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Proceedings Paper

Electrical and optical implementations of the PCNN
Author(s): James C. Kirsch; Brian K. Jones; Michele Ruggiero Banish; Heggere S. Ranganath; Jesse N. Viviano
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Paper Abstract

Pulse couple neural networks (PCNN) have demonstrated some very desirable properties. Chief among these is its ability to segment images very rapidly and very well. This capability has been demonstrated with many different types of imagery including synthetic aperture radar imagery, infrared imagery, optical correlator output imagery, and medical diagnostic imagery. Most of the implementations of this network have been done in software. Several attempts have been made to build electronic versions with varying degrees of success. Recently, an Army Phase II SBIR was awarded to incorporate a PCNN in a smart detector for both military and medical applications. One of the inherent difficulties in building an electronic PCNN is implementing the linking field that is the strength of this network. An optical implementation of the linking would potentially simplify the problem and take advantage of the inherent parallelism of optics. The resultant hardware could be simpler and faster than previous implementations making it an attractive solution. This paper will discuss the current status of the SBIR program, and present possible optical implementations using recently developed Vertical Cavity Surface Emitting Laser arrays.

Paper Details

Date Published: 13 November 2001
PDF: 12 pages
Proc. SPIE 4471, Algorithms and Systems for Optical Information Processing V, (13 November 2001); doi: 10.1117/12.449332
Show Author Affiliations
James C. Kirsch, U.S. Army Aviation and Missile Command (United States)
Brian K. Jones, U.S. Army Aviation and Missile Command (United States)
Michele Ruggiero Banish, SY Technology, Inc. (United States)
Heggere S. Ranganath, Univ. of Alabama in Huntsville (United States)
Jesse N. Viviano, U.S. Army Aviation and Missile Command (United States)


Published in SPIE Proceedings Vol. 4471:
Algorithms and Systems for Optical Information Processing V
Bahram Javidi; Demetri Psaltis, Editor(s)

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