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| Publisher | Springer-Verlag New York Inc. |
| ISBN 13 | 9781441930491 |
| ISBN 10 | 1441930493 |
| Book Description | More mathematicians have been taking part in the development of digital image processing as a science and the contributions are reflected in the increasingly important role modeling has played solving complex problems. This book is mostly concerned with energy-based models. Most of these models come from industrial projects in which the author was involved in robot vision and radiography: tracking 3D lines, radiographic image processing, 3D reconstruction and tomography, matching, deformation learning. Numerous graphical illustrations accompany the text. |
| Editorial Review | "...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) |
| Language | English |
| Author | Bernard Chalmond |
| Publication Date | 12 Dec 2011 |
| Number of Pages | 314 |
Modeling And Inverse Problems In Imaging Analysis paperback english - 12 Dec 2011
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