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Proceedings Paper

Artificial scenes and simulated imaging
Author(s): Stephen E. Reichenbach; Stephen K. Park; Rachel Alter-Gartenberg; Zia-ur Rahman
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Paper Abstract

A software simulation environment for controlled image processing research is described. The simulation is based on a comprehensive model of the end-to-end imaging process that accounts for statistical characteristics of the scene, image formation, sampling, noise, and display reconstruction. The simulation uses a stochastic process to generate super-resolution digital scenes with variable spatial structure and detail. The simulation of the imaging process accounts for the important components of digital imaging systems, including the transformation from continuous to discrete during acquisition and from discrete to continuous during display. This model is appropriate for a variety of problems that involve image acquisition and display including system design, image restoration, enhancement, compression, and edge detection. By using a model-based simulation, research can be conducted with greater precision, flexibility, and portability than is possible using physical systems and experiments can be replicated on any general-purpose computer.

Paper Details

Date Published: 1 October 1991
PDF: 12 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48399
Show Author Affiliations
Stephen E. Reichenbach, Univ. of Nebraska/Lincoln (United States)
Stephen K. Park, College of William and Mary (United States)
Rachel Alter-Gartenberg, Old Dominion Univ. (United States)
Zia-ur Rahman, Science and Technology Corp. (United States)

Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)

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