Abstract
Gibbs random field models describe image textures in terms of geometric structure and energy of pixel interactions. The interaction means statistical interdependence of signals, the structure is given by characteristic pixel neighbourhoods, and the energy depends on signal co- occurrences over the neighbourhoods. In translation invariant textures all the neighbourhoods have the same relative geometry. The interaction structure of such a texture is reflected in a model-based interaction map (MBIM) giving spatial distribution of the interaction energies over a large neighbourhood. We show that due to scale / orientation robustness, the MBIM allows to partition a given training sample into tiles acting as structural elements, or texels. Large-size textured images can be synthesised by replicating the training texels.
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Gimel’farb, G., Yu, L., Zhou, D. (2003). Geometric Structure and Randomness in Texture Analysis and Synthesis. In: Asano, T., Klette, R., Ronse, C. (eds) Geometry, Morphology, and Computational Imaging. Lecture Notes in Computer Science, vol 2616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36586-9_8
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DOI: https://doi.org/10.1007/3-540-36586-9_8
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