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Proceedings Paper

Leveraging lidar data to aid in hyperspectral image target detection in the radiance domain
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Paper Abstract

This paper talks about the problem of nding targets in shadows. It discusses, through example and empirical analysis, why shadowed targets look dierent to a sensor. A forward modeling approach is used to describe how ground materials (i.e., targets) manifest themselves through the atmosphere and appear to the sensor in the radiance domain. Changes in illumination can be obtained by processing co-registered LiDAR point cloud data to obtain solar and sky-loading scaling factors. These scaling factors are then used in the forward model to better estimate varying illuminated targets in the scene. A target detection application was applied and showed that the modied or dynamic forward model was able to detect targets in both the open and hard shadow.

Paper Details

Date Published: 9 May 2012
PDF: 12 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839007 (9 May 2012); doi: 10.1117/12.919808
Show Author Affiliations
Emmett J. Ientilucci, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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