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Stochastic Geometry for Image Analysis / edited by Xavier Descombes

Contributor(s): Material type: TextTextLanguage: English Series: Digital signal and image processing seriesPublication details: New Jersey : John Wiley, 2012.Description: x, 345pISBN:
  • 9781848212404
Subject(s): Other classification:
  • B2811 Q2
Summary: 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.
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Item type Current library Home library Call number Status Barcode
Textual Textual Central Science Library Central Science Library B2811 Q2 (Browse shelf(Opens below)) Available SL1558052

Includes Bibliography 325-340p.and Index 343-345p.

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.

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