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Table of contents (14 chapters)
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Introduction
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Spline Models
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Markov Models
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Modeling in Action
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Erratum
Keywords
About this book
Reviews
From the reviews:
"...This book is an excellent introduction to Bayesian imaging and spline models in image analysis. It can be used for courses aimed at both mathematical statisticians who want to learn more about applications to imaging and engineers who aim to incorporate adequate mathematical formalism into their research."-- MATHEMATICAL REVIEWS
"The introduction of this book clearly explains – at a level any undergraduate student in mathematics can understand – the basic concepts of image analysis. The examples throughout the book are well-explained and rich. The different types of modeling are also explained … . this book can be advised to students or beginning researchers who want to have a good overview with an easy, self-contained introduction to the field of Image Analysis." (Peter Leoni, Physicalia, Vol. 28 (4-6), 2006)
Authors and Affiliations
Bibliographic Information
Book Title: Modeling and Inverse Problems in Imaging Analysis
Authors: Bernard Chalmond
Series Title: Applied Mathematical Sciences
DOI: https://doi.org/10.1007/978-0-387-21662-1
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2003
Hardcover ISBN: 978-0-387-95547-6Published: 14 January 2003
Softcover ISBN: 978-1-4419-3049-1Published: 12 December 2011
eBook ISBN: 978-0-387-21662-1Published: 06 December 2012
Series ISSN: 0066-5452
Series E-ISSN: 2196-968X
Edition Number: 1
Number of Pages: XXII, 314
Topics: Mathematical Modeling and Industrial Mathematics, Applications of Mathematics, Statistical Theory and Methods, Computer Imaging, Vision, Pattern Recognition and Graphics, Theoretical, Mathematical and Computational Physics