A new method of colour texture modelling based on Gaussian distribution mixtures is discussed. We estimate the local statistical properties of the monospectral version of the target texture in the form of a Gaussian mixture of product components. The synthesized texture is obtained by means of a step-wise prediction of the texture image. In order to achieve a realistic colour texture image and to avoid possible loss of high-frequency details we use optimally chosen pieces of the original colour source texture in the synthesis phase. In this sense the proposed texture modelling method can be viewed as a statistically controlled sampling. By using multispectral or mutually registered BTF texture pieces the method can be easily extended also for these textures.