Paper
30 May 1995 Continuing developments in biologically inspired smart focal plane concepts
Author Affiliations +
Abstract
The Neuromorphic IR FPA Sensor developed by Amber Engineering, Inc., Goleta, CA for the Wright Laboratory Armament Directorate's Advanced Guidance Division, performs a Difference of Gaussians filtering function, similar to what occurs in the outer plexiform layer of the primate retinal system. This function requires a computationally intensive (digital-wise) spatial-temporal data smoothing operation, which is executed on the focal plane, at the seeker frame rate, while the image data is still in the analog domain. Implementation of analog operation provides great flexibility, not only in terms of the speed and power dissipation advantages, but also with the interface of other processes to the analog system. The fact that the human visual system is essentially based upon analog techniques helps to emphasize the point; nature has invested millions of years in the development of sensors and processing `wetware' which are highly tuned to their environment. Our goal is to take further advantage of the lessons which nature can teach us, and advance the state of the art in imaging detection and tracking by taking the next step to develop neuromorphic/corticomorphic focal plane devices. This paper will discuss some of the concepts the authors have been investigation in formulating advanced `smart' FPAs for future guided missile seeker applications.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul L. McCarley, Martin F. Wehling, and Mark A. Massie "Continuing developments in biologically inspired smart focal plane concepts", Proc. SPIE 2474, Smart Focal Plane Arrays and Focal Plane Array Testing, (30 May 1995); https://doi.org/10.1117/12.210576
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Sensors

Analog electronics

Image processing

Staring arrays

Infrared sensors

National Ignition Facility

Convolution

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