Title :
Range invariant anomaly detection for LWIR polarimetric imagery
Author :
Romano, Joao M. ; Rosario, Dalton S.
Author_Institution :
Dev., & Eng. Center, U.S. Army Armament Res., Picatinny Arsenal, NJ, USA
Abstract :
In this paper we present a modified version of a previously proposed anomaly detector for polarimetric imagery. This modified version is a more adaptive, range invariant anomaly detector based on the covariance difference test, the M-Box. The paper demonstrates the underlying issue of range to target dependency of the previous algorithm and offers a solution that is very easily implemented with the M-Box covariance test. Results are shown where the new algorithm is capable of identifying manmade objects as anomalies in both close and long range scenarios.
Keywords :
covariance matrices; infrared imaging; object detection; polarimetry; remote sensing; statistical testing; LWIR polarimetric imagery; M-Box covariance test; manmade object identification; range invariant anomaly detector; target dependency; Algorithm design and analysis; Clutter; Covariance matrices; Data collection; Detectors; Object recognition; LWIR; anomaly; detector; imagery; polarimetric;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop (AIPR), 2014 IEEE
Conference_Location :
Washington, DC
DOI :
10.1109/AIPR.2014.7041931