Rapid anomaly detection (RAND)

摘要

A rapid anomaly detection approach with corresponding method and system to detect anomalies in scene pixels making up a hyperspectral scene, efficiently, is presented. The approach includes tailoring an approximation of an anomaly score for each scene pixel, individually, based on an “intermediate anomaly score.” The intermediate score is computed using a portion of the terms used to compute the anomaly score. Scene pixels with low intermediate anomaly scores are removed from further processing. The remaining scene pixels are further processed, including computing anomaly scores to detect anomalies in these pixels. Advantageously, examples of the RAND approach process a few terms of all scene pixels, eliminate most scene pixels, and calculate more terms on high anomaly scoring scene pixels as needed.

主权项

1. A method for detecting an anomaly in a scene pixel of a hyperspectral scene, the anomaly being a spectrum different than spectra common to a plurality of scene pixels of the hyperspectral scene, the method comprising:
in an anomaly detector provided with hyperspectral imaging data for a plurality of scene pixels of a hyperspectral scene and provided with an anomaly equation for detecting an anomaly in a scene pixel without using an a priori spectral reference, and the anomaly equation including a set of terms sorted by descending importance: for each scene pixel in the plurality of scene pixels, computing an intermediate anomaly score based on a portion of the set of terms, the remaining terms of the set are not used to compute the intermediate anomaly score and are of less importance than the terms included in the portion; comparing the intermediate anomaly scores to a threshold; identifying scene pixels having intermediate anomaly scores less than the threshold as empty scene pixels that do not include anomalies; eliminating the empty scene pixels from the plurality of scene pixels; updating the anomaly equation to include one or more of the unused terms to form an updated anomaly equation if the number of eliminated scene pixels is less than a specified fraction of a total number of scene pixels and a number of computed intermediate anomaly scores is less than a counter; for each scene pixel remaining in the plurality of scene pixels, computing an updated intermediate anomaly score using the updated anomaly equation; comparing the updated intermediate anomaly scores to an updated threshold, the updated threshold being greater in value than the threshold; identifying scene pixels having updated intermediate anomaly scores less than the updated threshold as empty scene pixels that do not include anomalies; eliminating empty scene pixels from the remaining scene pixels; for each scene pixel remaining in the plurality of scene pixels, computing a full dimension anomaly score based on the set of terms of the anomaly equation if the number of eliminated scene pixels is greater than or equal to the specified fraction of the total number of scene pixels or the number of intermediate anomaly scores computed is greater than or equal to the counter; and declaring which scene pixels include anomalies based on comparisons of the computed full dimension anomaly scores to a full dimension anomaly score threshold, the full dimension anomaly score threshold being greater in value than the threshold and the updated threshold.