This book develops the stochastic geometry framework for imageanalysis purpose. Two main frameworks are described: markedpoint process and random closed sets models. We derive the mainissues for defining an appropriate model. The algorithms forsampling and optimizing the models as well as for estimatingparameters are reviewed. Numerous applications, coveringremote sensing images, biological and medical imaging, aredetailed. This book provides all the necessary tools fordeveloping an image analysis application based on modern stochasticmodeling.

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Articles li�s � Stochastic Geometry for Image Analysis

Stochastic Geometry for Image Analysis

Descombes, Xavier (EDT)

Neuf(s) - Couverture rigide

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