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Proceedings Paper

Optical image correlation using high-speed multiple quantum well spatial light modulators
Author(s): Keith Kang; Jeffry S. Powell; Richard D. Stack; Charles G. Garvin; John Alfred Trezza; James C. Kirsch; Brian K. Jones
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Paper Abstract

We review GaAs Fabry-Perot vertical cavity multiple quantum well (MQW) spatial light modulators (SLMs) developed at Sanders, a Lockheed Martin Company, and demonstrate their use in optical image correlation. These MQW SLMs are reflective- mode modulators using electrically-tunable absorption to modulate the reflected intensity. The operation of the MQW SLMs with a newly-developed Labview graphical user interface is described. A compact Vander-Lugt image correlator is described which was configured using MQW SLMs: binary 128 X 128 pixel image input with a binary filter plane. In addition, the architecture of 8-bit gray-scale MQW-SLM module developed at Sanders is discussed. The performance of the image correlator was characterized using amplitude-encoded binary phase-only filters and various test targets including test imagery supplied by US Army AMCOM, and is compared with simulations for peak-to-secondary efficiencies on these data. Finally, high-speed (250,000 frames per second) target recognition of 128 X 128 pixels binary input imagery is demonstrated.

Paper Details

Date Published: 9 March 1999
PDF: 11 pages
Proc. SPIE 3715, Optical Pattern Recognition X, (9 March 1999); doi: 10.1117/12.341289
Show Author Affiliations
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)
Charles G. Garvin, Sanders, A Lockheed Martin Co. (United States)
John Alfred Trezza, Sanders, A Lockheed Martin Co. (United States)
James C. Kirsch, U.S. Army Aviation and Missile Command (United States)
Brian K. Jones, U.S. Army Aviation and Missile Command (United States)


Published in SPIE Proceedings Vol. 3715:
Optical Pattern Recognition X
David P. Casasent; Tien-Hsin Chao, Editor(s)

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