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Handbook of Mathematical Methods in Imaging

Author: Otmar Scherzer
Publisher: New York, NY : Springer New York, 2015.
Series: Online access with purchase: Springer (t)
Edition/Format:  eBook : Document : English : Second editionView all editions and formats
Summary:
The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Otmar Scherzer
ISBN: 9781493907908 1493907905 9781493907915 1493907913
OCLC Number: 912394909
Description: 1 online resource (XVIII, 2178 pages) : illustrations (some color)
Contents: Linear Inverse Problems --
Large-Scale Inverse Problems in Imaging --
Regularization Methods for Ill-Posed Problems --
Distance Measures and Applications to Multi-Modal Variational Imaging --
Energy Minimization Methods --
Compressive Sensing --
Duality and Convex Programming --
EM Algorithms --
Iterative Solution Methods --
Level Set Methods for Structural Inversion and Image Reconstructions --
Expansion Methods --
Sampling Methods --
Inverse Scattering --
Electrical Impedance Tomography --
Synthetic Aperture Radar Imaging --
Tomography --
Optical Imaging --
Photoacoustic and Thermoacoustic Tomography: Image Formation Principles --
Mathematics of Photoacoustic and Thermoacoustic Tomography --
Wave Phenomena --
Statistical Methods in Imaging --
Supervised Learning by Support Vector Machines --
Total Variation in Imaging --
Numerical Methods and Applications in Total Variation Image Restoration --
Mumford and Shah Model and its Applications in Total Variation Image Restoration --
Local Smoothing Neighbourhood Filters --
Neighbourhood Filters and the Recovery of 3D Information --
Splines and Multiresolution Analysis --
Gabor Analysis for Imaging --
Shaper Spaces --
Variational Methods in Shape Analysis --
Manifold Intrinsic Similarity --
Image Segmentation with Shape Priors: Explicit Versus Implicit Representations --
Starlet Transform in Astronomical Data Processing --
Differential Methods for Multi-Dimensional Visual Data Analysis --
Wave fronts in Imaging, Quinto --
Ultrasound Tomography, Natterer --
Optical Flow, Schnoerr --
Morphology, Petros --
Maragos --
PDEs, Weickert. --
Registration, Modersitzki --
Discrete Geometry in Imaging, Bobenko, Pottmann --
Visualization, Hege --
Fast Marching and Level Sets, Osher --
Couple Physics Imaging, Arridge --
Imaging in Random Media, Borcea --
Conformal Methods, Gu --
Texture, Peyre --
Graph Cuts, Darbon --
Imaging in Physics with Fourier Transform (i.e. Phase Retrieval e.g Dark field imaging), J.R. Fienup --
Electron Microscopy, Öktem Ozan --
Mathematical Imaging OCT (this is also FFT based), Mark E. Brezinski --
Spect, PET, Faukas, Louis.
Series Title: Online access with purchase: Springer (t)
Responsibility: Otmar Scherzer, editor.

Abstract:

This handbook provides comprehensive coverage of mathematical techniques used in imaging science. The material is grouped into two themes: Inverse Problems (Algorithmic Reconstruction) and Signal and  Read more...

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