Ian Matthew Robinson

US Patent:

20140010471, Jan 9, 2014

Filed:

Jul 5, 2012

Appl. No.:

13/542181

Inventors:

Bradley A. FLANDERS - Whittier CA, US
Ian S. ROBINSON - Redondo Beach CA, US

Assignee:

RAYTHEON COMPANY - Waltham MA

International Classification:

G06K 9/40

US Classification:

382255

Abstract:

In accordance with various aspects of the disclosure, a system, a method, and computer readable medium having instructions for processing images is disclosed. For example, the method includes receiving an input datacube from which an input image is derived. The input datacube is transformed into a residual datacube by projecting out basis vectors from each spatial pixel in the input datacube, the residual datacube being used to derive a residual image. A statistical parameter value for samples of each focal plane pixel in the residual image is determined. Anomalous focal plane pixels are identified based upon a comparison of the determined statistical parameter value with the respective determined statistical parameter values of remaining focal plane pixels. Another comparison of residual values for each scanned sample of the identified anomalous focal plane pixels with values of corresponding scanned samples in the input datacube is performed.

US Patent:

20160055654, Feb 25, 2016

Filed:

Aug 25, 2014

Appl. No.:

14/467272

Inventors:

Bradley A. Flanders - Whittier CA, US
Anthony M. Sommese - Northport NY, US
Ian S. Robinson - Redondo Beach CA, US

International Classification:

G06T 7/40

Abstract:

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.