Abstract
This paper describes a software simulation environment for controlled image processing research. 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 superresolution 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.
Original language | English (US) |
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Pages (from-to) | 422-433 |
Number of pages | 12 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 1569 |
DOIs | |
State | Published - Oct 1 1991 |
Event | Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision 1991 - San Diego, United States Duration: Jul 21 1991 → … |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering