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Modeling and Inverse Problems in Imaging Analysis (Applied Mathematical Sciences)

Modeling and Inverse Problems in Imaging Analysis (Applied Mathematical Sciences)

Modeling and Inverse Problems in Imaging Analysis (Applied Mathematical
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Modeling and Inverse Problems in Imaging Analysis (Applied Mathematical Sciences) Paperback - 2011

by Chalmond, Bernard

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Details

  • Title Modeling and Inverse Problems in Imaging Analysis (Applied Mathematical Sciences)
  • Author Chalmond, Bernard
  • Binding Paperback
  • Edition Softcover reprin
  • Condition Used - Good
  • Pages 314
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 2011-12-12
  • Illustrated Yes
  • Features Illustrated
  • Bookseller's Inventory # 1441930493.G
  • ISBN 9781441930491 / 1441930493
  • Weight 1.05 lbs (0.48 kg)
  • Dimensions 9.21 x 6.14 x 0.71 in (23.39 x 15.60 x 1.80 cm)
  • Category Medical / Nursing
  • Dewey Decimal Code 006.42
  • Quantity available 1

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Reader reviews for Modeling and Inverse Problems in Imaging Analysis (Applied Mathematical Sciences)

From the publisher

This book is devoted to energy-based modeling issues. It will be useful to researchers and graduate students in mathematics, computer science, physics, and engineering.

From the rear cover

More mathematics 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. Through concrete image analysis problems, the author develops consistent modeling, a know-how generally hidden in the proposed solutions.

The book is divided into three main parts. The first two parts describe the theory behind the applications that are presented in the third part. These materials include splines (variational approach, regression spline, spline in high dimension) and random fields (Markovian field, parametric estimation, stochastic and deterministic optimization, continuous Gaussian field). Most of these applications come from industrial projects in which the author was involved in robot vision and radiography: tracking 3-D lines, radiographic image processing, 3-D reconstruction and tomography, matching and deformation learning. Numerous graphical illustrations accompany the text showing the performance of the proposed models.

This book will be useful to researchers and graduate students in mathematics, physics, computer science, and engineering.

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