This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

About the Author

Xavier Descombes is currently research director at INRIA (French research institute dedicated to digital science and technology). His research interests include Markov random fields, stochastic geometry and stochastic modeling in image processing.

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