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Image Analysis, Random Fields and Dynamic Monte Carlo Methods : a Mathematical Introduction /

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The book is mainly concerned with the mathematical foundations of Bayesian image analysis and its algorithms. This amounts to the study of Markov random fields and dynamic Monte Carlo algorithms like sampling, simulated annealing and stochastic gradient algorithms. The approach is introductory and e...

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Bibliographic Details
Main Author: Winkler, Gerhard
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 1995.
Series:Applications of Mathematics, Stochastic Modelling and Applied Probability ; 27.
Subjects:
Mathematics.
Medical radiology.
Software engineering.
Computer simulation.
Optical pattern recognition.
Distribution (Probability theory)
Radiology, Medical.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:The book is mainly concerned with the mathematical foundations of Bayesian image analysis and its algorithms. This amounts to the study of Markov random fields and dynamic Monte Carlo algorithms like sampling, simulated annealing and stochastic gradient algorithms. The approach is introductory and elemenatry: given basic concepts from linear algebra and real analysis it is self-contained. No previous knowledge from image analysis is required. Knowledge of elementary probability theory and statistics is certainly beneficial but not absolutely necessary. The necessary background from imaging is sketched and illustrated by a number of concrete applications like restoration, texture segmentation and motion analysis.
Item Description:Electronic resource.
Physical Description:1 online resource (xiv, 324 pages 59 illustrations)
ISBN:9783642975226 (electronic bk.)
3642975224 (electronic bk.)
ISSN:0172-4568 ;