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Stochastic Image Processing (Information Technology: Transmission, Processing, and Storag)

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Stochastic Image Processing (Information Technology: Transmission, Processing, and Storag) Cover

 

Synopses & Reviews

Publisher Comments:

Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although promoted as a promising approach for over thirty years, it has only been in the past few years that the theory and algorithms have developed to the point of providing useful solutions to old and new problems in image processing. Markov random fields are a multidimensional extension of Markov chains, but the generalization is complicated by the lack of a natural ordering of pixels in multidimensional spaces. Hidden Markov fields are a natural generalization of the hidden Markov models that have proved essential to the development of modern speech recognition, but again the multidimensional nature of the signals makes them inherently more complicated to handle. This added complexity contributed to the long time required for the development of successful methods and applications. This book collects together a variety of successful approaches to a complete and useful characterization of multidimensional Markov and hidden Markov models along with applications to image analysis. The book provides a survey and comparative development of an exciting and rapidly evolving field of multidimensional Markov and hidden Markov random fields with extensive references to the literature.

Synopsis:

Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although promoted as a promising approach for over thirty years, it has only been in the past few years that the theory and algorithms have developed to the point of providing useful solutions to old and new problems in image processing. Markov random fields are a multidimensional extension of Markov chains, but the generalization is complicated by the lack of a natural ordering of pixels in multidimensional spaces. Hidden Markov fields are a natural generalization of the hidden Markov models that have proved essential to the development of modern speech recognition, but again the multidimensional nature of the signals makes them inherently more complicated to handle. This added complexity contributed to the long time required for the development of successful methods and applications. This book collects together a variety of successful approaches to a complete and useful characterization of multidimensional Markov and hidden Markov models along with applications to image analysis. The book provides a survey and comparative development of an exciting and rapidly evolving field of multidimensional Markov and hidden Markov random fields with extensive references to the literature.

Table of Contents

Introduction.- Noncausal Markov Random Fields.- Causal Markov Random Fields.- Multiscale Markov Models.- Block-wise Markov Models.- Index.

Product Details

ISBN:
9780306481925
Author:
Won, Chee Sun
Publisher:
Springer
Author:
Chee Sun Won, Sun Won
Author:
Gray, Robert M.
Location:
Boston, MA
Subject:
Stochastic processes
Subject:
Imaging Systems
Subject:
Image processing
Subject:
Data Processing - Optical Data Processing
Subject:
Optical data processing
Subject:
Image processing -- Digital techniques.
Subject:
Science Reference-Technology
Subject:
Computer Graphics - General
Subject:
Image Processing and Computer Vision
Subject:
Computer Imaging, Vision, Pattern Recognition and Graphics
Subject:
Signal, Image and Speech Processing
Subject:
Electrical engineering
Subject:
Imaging / Radiology
Subject:
Computer Science
Subject:
Language, literature and biography
Subject:
Engineering
Subject:
Computer Vision
Subject:
Computer Engineering
Subject:
Radiology, medical
Copyright:
Edition Description:
Book
Series:
Information technology: transmission, processing, and storage
Series Volume:
51
Publication Date:
20040331
Binding:
HARDCOVER
Language:
English
Illustrations:
Yes
Pages:
180
Dimensions:
235 x 155 mm 467 gr

Related Subjects

Computers and Internet » Artificial Intelligence » Image Processing
Computers and Internet » Operating Systems » General
Reference » Science Reference » Technology

Stochastic Image Processing (Information Technology: Transmission, Processing, and Storag) Used Hardcover
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$65.00 In Stock
Product details 180 pages Kluwer Academic/Plenum Publishers - English 9780306481925 Reviews:
"Synopsis" by , Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although promoted as a promising approach for over thirty years, it has only been in the past few years that the theory and algorithms have developed to the point of providing useful solutions to old and new problems in image processing. Markov random fields are a multidimensional extension of Markov chains, but the generalization is complicated by the lack of a natural ordering of pixels in multidimensional spaces. Hidden Markov fields are a natural generalization of the hidden Markov models that have proved essential to the development of modern speech recognition, but again the multidimensional nature of the signals makes them inherently more complicated to handle. This added complexity contributed to the long time required for the development of successful methods and applications. This book collects together a variety of successful approaches to a complete and useful characterization of multidimensional Markov and hidden Markov models along with applications to image analysis. The book provides a survey and comparative development of an exciting and rapidly evolving field of multidimensional Markov and hidden Markov random fields with extensive references to the literature.
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