Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Titre: Stochastic Geometry for Image Analysis (Hardcover)
�diteur: ISTE Ltd and John Wiley & Sons Inc, London
Date de parution: 2011
Langue: anglais
ISBN � 10 chiffres: 1848212402
ISBN � 13 chiffres: 9781848212404
Reliure: Hardcover
�dition: Edition originale
�tat de l'article: new

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Synopsis

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.

� propos de l?auteur

Xavier Descombes, Director of Research INRIA, EPI Ariana

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