TY - BOOK ID - 26283796 TI - Image analysis, random fields and Markov chain Monte Carlo methods : a mathematical introduction PY - 2003 VL - 27 SN - 01724568 SN - 3540442138 9783540442134 3642629113 3642557600 PB - Berlin: Springer, DB - UniCat KW - Stochastic processes KW - Image processing KW - Markov random fields KW - Monte Carlo method KW - Monte-Carlo, MeĢthode de KW - Statistical methods KW - beeldanalyse KW - Probabilities. KW - Optical data processing. KW - Numerical analysis. KW - Computer simulation. KW - Radiology. KW - StatisticsĀ . KW - Probability Theory and Stochastic Processes. KW - Image Processing and Computer Vision. KW - Numerical Analysis. KW - Simulation and Modeling. KW - Imaging / Radiology. KW - Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. KW - Statistical analysis KW - Statistical data KW - Statistical science KW - Mathematics KW - Econometrics KW - Radiological physics KW - Physics KW - Radiation KW - Computer modeling KW - Computer models KW - Modeling, Computer KW - Models, Computer KW - Simulation, Computer KW - Electromechanical analogies KW - Mathematical models KW - Simulation methods KW - Model-integrated computing KW - Mathematical analysis KW - Optical computing KW - Visual data processing KW - Bionics KW - Electronic data processing KW - Integrated optics KW - Photonics KW - Computers KW - Probability KW - Statistical inference KW - Combinations KW - Chance KW - Least squares KW - Mathematical statistics KW - Risk KW - Optical equipment KW - Image processing - Statistical methods UR - https://www.unicat.be/uniCat?func=search&query=sysid:26283796 AB - 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. ER -