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Level Set and PDE Based Reconstruction Methods in Imaging

Cetraro, Italy 2008, Editors: Martin Burger, Stanley Osher

  • Martin Burger
  • Andrea C.G. Mennucci
  • Stanley Osher
  • Martin Rumpf

Part of the Lecture Notes in Mathematics book series (LNM, volume 2090)

Also part of the C.I.M.E. Foundation Subseries book sub series (LNMCIME, volume 2090)

Table of contents

  1. Front Matter
    Pages i-vii
  2. Martin Burger, Stanley Osher
    Pages 1-70
  3. Alex Sawatzky, Christoph Brune, Thomas Kösters, Frank Wübbeling, Martin Burger
    Pages 71-142
  4. Andrea C. G. Mennucci
    Pages 205-319
  5. Back Matter
    Pages 321-322

About this book

Introduction

This book takes readers on a tour through modern methods in image analysis and reconstruction based on level set and PDE techniques, the major focus being on morphological and geometric structures in images. The aspects covered include edge-sharpening image reconstruction and denoising, segmentation and shape analysis in images, and image matching. For each, the lecture notes provide insights into the basic analysis of modern variational and PDE-based techniques, as well as computational aspects and applications.

Keywords

94A08,35Q94,68U10,65K10,35J20,45Q05,53C44 Image Analysis Image Reconstruction Inverse Problems Shape Spaces Variational Methods in Imaging

Authors and affiliations

  • Martin Burger
    • 1
  • Andrea C.G. Mennucci
    • 2
  • Stanley Osher
    • 3
  • Martin Rumpf
    • 4
  1. 1.Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
  2. 2.Scuola Normale SuperiorePisaItaly
  3. 3.Department of MathematicsUniversity of CaliforniaLos AngelesUSA
  4. 4.Institute for Numerical SimulationUniversity of BonnBonnGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-01712-9
  • Copyright Information Springer International Publishing Switzerland 2013
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-01711-2
  • Online ISBN 978-3-319-01712-9
  • Series Print ISSN 0075-8434
  • Series Online ISSN 1617-9692
  • Buy this book on publisher's site