Pulse-coupled neural network sensor fusion

John L. Johnson; Marius P. Schamschula; Ramarao Inguva; H. John Caulfield

doi:10.1117/12.303682

20 March 1998 Pulse-coupled neural network sensor fusion

John L. Johnson, Marius P. Schamschula, Ramarao Inguva, H. John Caulfield

Proceedings Volume 3376, Sensor Fusion: Architectures, Algorithms, and Applications II; (1998) https://doi.org/10.1117/12.303682
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

Perception is assisted by sensed impressions of the outside world but not determined by them. The primary organ of perception is the brain and, in particular, the cortex. With that in mind, we have sought to see how a computer-modeled cortex--the PCNN or Pulse Coupled Neural Network--performs as a sensor fusing element. In essence, the PCNN is comprised of an array of integrate-and-fire neurons with one neuron for each input pixel. In such a system, the neurons corresponding to bright pixels reach firing threshold faster than the neurons corresponding to duller pixels. Thus, firing rate is proportional to brightness. In PCNNs, when a neuron fires it sends some of the resulting signal to its neighbors. This linking can cause a near-threshold neuron to fire earlier than it would have otherwise. This leads to synchronization of the pulses across large regions of the image. We can simplify the 3D PCNN output by integrating out the time dimension. Over a long enough time interval, the resulting 2D (x,y) pattern IS the input image. The PCNN has taken it apart and put it back together again. The shorter- term time integrals are interesting in themselves and will be commented upon in the paper. The main thrust of this paper is the use of multiple PCNNs mutually coupled in various ways to assemble a single 2D pattern or fused image. Results of experiments on PCNN image fusion and an evaluation of its advantages are our primary objectives.

Citation Download Citation

John L. Johnson, Marius P. Schamschula, Ramarao Inguva, and H. John Caulfield "Pulse-coupled neural network sensor fusion", Proc. SPIE 3376, Sensor Fusion: Architectures, Algorithms, and Applications II, (20 March 1998); https://doi.org/10.1117/12.303682

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