We examine how local position information of different complex scenes is represented in the visual system. A 2AFC paradigm was used to examine internal noise and sampling efficiency for three classes of stimuli: natural objects, fractal patterns and random circular patterns, all synthesized from the same set of Gabor wavelets. Each trial, a noiseless source image was presented first for 1 sec, followed by a reference image that contained a fixed amount of external position noise (s) on each element, and a target image containing additional position noise (s+Ds) under the control of a staircase. Subjects identified the image with less noise. Equivalent noise functions fitting the results indicated approximately identical internal noise but sampling efficiency that increased with predictability across image classes. This suggests a flexible position representation that compares the observed structure with prior experience.

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