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Handbook of Mathematical Methods in Imaging

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Cover of 'Handbook of Mathematical Methods in Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Linear Inverse Problems
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    Chapter 2 Large-Scale Inverse Problems in Imaging
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    Chapter 3 Regularization Methods for Ill-Posed Problems
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    Chapter 4 Distance Measures and Applications to Multi-Modal Variational Imaging
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    Chapter 5 Energy Minimization Methods
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    Chapter 6 Handbook of Mathematical Methods in Imaging
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    Chapter 7 Duality and Convex Programming
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    Chapter 8 EM Algorithms
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    Chapter 9 Iterative Solution Methods
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    Chapter 10 Level Set Methods for Structural Inversion and Image Reconstruction
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    Chapter 11 Expansion Methods
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    Chapter 12 Sampling Methods
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    Chapter 13 Inverse Scattering
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    Chapter 14 Electrical Impedance Tomography
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    Chapter 15 Synthetic Aperture Radar Imaging
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    Chapter 16 Tomography
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    Chapter 17 Optical Imaging
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    Chapter 18 Photoacoustic and Thermoacoustic Tomography: Image Formation Principles
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    Chapter 19 Mathematics of Photoacoustic and Thermoacoustic Tomography
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    Chapter 20 Wave Phenomena
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    Chapter 21 Statistical Methods in Imaging
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    Chapter 22 Supervised Learning by Support Vector Machines
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    Chapter 23 Total Variation in Imaging
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    Chapter 24 Numerical Methods and Applications in Total Variation Image Restoration
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    Chapter 25 Mumford and Shah Model and its Applications to Image Segmentation andImage Restoration
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    Chapter 26 Local Smoothing Neighborhood Filters
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    Chapter 27 Neighborhood Filters and the Recovery of 3D Information
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    Chapter 28 Splines and Multiresolution Analysis
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    Chapter 29 Gabor Analysis for Imaging
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    Chapter 30 Shape Spaces
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    Chapter 31 Variational Methods in Shape Analysis
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    Chapter 32 Manifold Intrinsic Similarity
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    Chapter 33 Image Segmentation with Shape Priors: Explicit Versus Implicit Representations
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    Chapter 34 Starlet Transform in Astronomical Data Processing
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    Chapter 35 Differential Methods for Multi-Dimensional Visual Data Analysis
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Title
Handbook of Mathematical Methods in Imaging
Published by
Springer New York, November 2010
DOI 10.1007/978-0-387-92920-0
ISBNs
978-0-387-92919-4, 978-0-387-92920-0
Editors

Scherzer, Otmar, Scherzer, Otmar

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Spain 1 <1%
Sweden 1 <1%
Unknown 135 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 31%
Researcher 31 22%
Student > Master 23 17%
Other 7 5%
Professor 6 4%
Other 21 15%
Unknown 8 6%
Readers by discipline Count As %
Engineering 49 35%
Computer Science 23 17%
Mathematics 19 14%
Physics and Astronomy 13 9%
Earth and Planetary Sciences 5 4%
Other 16 12%
Unknown 14 10%