Details

Subject(s)

• Image processing—Digital techniques—Mathematics [Browse]

Publisher

• Society for Industrial and Applied Mathematics [Browse]

Series

Other titles in applied mathematics. [More in this series]

Restrictions note

Restricted to subscribers or individual electronic text purchasers.

Summary note

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; and an 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.

Bibliographic references

Includes bibliographical references (pages 329-334) and index.

System details

• Mode of access: World Wide Web.
• System requirements: Adobe Acrobat Reader.

Source of description

Description based on title page of print version.

Contents

• Probability, estimation, and random processes
• Causal Gaussian models
• Non-causal Gaussian models
• Map estimation with Gaussian priors
• Non-Gaussian MRF models
• Map estimation with non-Gaussian priors
• Surrogate functions and majorization
• Constrained optimization and proximal methods
• Plug-and-play and advanced priors
• Model parameter estimation
• The expectation-maximization (EM) algorithm
• Markov chains and hidden Markov models
• General MRF models
• Stochastic simulation
• Bayesian segmentation
• Poisson data models.

Show 13 more Contents items

Other format(s)

Also available in print version.

ISBN

1-61197-713-4

Publisher no.

OT180

LCCN

2022004620

Doi

• 10.1137/1.9781611977134

Statement on language in description

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