Anomaly detection in terrestrial hyperspectral video using variants of the RX algorithm
There is currently interest in detecting the use of chemical and biological weapons using hyperspectral sensors. Much of the research in this area assumes the spectral signature of the weapon is known in advance. Unfortunately, this may not always be the case. To obviate the reliance on a library of known target signatures, we instead view this as an anomaly detection problem. In this thesis, the RX algorithm, a benchmark anomaly detection algorithm for multi- and hyper-spectral data is reviewed, as are some standard extensions. This class of likelihood ratio test-based algorithms is generally ...
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