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This chapter describes a procedure for evaluating imager resolution. A resolution metric is presented that predicts the effect of imager blur, noise, and sampling on the probability of correctly identifying targets. The targeting task performance (TTP) metric predicts the results of the target identification experiments described in Chapter 6. The resolution metric quantifies the ability to identify objects and, in general, to discriminate scene details.

Target acquisition task performance depends on how well information is coupled from the scene to the observer. System performance cannot be predicted without considering the characteristics of human vision. Imager noise is unimportant if it is too fine grained to bother the observer. Imager resolution is wasted if it far exceeds human acuity. Figure 7.1 shows an imager connected to a display and viewed by an observer. Observer vision is treated as a "black box." Psychophysical data are used to characterize visual thresholds and noise. The imager is evaluated by determining how well input spatial information is coupled to the human visual system.

Experimentally, resolution predicts the probability of identifying objects in a known target set. Mathematically, resolution is calculated by stimulating the imager with a broad frequency spectrum. The TTP metric is an integral of all of the spatial frequency content that exceeds visual thresholds. TTP quantifies how well input spatial information is coupled to the observer. Poor coupling reduces the probability of identifying objects. Good coupling improves the probability of identifying objects. TTP is validated by the fact that it predicts experimental object identification probabilities.

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