Automatic Forest Canopy Removal Algorithm for Underneath Obscure Target Detection by Airborne LiDAR Point Cloud Data

摘要

The thermal imaging cameras can see the heat signature of people, boats, and vehicles in total darkness as well as through smoke, haze, and light fog, but not through the forest canopy. This study develops a novel algorithm to help detecting obscure targets undemeath forest canopy and mitigate the vegetation problem for those bare ground point extraction filters as well. By examining our automatically processed results with actual LiDAR data, the forest canopy is successfully removed where all obscure vehicles or buildings underneath canopy can now be easily seen. Besides, the occluded rate of forest canopy and the detailed underneath x-y point distribution can be easily obtained accordingly. This will be very useful for predicting the performance of occluded target detection with respect to various object locations.