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Background Aviation system designers and evaluators frequently need to know how visible a target, a display element, or an image compression artifact will be over a range of conditions. Sometimes psychophysical measurements can answer this question, but often a computational model is what the designer or system engineer really needs, because the system is not yet realized or the conditions are too numerous. Objectives The goal of this program is to develop computational models which take as input computer images or video sequences of such images, and give as output the probability that an observer can see the difference between a pair of such images or sequences or the probability that specific targets are detectable in such images. Approach The basic approach to the discrimination problem is to obtain discrimination data and then develop and calibrate the models so they account for the data. Biological vision science as well as psychophysical measurements guides the model development. While the discrimination models are intended to reflect the limitations of sensory processing, target detection involves the selection of target features as a function of the image content. Techniques will be further developed to examine the learning of target features, to identify observer target templates, and to predict detection performance in noisy or cluttered images when these processes become important. Level 3 Milestones FY98 Contrast-gain control visibility model. Points of Contact
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