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A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data

IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society, v.47 no.8 pt.2, 2009년, pp.2913 - 2922  

Wei-Lwun Lu (Dept. of Comput. Sci., Univ. of British Columbia, Vancouver, BC, Canada) ,  Murphy, K.P. (Dept. of Comput. Sci., Univ. of British Columbia, Vancouver, BC, Canada) ,  Little, J.J. (Dept. of Comput. Sci., Univ. of British Columbia, Vancouver, BC, Canada) ,  Sheffer, A. (Dept. of Comput. Sci., Univ. of British Columbia, Vancouver, BC, Canada) ,  Hongbo Fu

Abstract AI-Helper 아이콘AI-Helper

Recent advances in airborne light detection and ranging (LiDAR) technology allow rapid and inexpensive generation of digital surface models (DSMs), 3-D point clouds of buildings, vegetations, cars, and natural terrain features over large regions. However, in many applications, such as flood modeling...

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