On The Visual Discrimination of Self-Similar Random Textures
R.A. Rensink, Laboratory for Computational Vision, University of British Columbia, Vancouver, Canada.

In Proceedings of the IEEE Society Workshop on Computer Vision, pp. 240-242. 1987. [pdf]

Abstract

This paper examines several issues relating to the perception of self-similar random textures. (1) Relations are established between self-similar random fields, stochastic fractals, and self-similar noises. (2) Experiments on self-similar gaussian line textures show that both the similarity parameter H and the scaling ratio h influence discriminability, but do not completely govern it. (3) The empirical results are shown to be compatible with a model of texture perception based upon the set of spatial-frequency channels putatively involved in form vision.

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