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11 April 2008 The impact of spatio-temporal focal plane array nonuniformity noise on target search and identification performance
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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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard L. Espinola, Patrick O'Shea, Jason G. Zeibel, and Joseph P. Reynolds "The impact of spatio-temporal focal plane array nonuniformity noise on target search and identification performance", Proc. SPIE 6941, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 69410L (11 April 2008);


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