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Barone P., Frigessi A., Piccioni M.(eds.) Stochastic Models, Statistical Methods, and Algorithms in Image Analysis

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Barone P., Frigessi A., Piccioni M.(eds.) Stochastic Models, Statistical Methods, and Algorithms in Image Analysis
N.-Y.: Springer, 1992. - 258p.
This volume comprises a collection of papers by world- renowned experts on image analysis. The papers range from survey articles to research papers, and from theoretical topics such as simulated annealing through to applied image reconstruction. It covers applications as diverse as biomedicine, astronomy, and geophysics. As a result, any researcher working on image analysis will find this book provides an up-to-date overview of the field and in addition, the extensive bibliographies will make this a useful reference.
Contents :
Front Matter
Edge Preserving Image Restoration
Boltzmann Machines : High-Order Interactions and Synchronous Learning
Bayesian 3-D Path Search and Its Applications to Focusing Seismic Data
Edge Detection and Segmentation of Textured Plane Images
IFS Algorithms for Wavelet Transforms, Curves and Surfaces, and Image Compression
Image restoration by stochastic dichotomic reconstruction of contour lines
A Comparison of Simulated Annealing of Gibbs Sampler and Metropolis Algorithm
Some Limit Theorems on Simulated Annealing
Statistical analysis of Markov random fields using large deviation estimates
Metropolis Methods, Gaussian Proposals and Antithetic Variables
The Chi-Square Coding Test for Nested Markov Random Field Hypotheses
Asymptotic Comparison of Estimators in the Ising Model
A Remark on the Ergodicity of Systematic Sweep in Stochastic Relaxation
Application of Bayesian Methods to Segmentation in Medical Images
Some Suggestions for Transmission Tomography Based on the EM Algorithm
Deconvolution in Optical Astronomy. A Bayesian Approach
Parameter Estimation For Imperfectly Observed Gibbs Fields and Some Comments on Chalmond’s EM Gibbsian Algorithm
Back Matter
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