Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing

The solution of inverse problems is an unavoidable step in the signal and image processing chain, situated between data acquisition and decision making. Various inversion problems are presented by the authors of this book, such as tomography, detection-estimation, multi-resolution analysis, moving object tracking, and sparse approximations. Recent mathematical concepts and tools in information theory, optimization, Bayesian inference and statistical modeling are put into practice in these different contexts.
Each chapter is devoted to a widely developed and documented application. Through various perspectives, a vast number of fields is covered : medical and biological imaging, astronomy, non-destructive evaluation, video processing, digital communications, sensor networks, etc.