Electrical and optical implementations of the PCNN

James C. Kirsch; Brian K. Jones; Michele Ruggiero Banish; Heggere S. Ranganath; Jesse N. Viviano

doi:10.1117/12.449332

13 November 2001 Electrical and optical implementations of the PCNN

James C. Kirsch, Brian K. Jones, Michele Ruggiero Banish, Heggere S. Ranganath, Jesse N. Viviano

Proceedings Volume 4471, Algorithms and Systems for Optical Information Processing V; (2001) https://doi.org/10.1117/12.449332
Event: International Symposium on Optical Science and Technology, 2001, San Diego, CA, United States

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.

Citation Download Citation

James C. Kirsch, Brian K. Jones, Michele Ruggiero Banish, Heggere S. Ranganath, and Jesse N. Viviano "Electrical and optical implementations of the PCNN", Proc. SPIE 4471, Algorithms and Systems for Optical Information Processing V, (13 November 2001); https://doi.org/10.1117/12.449332

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