This paper demonstrates the combination of lidar and passive polarimetric infrared imaging for object detection and classification. Lidar imaging characterizes reflective properties and provides high-resolution 3-D spatial information, and passive imaging offers faster imaging capabilities of large scenes. A cooperative imaging approach improves the imaging process by exploiting polarimetric features of hidden objects and cueing only the anomalous regions for further interrogation. Then, features from each sensor are combined for object classification. A demonstrator is assembled and utilized to evaluate the hybrid approach in an outdoor environment. The adaptive scanning technique reduces lidar scan time by 99%, locates the hidden object among the top areas cued, and outperforms single modality classification accuracy by over 20%. The demonstration verifies that hybrid lidar and passive polarimetric imaging is applicable for the classification of objects hidden in a large scene.
Demonstration of hybrid lidar and passive polarimetric infrared imaging
Signal Processing, Sensor/Information Fusion, and Target Recognition XXX ; 2021 ; Online Only,Florida,United States
Proc. SPIE ; 11756
2021-04-12
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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