Recent developments in infrared focal plane array technology have led to the wide use of staring sensors in many tactical
scenarios. With all of its advancements, however, several noise sources remain present to degrade imagery and impede
performance. Fixed pattern noise, arising from detector nonuniformities in focal plane arrays, is a noise source that can
severely limit infrared imaging system performance. In addition, temporal noise, arising from frame to frame
nonuniformities, can further hinder the observer from perceiving the target within the tactical scene and performing a
target acquisition task.
In this paper, we present a new method of simulating realistic spatial and temporal noise effects, derived from focal
plane array statistics, on infrared imagery, and study their effect on the tasks of search and identification of a tank
vehicle. In addition, we assess the utility of bad pixel substitution as a possible correction algorithm to mitigate these
effects. First, tank images are processed with varying levels of fixed pattern and temporal noise distributions with
differing percentage of highly noisy detectors lying outside the operability specification. Then, a series of controlled
human perception experiments are performed using trained observers tasked to identify and search for tank targets,
respectively, through the combinations of noise. Our results show promise for a relaxation of the operability
specification in focal plane array development without severe degradation in task performance.