Detection of Unresolved and Subpixel-Scale Anomalous Objects in Hyperspectral Imagery
Abstract
Basic Research objectives of our three-year proposal include to (1) achieve an understanding of the relationship of the complexity of hyperspectral image data cubes and the degree of object anomaly from its immediate neighborhood that is detectable; (2) investigate alternative algorithms to autonomously detect and locate subpixel and unresolved anomalies in hyperspectral imagery; (3) investigate the utility of spectral bands selection of the image data cubes to improve performance and reduction of computational resources; (4) investigate the probability of detection and false-alarm rate of alternative algorithms including impact of image subpixel microdithering upon a focal plane array; and (5) investigate the efficacy of improving anomalous object detection performance if a synthetic resolution-enhancement algorithm is applied to the image data cube.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 17, 2016
- Source ID
- W911NF1510531
Entities
People
- Barry Johnson
Organizations
- Alabama A & M College
- Army Contracting Command
- Office of the Secretary of Defense