Texture discrimination based on global feature alignments

Abstract

Three experiments are reported that examined the abilities of human observers to discriminate textures with identical distributions of orientation and spatial frequency. In Experiment 1, the stimuli consisted of low-pass filtered noise that was uniformly distributed and spatially isotropic. Observers were able to discriminate textures with identical image statistics when their frequencies were 1 cpd or less, but performance dropped off sharply for textures with higher frequencies. In Experiment 2, a novel procedure was employed with which it is possible to increase the high-frequency energy in the amplitude spectrum of a texture, while preserving the macroscopic alignments of its phase spectrum. The results reveal that this has little effect on performance, thus indicating that it is not spatial frequency per se that limits the abilities of observers to discriminate macroscopic texture patterns. When the phase spectra of these textures were randomly scrambled in Experiment 3, the frequency thresholds for discriminating textures reverted back to 1 cpd as was obtained in Experiment 1. These results provide strong evidence that human observers make use of two distinct procedures for discriminating patches of texture: One based on image statistics that is possible for all textures; and another based on macroscopic phase alignments that define features that are larger than 1°.