Stochastic Geometry for Image Analysis

Contributor(s):

Descombes, Xavier [editor.]

Material type:

TextLanguage: 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.

Item type:

Textual

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	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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