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Author:   Stanley Osher ,  Nikos Paragios
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2003 ed.
Dimensions:   Width: 15.50cm , Height: 3.00cm , Length: 23.50cm
Weight:   1.045kg
ISBN:  

9780387954882

ISBN 10:   0387954880
Pages:   513
Publication Date:   17 July 2003
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Level Set Methods & Lagrangian Approaches.- Level Set Methods.- Deformable Models: Classic, Topology-Adaptive and Generalized Formulations.- Edge Detection & Boundary Extraction.- Fast Methods for Implicit Active Contour Models.- Fast Edge Integration.- Variational Snake Theory.- Scalar & Vector Image Reconstruction, Restoration.- Multiplicative Denoising and Deblurring: Theory and Algorithms.- Total Variation Minimization for Scalar/Vector Regularization.- Morphological Global Reconstruction and Levelings: Lattice and PDE Approaches.- Grouping.- Fast Marching Techniques for Visual Grouping & Segmentation.- Multiphase Object Detection and Image Segmentation.- Adaptive Segmentation of Vector Valued Images.- Mumford-Shah for Segmentation and Stereo.- Knowledge-based Segmentation & Registration.- Shape Analysis towards Model-based Segmentation.- Joint Image Registration and Segmentation.- Image Alignment.- Motion Analysis.- Variational Principles in Optical Flow Estimation and Tracking.- Region Matching and Tracking under Deformations or Occlusions.- Computational Stereo & Implicit Surfaces.- Computational Stereo: A Variational Method.- Visualization, Analysis and Shape Reconstruction of Sparse Data.- Variational Problems and Partial Differential Equations on Implicit Surfaces: Bye Bye Triangulated Surfaces?.- Medical Image Analysis.- Knowledge-Based Segmentation of Medical Images.- Topology Preserving Geometric Deformable Models for Brain Reconstruction.- Simulations & Graphics.- Editing Geometric Models.- Simulating Natural Phenomena.

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