The core of the system we developed is a resolution-independent, acuity-based blur algorithm. This allows us to import an image at any resolution (eg, 72 dots per inch for display on a screen, or 300 dots per inch for high-resolution printing) and set parameters that inform the system of the real-world size of the scene represented in the image, the viewing distance, and the view angle. The blur algorithm then calculates the amount of pixel blur needed to simulate a given acuity, taking into account all these parameters, along with calibration data that define the baseline relationship between visual acuity and pixel blur. These data were created by observing different lines of properly sized, randomized Snellen letters in pairs so that one line is slightly smaller than the other. Pixel blur was applied to them until the larger line was just legible and the smaller line was not. Eccentricity fall-off was simulated using this blur algorithm and the values in the Table. However, the system is designed so that it is very easy to switch to other data sets for other purposes. The core project file, along with a sample image and brief instructions, are available on request from the authors.