Image analysis, random fields, and dynamic Monte Carlo methods
a mathematical introduction
by Winkler, Gerhard
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 elementary: 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.
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Image analysis, random fields, and dynamic Monte Carlo methods: a mathematical introduction
1995, Springer-Verlag, Springer-Verlag Berlin and Heidelberg GmbH & Co. K
in English
3540570691 9783540570691
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Includes bibliographical references (p. [307]-320) and index.
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- Created April 1, 2008
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| March 28, 2025 | Edited by ImportBot | Redacting ocaids |
| July 15, 2024 | Edited by MARC Bot | import existing book |
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