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

Emmett J. Ientilucci

doi:10.1117/12.919808

9 May 2012 Leveraging lidar data to aid in hyperspectral image target detection in the radiance domain

Emmett J. Ientilucci

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 839007 (2012) https://doi.org/10.1117/12.919808
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

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.

Citation Download Citation

Emmett J. Ientilucci "Leveraging lidar data to aid in hyperspectral image target detection in the radiance domain", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 839007 (9 May 2012); https://doi.org/10.1117/12.919808

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