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.