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The goal of this book is to deal with inverse problems and regularized solutions using Bayesian statistical tools, with a particular view to signal and image estimation. Chapters 1-3 cover the theoretical notions that make it possible to cast inverse problems within a mathematical framework. Chapters 4-6 address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions linked to image estimation.
Chapters 9-14 put the main tools introduced in the previous chapters into a practical context in important applicative areas, such as astronomy or medical imaging.