1. A method for determining the probability of a human observer correctly performing a visual discrimination task based on a visual display of a dynamic image stream or movie, comprising: an imaging system configured to determine a number of resolvable cycles needed by the human observer for a fifty percent probability of discrimination task completion as a V 50 value given a set of targets in a static image perception experiment; use the determined V 50 value with a resolvable cycles value V of the target set from the movie in an empirical target transfer probability function to calculate probability values P ∞ of correctly performing the visual discrimination task of a target at a given instance in time within the movie, wherein the visual discrimination task is based on the number of resolvable cycles needed by the human observer for a fifty percent probability of discrimination task completion for performing the same visual discrimination task of the same targets in the static image given an infinite amount of time; measure calibration constants A and B from the static image perception experiment and encompassing the target set and clutter level of the movie; modify the P ∞ values by a time limited search equation based on an actual time in the movie in seconds, an experimental time delay associated with experimental set up, and a mean time to perform the visual discrimination task, wherein the mean time to perform the visual discrimination task is based on the P ∞ values and the measured calibration constants A and B; and determining the probability of a human observer correctly performing a visual discrimination task based on the modified P∞.