Geometric Level Set Methods in Imaging, Vision, and Graphics

• Κύριοι συγγραφείς: Osher, Stanley (Συγγραφέας), Paragios, Nikos (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York, 2003.
• Θέματα: Computer science.; Computer graphics.; Image processing.; Pattern recognition.; Computer mathematics.; Computer Science.; Image Processing and Computer Vision.; Computer Graphics.; Pattern Recognition.; Computational Mathematics and Numerical Analysis.; Signal, Image and Speech Processing.

  Level set methods are emerging techniques for representing, deforming, and recovering structures in an arbitrary dimension across different fields (mathematics, fluid dynamics, graphics, imaging, vision, etc.). Advances in numerical analysis have led to computationally efficient tools for computing and analyzing interface motion within level set frameworks in a host of application settings. This authoritative edited survey provides readers with the state-of-the-art in applying level set techniques in the imaging, vision, and graphics domains, presenting thematically grouped chapters contributed by leading experts from both industry and academia. The work bridges the theoretical foundations of level set methods with the latest significant applications. It will assist readers with both the technical aspects of the field as well as its practical ramifications for areas like medical imaging, computer animation, film restoration, video surveillance, visual inspection, and a range of scientific and engineering disciplines. Topics and features: * Covers comprehensively the applications of imaging, vision, & graphics * Includes a helpful introductory survey chapter on level set methods * Provides a complete overview of concepts and advanced technologies in the field * Describes leading-edge research, providing insight into a variety of potential avenues for problem solving * Supplies numerous implementations, examples, and relevant and useful experimental results This essential resource carefully integrates the theoretical foundations of level set methods with their actual performance capabilities. Its clarity of organization and approach makes the book accessible for researchers and professionals working in the areas of vision, graphics, image processing, robotics, mathematics, and computational geometry.>. 

 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.