Figure 2.

(a) Signal and template used for simulating the letter detection task with an ideal-observer model. The white haze shows the extent of the intrinsic spatial uncertainty of the model observer for M = 1,000 and spatial extent (d) equal to 64. The template used by the model is shown in green. The letter stimulus is shown in red. The overlapping regions are shown in yellow, (b) Classification images from the ideal-observer model performing the letter detection task at an accuracy level of 75% correct: first column, classification-image and spatial-extent estimations for the medium spatial uncertainty condition (M = 1,000, d = 32); second column, classification-image and spatial-extent estimations for a medium spatial uncertainty condition (M = 250, d = 32), which has the same spatial density of templates as the high-uncertainty condition; third column, classification-image and spatial-extent estimations for the high spatial uncertainty condition (M = 1,000, d = 64). The error functions of spatial-extent estimations are labeled by the putative template used for the estimation. The value of d at the minimum of each curve represents the estimated spatial extent and is marked by the position of the corresponding label. The green curves were obtained using the model’s template, the red curves were obtained using the stimulus letter as the template, and the black curves were obtained using letters that resembled (in terms of rms distance) the model template.