
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods
A Mathematical Introduction
Résumé
This second edition of G. Winkler's successful book on random field approaches to image analysis, related Markov Chain Monte Carlo methods, and statistical inference with emphasis on Bayesian image analysis concentrates more on general principles and models and less on details of concrete applications. Addressed to students and scientists from mathematics, statistics, physics, engineering, and computer science, it will serve as an introduction to the mathematical aspects rather than a survey. Basically no prior knowledge of mathematics or statistics is required. The second edition is in many parts completely rewritten and improved, and most figures are new. The topics of exact sampling and global optimization of likelihood functions have been added. This second edition comes with a CD-ROM by F. Friedrich,containing a host of (live) illustrations for each chapter. In an interactive environment, readers can perform their own experiments to consolidate the subject.
Contents- Bayesian Image Analysis: Introduction
- The Gibbs Sampler and Simulated Annealing
- Variations of the Gibbs Sampler
- Metropolis Algorithms and Spectral Methods
- Texture Analysis
- Parameter Estimation
- Supplement
- Appendix
L'auteur - Gerhard Winkler
Winkler, G., Institute of Biomathematics and Biometry (IBB), Neuherberg, Germany
Caractéristiques techniques
PAPIER | |
Éditeur(s) | Springer |
Auteur(s) | Gerhard Winkler |
Parution | 04/12/2002 |
Édition | 2eme édition |
Nb. de pages | 388 |
Format | 16 x 24 |
Couverture | Relié |
Poids | 740g |
Intérieur | Noir et Blanc |
EAN13 | 9783540442134 |
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