Bayesian Approach to Image Interpretation

Abstract

List of Figures. List of Tables. Preface. Acknowledgments. 1: Overview. 1. Introduction. 2. Image Interpretation. 3. Literature Review. 4. Approaches. 5. Layout of the Monograph. 2: Background. 1. Introduction. 2. Markov Random Field Models. 3. Multiresolution. 3: MRF Framework For Image Interpretation. 1. MRF on a Graph. 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. 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. 6: Conclusions. Appendices: Appendix A. Bayesian Reconstruction. Appendix B. Proof of Hammersley-Clifford Theorem. Appendix C. Simulated Annealing Algorithm - Selecting Toin practise. Appendix D. Custom Made Pyramids. Appendix E. Proof of Theorem 4.6. Appendix F. k-means clustering. Appendix G. Features used in Image Interpretation. Appendix H. Knowledge Acquisition. Appendix I. HMM for Clique Functions. References. Index.