Neural network processor

Michele R. Banish D.V.M.; David B. Chenault; John S. Harchanko

doi:10.1117/12.560815

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21 October 2004 Neural network processor

Michele R. Banish D.V.M.; David B. Chenault; John S. Harchanko

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Proceedings Volume 5563, Infrared Systems and Photoelectronic Technology; (2004) https://doi.org/10.1117/12.560815
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

A Pulse Coupled Neural Network (PCNN) has been developed in order to segment image data to reduce the amount of downstream processing. This paper discusses the results of applying the PCNN algorithm to data generated by various sensor platforms. The PCNN algorithm was applied to data generated by a Long Wave Infrared Imaging Polarimeter. The PCNN correctly identified the concealed vehicles and the disturbed earth and rejected 96% of the remaining pixels because they had no information content. Next, the results of applying the PCNN algorithm to noisy infrared seeker data are presented. The PCNN correctly idnetified the target even though the background was quite noisy. Finally, the PCNN algorith was applied to images containing solar glint. It correctly passed only 3& of the pixels to the downstream target/glint decision algorithm. To obtain maximum data throughput, the PCNN can be implemented in hardware.

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Michele R. Banish D.V.M., David B. Chenault, and John S. Harchanko "Neural network processor", Proc. SPIE 5563, Infrared Systems and Photoelectronic Technology, (21 October 2004); https://doi.org/10.1117/12.560815

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