation of terrain points from off-terrain points which are both recorded by the LIDAR sensor. In this paper a new method, combination of morphological filtering and TIN densification, is proposed to separate 3D off-terrain points.
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Qi Li, Qi Li, Hongchao Ma, Hongchao Ma, Jianwei Wu, Jianwei Wu, Liqiao Tian, Liqiao Tian, Feng Qiu, Feng Qiu, } "Filter algorithm for airborne LIDAR data", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67870J (15 November 2007); doi: 10.1117/12.748474; https://doi.org/10.1117/12.748474
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