15 August 1989 Reconstructing Irregularly Sampled Images by Neural Networks
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Proceedings Volume 1077, Human Vision, Visual Processing, and Digital Display; (1989); doi: 10.1117/12.952721
Event: OE/LASE '89, 1989, Los Angeles, CA, United States
Abstract
Neural-network-like models of receptor position learning and interpolation function learning are being developed as models of how the human nervous system might handle the problems of keeping track of the receptor positions and interpolating the image between receptors. These models may also be of interest to designers of image processing systems desiring the advantages of a retina-like image sampling array.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Albert J. Ahumada, John I. Yellott, "Reconstructing Irregularly Sampled Images by Neural Networks", Proc. SPIE 1077, Human Vision, Visual Processing, and Digital Display, (15 August 1989); doi: 10.1117/12.952721; https://doi.org/10.1117/12.952721
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KEYWORDS
Receptors

Visualization

Visual system

Human vision and color perception

Image processing

Neural networks

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