BLIND IMAGE DECONVOLUTION: PROBLEM FORMULATION AND EXISTING APPROACHES Tom E. Bishop, S. Derin Babacan, Bruno Amizic, Aggelos K. Katsaggelos, Tony Chan, and Rafael Molina Introduction Mathematical Problem Formulation Classification of Blind Image Deconvolution Methodologies Bayesian Framework for Blind Image Deconvolution Bayesian Modeling of Blind Image Deconvolution Bayesian Inference Methods in Blind Image Deconvolution Non-Bayesian Blind Image Deconvolution Models Conclusions References BLIND IMAGE DECONVOLUTION USING BUSSGANG TECHNIQUES: APPLICATIONS TO IMAGE DEBLURRING AND TEXTURE SYNTHESIS Patrizio Campisi, Alessandro Neri, Stefania Colonnese, Gianpiero Panci, and Gaetano Scarano Introduction Bussgang Processes Single-Channel Bussgang Deconvolution Multichannel Bussgang deconvolution Conclusions References BLIND MULTIFRAME IMAGE DECONVOLUTION USING ANISOTROPIC SPATIALLY ADAPTIVE FILTERING FOR DENOISING AND REGULARIZATION Vladimir Katkovnik, Karen Egiazarian, and Jaakko Astola Introduction Observation Model and Preliminaries Frequency Domain Equations Projection Gradient Optimization Anisotropic LPA-ICI Spatially Adaptive Filtering Blind Deconvolution Algorithm Identifiability and Convergence Simulations Conclusions Acknowledgments References BAYESIAN METHODS BASED ON VARIATIONAL APPROXIMATIONS FOR BLIND IMAGE DECONVOLUTION Aristidis Likas and Nikolas P. Galatsanos Introduction Background on Variational Methods Variational Blind Deconvolution Numerical Experiments Conclusions and Future Work APPENDIX A: Computation of the Variational Bound F(q,?) APPENDIX B: Maximization of F(q,?) References DECONVOLUTION OF MEDICAL IMAGES FROM MICROSCOPIC TO WHOLE BODY IMAGES Oleg V. Michailovich and Dan R. Adam Introduction Nonblind Deconvolution Blind Deconvolution in Ultrasound Imaging Blind Deconvolution in SPECT Blind Deconvolution in Confocal Microscopy Summary References BAYESIAN ESTIMATION OF BLUR AND NOISE IN REMOTE SENSING IMAGING Andre Jalobeanu, Josiane Zerubia, and Laure Blanc-Feraud Introduction The Forward Model Bayesian Estimation: Invert the Forward Model Possible Improvements and Further Development Results Conclusions Acknowledgments References DECONVOLUTION AND BLIND DECONVOLUTION IN ASTRONOMY Eric Pantin, Jean-luc Starck, and Fionn Murtagh Introduction The Deconvolution Problem Linear Regularized Methods CLEAN Bayesian Methodology Iterative Regularized Methods Wavelet-Based Deconvolution Deconvolution and Resolution Myopic and Blind Deconvolution Conclusions and Chapter Summary Acknowledgments References MULTIFRAME BLIND DECONVOLUTION COUPLED WITH FRAME REGISTRATION AND RESOLUTION ENHANCEMENT Filip Sroubek, Jan Flusser, and Gabriel Cristobal Introduction Mathematical Model Polyphase Formulation Reconstruction of Volatile Blurs Blind Superresolution Experiments Conclusions Acknowledgments References BLIND RECONSTRUCTION OF MULTIFRAME IMAGERY BASED ON FUSION AND CLASSIFICATION Dimitrios Hatzinakos, Alexia Giannoula, and Jianxin Han Introduction System Overview Recursive Inverse Filtering with Finite Normal-Density Mixtures (RIF-FNM) Optimal Filter Adaptation Effects of Noise The Fusion and Classification Recursive Inverse Filtering Algorithm (FAC-RIF) Experimental Results Final Remarks References BLIND DECONVOLUTION AND STRUCTURED MATRIX COMPUTATIONS WITH APPLICATIONS TO ARRAY IMAGING Michael K. Ng and Robert J. Plemmons Introduction One-Dimensional Deconvolution Formulation Regularized and Constrained TLS Formulation Numerical Algorithms Two-Dimensional Deconvolution Problems Numerical Examples Application: High-Resolution Image Reconstruction Concluding Remarks and Current Work Acknowledgments References INDEX