Abstract
Markov/Gibbs models represent digital images as samples of Markov random fields (MRF) on finite 2D lattices with Gibbs probability distributions (GPD). Most of the known models take account of only pairwise pixel interactions. These models, studied in general form by Dobrushin [11], Averintsev [1], and Besag [3], were first applied to the images by Cross and Jain [9], Hassner and Sklansky [23], Lebedev et al. [25], Derin et al. [10], Geman and Geman [15]. Later, they were studied in numerous works (see, for instance, surveys [24, 13, 7, 28]). The models have features useful for describing and analysing image textures.
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Gimel’farb, G.L. (1997). Non-Markov Gibbs image model with almost local pairwise pixel interactions. In: Solina, F., Kropatsch, W.G., Klette, R., Bajcsy, R. (eds) Advances in Computer Vision. Advances in Computing Science. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6867-7_10
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DOI: https://doi.org/10.1007/978-3-7091-6867-7_10
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