Foundations of Computational Imaging: A Model-Based Approach

丛 书 名：Other Titles in Applied Mathematics

作     者：Charles A. Bouman 

I S B N：(纸本) 9781611977127 

出 版 社：Society for Industrial and Applied Mathematics 

出 版 年：2022年

主 题 词：computational imaging model-based iterative reconstruction MAP estimation Markov random fields EM algorithm inverse problems Plug-and-play priors image reconstruction constrained optimization augmented Lagrangian ADMM statistical signal processing tomography 

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

摘      要：Collecting a set of classical and emerging methods not available in a single treatment, Foundations of Computational Imaging: A Model-Based Approach is the first book to define a common foundation for the mathematical and statistical methods used in computational imaging. The book brings together a blend of research with applications in a variety of disciplines, including applied math, physics, chemistry, optics, and signal processing, to address a collection of problems that can benefit from a common set of methods. Readers will find basic techniques of model-based image processing;a comprehensive treatment of Bayesian and regularized image reconstruction methods; andan integrated treatment of advanced reconstruction techniques, such as majorization, constrained optimization, alternating direction method of multipliers (ADMM), and Plug-and-Play methods for model integration.