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29 April 2010 Automatic forest canopy removal algorithm for underneath obscure target detection by airborne lidar point cloud data
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Abstract
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 underneath 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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Li-Der Chang, K. Clint Slatton, Vivek Anand, Pang-Wei Liu, Heezin Lee, and Michael V. Campbell "Automatic forest canopy removal algorithm for underneath obscure target detection by airborne lidar point cloud data", Proc. SPIE 7664, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV, 766424 (29 April 2010); https://doi.org/10.1117/12.849822
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