Parsimonious texture synthesis using binomial linear prediction

An unsupervised texture synthesis method operating in a dimensionally small parameter space is presented. It consists of two stages. In the first stage, the morphological structure of a given prototype is reproduced using an hard limited Gaussian random field. The second stage is a simple low pass filter for texture reconstruction from a binary input. The model identification process is described and synthetic texture examples are reported.