Detection and scaling of statistical differences between visual textures

Stochastically textured patterns were used to investigate the sensitivity of Ss to differences in the statistical distributions of locally defined properties of element density and shape. The results of the study indicate that when the textures were most structured, in terms of their variance, Ss were most accurate at detecting dissimilarities between pairs of patterns. Ss also rated the similarity of the statistical distributions of elements of patterns differing in local properties. Multidimensional scaling analysis of the ratings showed two dimensions, representing monotonic orderings of the stimuli.