Non-Markov Gibbs image model with almost local pairwise pixel interactions

  • Georgy L. Gimel’farb
Conference paper
Part of the Advances in Computing Science book series (ACS)


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.


Gray Level Interaction Structure Markov Random Field Stochastic Approximation Exponential Family 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag/Wien 1997

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  • Georgy L. Gimel’farb

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