Geometric Level Set Methods in Imaging, Vision and Graphics - Osher, Stanley J.

Geometric Level Set Methods in Imaging, Vision and Graphics

Stanley J. Osher

Yayınevi: Springer

Yayın tarihi: 05/2003

ISBN: 9780387954882

Yazar : Nikos Paragios

Ciltli | İngilizce | 542 Sayfa |

Tür: Matematik-İstatistik

  • Temin Süresi 49 - 63 iş günü


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The topic of level sets is currently very timely and useful. They are powerful numerical techniques for analyzing and computing interface motion in a host of application settings. In computer vision, it has been applied to stereo and segmentation, whereas in graphics it has been applied to the postproduction process of in-painting and 3-D model construction. Osher is co-inventor of the Level Set Methods, a pioneering framework introduced jointly with Professor James Sethian from the University of Berkeley in 1998. This methodology has been used up to now to provide solutions to a wide application range not limited to image processing, computer vision, robotics, fluid mechanics, crystallography, lithography, and computer graphics. The topic is of great interest, and the audience is not limited to students, professors, universities, and people working in the areas of graphics (post-production), video-based surveillance, visual inspection, augmented reality, document image processing, and medical image processing. These techniques are already employed to provide solutions and products in the industry too (Cognitech, Siemens, Philips, Focus Imaging).

This book can be suitable for a short professional course related with the processing of visual information.

Table of Contents
List of Contributors
I Level Set Methods & Lagrangian Approaches 1
1 Level Set Methods by Stanley Osher 3
2 Deformable Models: Classic, Topology-Adaptive and Generalized Formulations by Demetri Terzopoulos 21
II Edge Detection & Boundary Extraction 41
3 Fast Methods for Implicit Active Contour Models by Joachim Weickert and Gerald Kuhne 43
4 Fast Edge Integration by Ron Kimmel 59
5 Variational Snake Theory by Agnes Desolneux and Lionel Moisan and Jean-Michel Morel 79
III Scalar & Vector Image Reconstruction, Restoration 101
6 Multiplicative Denoising and Deblurring: Theory and Algorithms by Leonid Rudin and Pierre-Luis Lions and Stanley Osher 103
7 Total Variation Minimization for Scalar/Vector Regularization by Francoise Dibos and Georges Koepfler and Pascal Monasse 121
8 Morphological Global Reconstruction and Levelings: Lattice and PDE Approaches by Petros Maragos 141
IV Grouping 157
9 Fast Marching Techniques for Visual Grouping & Segmentation by Eftychis Sifakis and George Tziritas 159
10 Multiphase Object Detection and Image Segmentation by Luminita Vese 175
11 Adaptive Segmentation of Vector Valued Images by Mikael Rousson and Rachid Deriche 195
12 Mumford-Shah for Segmentation and Stereo by Anthony Yezzi and Stefano Soatto and Hailin Jin and Andy Tsai and Alan Willsky 207
V Knowledge-based Segmentation & Registration 229
13 Shape Analysis towards Model-based Segmentation by Nikos Paragios and Mikael Rousson 231
14 Joint Image Registration and Segmentation by Baba Vemuri and Yunmei Chen 251

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