This text presents techniques for describing image textures.
Contrary to the usual practice of embedding the images to known
modelling frameworks borrowed from statistical physics or other
domains, this book deduces the Gibbs models from basic image
features and tailors the modelling framework to the images. This
approach results in more general Gibbs models than can be either
Markovian or non-Markovian and possess arbitrary interaction
structures and strengths. The book presents computationally
feasible algorithms for parameter estimation and image simulation
and demonstrates their abilities and limitations by numerous
experimental results. The book avoids too abstract mathematical
constructions and gives explicit image-based explanations of all
the notions involved.
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