<title>Intelligent sensors research using pulse-coupled neural networks for focal plane image processing</title>

Abstract

An important difference between biological vision systems and their electronic counterparts is the large number of feedback signals controlling each aspect of the image collection process. For every forward path of information in the brain, from sensor to comprehension, there appears to be several neural bundles which send information back to the sensor to modify the way the information is collected. In this paper we will examine the role of such feedback signals and suggest algorithms for intelligent processing of images directly on the focal plane, using feedback. We consider first what form these signals might take and how they can be used to implement functions common to conventional image processing with the objective of moving the computation out of the digital domain and place much of its on the focal plane, or analog processing close to the focal plane. While this work falls under the general heading of artificial neural networks, it goes beyond the static processing of signals suggested by the McCulloch and Pitts model of the neuron and the Laplacian image processing suggested by Carver Mead by including the dynamics of temporal encoding in the analysis process.