Franklin

Handbook of Mathematical Methods in Imaging / edited by Otmar Scherzer.

Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2020.
Format/Description:
Book
1 online resource (XVIII, 455 pages) : 150 illustrations
Series:
Mathematics and Statistics (Springer-11649)
Contained In:
Springer Nature Living Reference
Status/Location:
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Details

Subjects:
Applied mathematics.
Engineering mathematics.
Optical data processing.
Signal processing.
Image processing.
Speech processing systems.
Numerical analysis.
Radiology.
Local subjects:
Applications of Mathematics. (search)
Image Processing and Computer Vision. (search)
Signal, Image and Speech Processing. (search)
Numerical Analysis. (search)
Imaging / Radiology. (search)
System Details:
text file PDF
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 by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.
Contents:
Introduction
Part 1: Inverse Problems
Tomography
MR DTI
Hybrid Methods
Nonlinear Inverse Problems
EIT
Scattering
Sampling Methods
Expansion Methods
Regularization Methods for Ill-Posed Problems
Iterative Solution Methods
Wave Phenomena
Seismic
Radar
Ultrasound
Part 2: Signal and Image Processing
Morphological Image Processing
Learning, Classification, Data Mining
Partial Differential Equations
Variational Methods for Image Analysis
Level Set Methods Including Fast Marching Methods
Segmentation
Registration, Optical Flow
Duality and Convex Minimization
Spline, Statistics
Wavelets
Fourier Analysis
Compressed Sensing
Geometry Processing
Compression
Computational Geometry
Shape Spaces
PDEs and Variational Methods on Manifold
References
Subject Index.
Contributor:
Scherzer, Otmar. editor., Editor,
SpringerLink (Online service)
ISBN:
978-3-642-27795-5
9783642277955
Publisher Number:
10.1007/978-3-642-27795-5 doi
Access Restriction:
Restricted for use by site license.