Bayesian approach to image interpretation /

• Κύριος συγγραφέας: Kopparapu, Sunil K. (συγγραφέας.)
• Άλλοι συγγραφείς: Desai, Uday B. (συγγραφέας.)
• Μορφή: Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston : Kluwer Academic Publishers, c2001.
• Σειρά: Kluwer international series in engineering and computer science
• Θέματα: Επεξεργασία εικόνας > Ψηφιακές τεχνικές; Τεχνητή όραση; Μπεϋζιανή στατιστική θεωρία αποφάσεων; Ηλεκτρονικά βιβλία

Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and pr...

Πίνακας περιεχομένων:

• Cover
• Table of Contents
• List of Figures
• List of Tables
• Preface
• Acknowledgements
• Chapter 1. Overview
• 1. Introduction
• 2. Image Interpretation
• 3. Literature Review
• 4. Approaches
• 5. Layout of the Monograph
• Chapter 2. Background
• 1. Introduction
• 2. Markov Random Field Models
• 3. Multiresolution
• Chapter 3. MRF Framework for Image Interpretation
• 1. MRF on a Graph
• Chapter 4. Bayesian Net Approach to Interpretation
• 1. Introduction
• 2. MRF model leading to Bayesian Network Formulation
• 3. Bayesian Networks and Probabilistic Inference
• 4. Probability Updating in Bayesian Networks
• 5. Bayesian Networks for Gibbsian Image Interpretation
• 6. Experimental Results
• 7. Conclusions
• Chapter 5. Joint Segmentation and Image Interpretation
• 1. Introduction
• 2. Image Interpretation using Integration
• 3. The Joint Segmentation and Image Interpretation Scheme
• 4. Experimental Results
• 5. Conclusions
• Chapter 6. Conclusions
• Appendices
• Appendix A. Bayesian Reconstruction
• Appendix B. Proof of Hammersley-Clifford Theorem
• 1. Justification for the General form for U(x)
• Appendix C. Simulated Annealing Algorithm-Selecting T0 in practise
• 1. Experiments
• Appendix D. Custom Made Pyramids
• Appendix E. Proof of Theorem 4.6
• Appendix F. k-means clustering
• Appendix G. Features used in Image Interpretation
• 1. Primary Features
• 2. Secondary Features
• Appendix H. Knowledge Acquisition
• 1. How to merge regions using the XV color editor
• 2. Acquired Knowledge
• 3. Knowledge Pyramid
• Appendix I. HMM for Clique Functions
• References