Image Analysis, Random Fields and Dynamic Monte Carlo Methods : A Mathematical Introduction / by Gerhard Winkler
(Applications of Mathematics, Stochastic Modelling and Applied Probability ; 27)
| データ種別 | 電子ブック |
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| 出版者 | Berlin, Heidelberg : Springer Berlin Heidelberg |
| 出版年 | 1995 |
| 本文言語 | 英語 |
| 大きさ | XIV, 324 p : online resource |
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| 内容注記 | I. Bayesian Image Analysis: Introduction 1. The Bayesian Paradigm 2. Cleaning Dirty Pictures 3. Random Fields II. The Gibbs Sampler and Simulated Annealing 4. Markov Chains: Limit Theorems 5. Sampling and Annealing 6. Cooling Schedules 7. Sampling and Annealing Revisited III. More on Sampling and Annealing 8. Metropolis Algorithms 9. Alternative Approaches 10. Parallel Algorithms IV. Texture Analysis 11. Partitioning 12. Texture Models and Classification V. Parameter Estimation 13. Maximum Likelihood Estimators 14. Spacial ML Estimation VI. Supplement 15. A Glance at Neural Networks 16. Mixed Applications VII. Appendix A. Simulation of Random Variables B. The Perron-Frobenius Theorem C. Concave Functions D. A Global Convergence Theorem for Descent Algorithms References |
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| 一般注記 | 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 |
| 著者標目 | *Winkler, Gerhard author SpringerLink (Online service) |
| 件 名 | LCSH:Mathematics LCSH:Radiology LCSH:Software engineering LCSH:Computer simulation LCSH:Pattern recognition LCSH:Probabilities LCSH:Statistics FREE:Mathematics FREE:Probability Theory and Stochastic Processes FREE:Pattern Recognition FREE:Simulation and Modeling FREE:Imaging / Radiology FREE:Software Engineering/Programming and Operating Systems FREE:Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
| 分 類 | DC23:519.2 |
| 巻冊次 | ISBN:9783642975226 
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| ISBN | 9783642975226 |
| URL | http://dx.doi.org/10.1007/978-3-642-97522-6 |
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