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14 May 2018 Anomaly detection of passive polarimetric LWIR augmented LADAR
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It is known that LADAR imaging can characterize reflective properties of a scene and provide high resolution threedimensional spatial information useful for target classification; however, scanning and processing high resolution LADAR data is extremely time and computational resource consuming. In remote sensing applications, polarization sensitive imagery can improve target-clutter discrimination of man-made objects in a natural background and anomaly detection algorithms have been shown to accurately identify areas of interest in low resolution imagery. In this paper, we investigate the possibility of enabling passively augmented LADAR for target detection by utilizing polarimetric thermal imagery to cue high resolution LADAR scans of anomalous regions of a scene. A statistical outlier detection algorithm is explored with features extracted from passive polarimetric LWIR imagery collected on an outdoor range under various conditions. The data collection process and products are discussed as well as the performance of anomaly detection algorithms for LADAR cueing. In both data collection and image processing, foliage penetration of partially hidden targets is considered. Data analysis shows polarization information of paired systems improves true positive rate and target detection rate with an acceptable false positive rate while greatly reducing LADAR scan time. As a result, a spatial clustering and anomaly ranking system is introduced to prioritize the most likely anomaly among multiple detections; minimizing time consumed performing LADAR scanning and processing.
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Jarrod P. Brown, Rodney G. Roberts, Chad M. Welsh, Darrell B. Card, and Christian K. Keyser "Anomaly detection of passive polarimetric LWIR augmented LADAR", Proc. SPIE 10655, Polarization: Measurement, Analysis, and Remote Sensing XIII, 106550U (14 May 2018);

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