Geometric Level Set Methods in Imaging, Vision, and Graphics (eBook, PDF)

Redaktion: Osher, Stanley; Paragios, Nikos

• Format: PDF

Produktbeschreibung

First book to clearly explain and apply new level set methods to problems and applications in computer vision, graphics, and imaging. An essential compilation of survey chapters from the leading researchers in the field, emphasizing the applications of the methods.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 513
• Erscheinungstermin: 8. Mai 2007
• Englisch
• ISBN-13: 9780387218106
• Artikelnr.: 43999013

Autorenporträt

First book to clearly explain and apply new level set methods to problems and applications in computer vision, graphics, and imaging. An essential compilation of survey chapters from the leading researchers in the field, emphasizing the applications of the methods.

Inhaltsangabe

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.