Some scenarios require performance estimation of an imaging or a computer vision system, prior to its actual operation. These occur in system design, as well as in tasks of high risk or cost. To predict the performance, we propose an image-based approach, which accounts for underlying image-formation processes, while using real image data. We give detailed description of image formation, from scene photons, to image gray-levels. This analysis includes all the optical, electrical and digital sources of signal distortion and noise.
Based on this analysis and on our access to the camera parameters, we devise a simple image-based algorithm. It transforms a baseline high quality image, to render an estimated outcome of the system we wish to operate or design. We demonstrate our approach on thermal imaging systems (infrared spectrum 3-5 microns).