Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction

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Gerhard Winkler

Image Analysis, Random Fields and Markov Chain Monte Carlo Methods

A Mathematical Introduction

Gerhard Winkler

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English

Springer Verlag
01 June 2006

Mathematics & Sciences; Probability & statistics; Maths for computer scientists; Image processing

Series: Stochastic Modelling and Applied Probability

""This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo methods commonly used...

This book will be useful, especially to researchers with a strong background in probability and an interest in image analysis. The author has presented the theory with rigor!he doesn't neglect applications, providing numerous examples of applications to illustrate the theory."" -- MATHEMATICAL REVIEWS

By: Gerhard Winkler
Imprint: Springer Verlag
Country of Publication: Germany
Edition: 2nd Revised edition
Volume: v. 27
Dimensions: Height: 235mm, Width: 155mm, Spine: 23mm
Weight: 807g
ISBN: 9783540442134
ISBN 10: 3540442138
Series: Stochastic Modelling and Applied Probability
Pages: 406
Publication Date: 01 June 2006
Audience: College/higher education , Professional and scholarly , Professional & Vocational , A / AS level , Further / Higher Education
Format: Mixed media product
Publisher's Status: Active

Reviews for Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction

From the reviews of the second edition: This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo methods commonly used in this approach. ... this book will be useful, especially to researchers with a strong background in probability and an interest in image analysis. The author has presented the theory with rigor ... . he doesn't neglect applications, providing numerous examples of applications to illustrate the theory and an abundant bibliography pointing to more detailed related work. (Pham Dinh Tuan, Mathematical Reviews, Issue 2004 c) Based on the Baysian approach the author focuses on the principles of classical image analysis rather than on applications and implementations. Little mathematical knowledge is needed to read the book, thus it is well suited for lectures on image analysis. (Ch. Cenker, Monatshefte fur Mathematik, Vol. 146 (4), 2005)