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Proceedings Paper

Detection and processing of hyperspectral imaging data with quantum-well devices
Author(s): Thomas P. McElwain; Keith Kang; Jeffry S. Powell; Richard D. Stack; John Alfred Trezza
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Paper Abstract

The effectiveness of utilizing spatial light modulators (SLMs), developed at Sanders, for reducing some of the critical bottlenecks inherent within the Hyperspectral Imaging (HSI) chain will be presented. Specifically, the more common classification, detection, and endmember selection algorithm used in HSI, which are suitable for optical implementation, are presented here. These algorithms were reformulated for implementation on a compact Vander- Lugt correlator based on Sanders' multi-level quantum well (MQW) spatial light modulator (SLM). Sanders devices are GaAs Fabry-Perot vertical cavity multiple quantum well (MQW) SLMs consisting of MQW optical chips flip-chip bonded to Si/CMOS driver circuitry. Details of the reformation of Pixel Purity Index, an endmember selection algorithm, to the optical correlator is presented as well as a projection of its performance based on software simulations. In addition, hardware results are presented for Spectral Angle Mapper based on a Vander-Lugt implementation using Sanders 128 X 128 binary SLMs. An opto-electronic hyperspectral workstation accelerator is proposed which is based on a Vander-Lugt correlator using Sanders' MQW-SLMs and FPGA- based compute nodes and has the capability of 6.4 Million 1D correlations per second for HSI endmember selection, classification and detection.

Paper Details

Date Published: 29 June 2000
PDF: 12 pages
Proc. SPIE 4041, Visual Information Processing IX, (29 June 2000); doi: 10.1117/12.390477
Show Author Affiliations
Thomas P. McElwain, Sanders, A Lockheed-Martin Co. (United States)
Keith Kang, Sanders, A Lockheed-Martin Co. (United States)
Jeffry S. Powell, Sanders, A Lockheed-Martin Co. (United States)
Richard D. Stack, Sanders, A Lockheed-Martin Co. (United States)
John Alfred Trezza, Sanders, A Lockheed-Martin Co. (United States)

Published in SPIE Proceedings Vol. 4041:
Visual Information Processing IX
Stephen K. Park; Zia-ur Rahman, Editor(s)

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