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Foundations of computational imaging : a model-based approach

Foundations of computational imaging : a model-based approach (Loan 1 times)

Material type
단행본
Personal Author
Bouman, Charles Addison, author.
Title Statement
Foundations of computational imaging : a model-based approach / Charles A. Bouman.
Publication, Distribution, etc
Philadelphia :   Society for Industrial and Applied Mathematics,   2022.  
Physical Medium
xi, 337 p. : ill. ; 26 cm.
ISBN
9781611977127
요약
"This book provides a foundation for a collection of theoretical material that can serve as a common language for both researchers and practitioners of Computational Imaging"--
Content Notes
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.
Bibliography, Etc. Note
Includes bibliographical references and index.
Subject Added Entry-Topical Term
Image processing --Digital techniques --Mathematics.
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020 ▼z 9781611977134 ▼q (ebook)
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040 ▼a LBSOR/DLC ▼b eng ▼e rda ▼c DLC ▼d 211009
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100 1 ▼a Bouman, Charles Addison, ▼e author.
245 1 0 ▼a Foundations of computational imaging : ▼b a model-based approach / ▼c Charles A. Bouman.
260 ▼a Philadelphia : ▼b Society for Industrial and Applied Mathematics, ▼c 2022.
264 1 ▼a Philadelphia : ▼b Society for Industrial and Applied Mathematics, ▼c [2022]
300 ▼a xi, 337 p. : ▼b ill. ; ▼c 26 cm.
336 ▼a text ▼b txt ▼2 rdacontents
337 ▼a unmediated ▼b n ▼2 rdamedia
338 ▼a volume ▼b nc ▼2 rdacarrier
504 ▼a Includes bibliographical references and index.
505 0 ▼a 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.
520 ▼a "This book provides a foundation for a collection of theoretical material that can serve as a common language for both researchers and practitioners of Computational Imaging"-- ▼c Provided by publisher.
650 0 ▼a Image processing ▼x Digital techniques ▼x Mathematics.
945 ▼a ITMT

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/Western Books/ Call Number 006.6 B764f Accession No. 111869339 Availability In loan Due Date 2023-01-11 Make a Reservation Available for Reserve R Service M

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