This paper describes the performance of an image capture simulator. The general model underlying the simulator assumes that a) the image capture device contains multiple classes of sensors with different spectral sensitivities and b) that each sensor responds linearly to light intensity over most of its operating range. We place no restrictions on the number of sensor classes, their spectral sensitivities, or their spatial arrangement. The input to the simulator is a set of narrow-band images of the scene taken with a custom-designed hyperspectral camera system. The parameters for the simulator are the number of sensor classes, the sensor spectral sensitivities, the noise statistics and number of quantization levels for each sensor class, the spatial arrangement of the sensors, and the exposure duration. The output of the simulator is the raw image data that would have been acquired by the simulated image capture device. To test the simulator, we acquired images of the same scene both with our hyperspectral camera and with a calibrated Kodak DCS-200 digital color camera. We used the simulator to predict the DCS-200 output from the hyperspectral data. The agreement between simulated and acquired images validated the image capture response model, the spectral calibrations, and our simulator implementation. We believe the simulator will provide a useful tool for understanding the effect of varying the design parameters of an image capture device.