Figure 1.

“Dead leaves'' in natural images. (A) Twelve circular patches of elliptical primitives are laid over a natural image at three eccentricities from the centre on each cardinal axis. The radius of the patch increases with eccentricity. Each ellipse takes on the greyscale value of the image pixel at its centre, matching the dead leaves patches in space-averaged luminance and contrast. On fixating the cross in the centre of the image, you may note that some patches are harder to discriminate than others—thus local image properties modulate crowding. In the experiment, observers reported the location of a single patch of dead leaves relative to fixation (4AFC). Our analysis aimed to determine the local image properties in the underlying natural image that are correlated with discrimination performance. (B) Seven image statistics were computed at four Gaussian-weighted scales (here, the finest scale, σ = 2 pixels, is shown). These statistics are used to predict performance on the discrimination task, along with task parameters such as patch size.