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 multiple locations in the US or from the UK, depending on stock availability.

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Titolo: Stochastic Geometry for Image Analysis (Hardcover)
Editore: ISTE Ltd and John Wiley & Sons Inc, London
Data di pubblicazione: 2011
Lingua: Inglese
ISBN 10: 1848212402
ISBN 13: 9781848212404
Rilegatura: Hardcover
Edizione: prima edizione
Condizione: new

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Riassunto

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.

Informazioni sull?autore

Xavier Descombes, Director of Research INRIA, EPI Ariana

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