The ability to detect and identify camouflaged targets is critical in combat environments. Hyperspectral and Multispectral cameras allow a soldier to identify threats more effectively than traditional RGB cameras due to both increased color resolution and ability to see beyond visible light. Static imagers have proven successful, however the development of video rate imagers allows for continuous real time target identification and tracking. This paper presents an analysis of existing anomaly detection algorithms and how they can be adopted to video rates, and presents a general purpose semisupervised real time anomaly detection algorithm using multiple frame sampling.

Date Published: 21 May 2015
PDF: 10 pages
Proc. SPIE 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 94720Q (21 May 2015); doi: 10.1117/12.2177161

Published in SPIE Proceedings Vol. 9472:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI
Miguel Velez-Reyes; Fred A. Kruse, Editor(s)