1. A spectral anomaly detection method, comprising the steps of: generating a panchromatic image; segmenting the panchromatic image into a dark cluster data set and a bright cluster data set; separately performing principal component analysis of the dark cluster data set, the bright cluster data set, and a border cluster data set to produce a plot of principal components for the dark cluster data set, the bright cluster data set, and the border cluster data set, wherein the border cluster data set comprises a data set between the bright cluster data set and dark cluster data set; applying an anomaly detection algorithm to an adaptively selected subset of principal components for the dark cluster data set, the bright cluster data set, and border cluster data set to produce a dark cluster detection score, a bright cluster detection score, and a border cluster detection score; applying a separate detection thresholding algorithm to each of the dark cluster detection score, bright cluster detection score, and border cluster detection score; and combining the results of the detection thresholding algorithms in a single detection plane.