Texture modelling by discrete distribution mixtures

Authors:
J. Grim;M. Haindl
Affiliations:
Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, P.O. BOX 18, 18208 Prague 8, Czech Republic;Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, P.O. BOX 18, 18208 Prague 8, Czech Republic
Venue:
Computational Statistics & Data Analysis
Year:
2003

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Abstract

A new method of texture modelling based on discrete distribution mixtures is proposed. Unlike some alternative approaches the statistical properties of textures are modelled by a discrete distribution mixture of product components. The univariate distributions in the products are represented in full generality by vectors of probabilities without any constraints. The texture analysis is made in the original quantized grey level coding. An efficient texture synthesis is based on easy computation of arbitrary conditional distributions from the model. We include several successful monospectral texture applications of the method to demonstrate the advantages and weak points of the presented approach.