Author: Rideaux, Reuben; West, Rebecca K.; Bex, Peter J.; Mattingley, Jason B.; Harrison, William J.
Title: Spatial structure, phase, and the contrast of natural images Cord-id: nb7r5e79 Document date: 2021_6_17
ID: nb7r5e79
Snippet: The sensitivity of the human visual system is thought to be shaped by environmental statistics. A major endeavour in visual neuroscience, therefore, is to uncover the image statistics that predict perceptual and cognitive function. When searching for targets in natural images, for example, it has recently been proposed that target detection is inversely related to the spatial similarity of the target to its local background. We tested this hypothesis by measuring observers’ sensitivity to targ
Document: The sensitivity of the human visual system is thought to be shaped by environmental statistics. A major endeavour in visual neuroscience, therefore, is to uncover the image statistics that predict perceptual and cognitive function. When searching for targets in natural images, for example, it has recently been proposed that target detection is inversely related to the spatial similarity of the target to its local background. We tested this hypothesis by measuring observers’ sensitivity to targets that were blended with natural image backgrounds. Importantly, targets were designed to have a spatial structure that was either similar or dissimilar to the background. Contrary to masking from similarity, however, we found that observers were most sensitive to targets that were most similar to their backgrounds. We hypothesised that a coincidence of phase-alignment between target and background results in a local contrast signal that facilitates detection when target-background similarity is high. We confirmed this prediction in a second experiment. Indeed, we show that, by solely manipulating the phase of a target relative to its background, the target can be rendered easily visible or completely undetectable. Our study thus reveals a set of image statistics that predict how well people can perform the ubiquitous task of detecting an object in clutter.
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