Leveraging Lidar Data to Aid in Hyperspectral Image Target Detection in the Radiance Domain

This paper talks about the problem of finding targets in shadows. It discusses, through example and empirical analysis, why shadowed targets look different 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 modified or dynamic forward model was able to detect targets in both the open and hard shadow.