Handbook of Mathematical Methods in Imaging

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 t...

Full description

Corporate Author: SpringerLink (Online service)
Other Authors: Scherzer, Otmar. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2015.
Edition:2nd ed. 2015.
Subjects:
Online Access:https://doi.org/10.1007/978-1-4939-0790-8
LEADER 05605nam a22005655i 4500
001 978-1-4939-0790-8
003 DE-He213
005 20210622033218.0
007 cr nn 008mamaa
008 150530s2015 xxu| s |||| 0|eng d
020 |a 9781493907908  |9 978-1-4939-0790-8 
024 7 |a 10.1007/978-1-4939-0790-8  |2 doi 
050 4 |a QA76.9.M35 
072 7 |a PBWH  |2 bicssc 
072 7 |a MAT003000  |2 bisacsh 
072 7 |a PBWH  |2 thema 
082 0 4 |a 004.0151  |2 23 
245 1 0 |a Handbook of Mathematical Methods in Imaging  |h [electronic resource] /  |c edited by Otmar Scherzer. 
250 |a 2nd ed. 2015. 
264 1 |a New York, NY :  |b Springer New York :  |b Imprint: Springer,  |c 2015. 
300 |a 472 illus., 200 illus. in color. eReference.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a 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. 
520 |a 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. This expanded and revised second edition contains updates to existing chapters and 16 additional entries on important mathematical methods such as graph cuts, morphology, discrete geometry, PDEs, conformal methods, to name a few. 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 200 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. 
650 0 |a Computer science—Mathematics. 
650 0 |a Computer mathematics. 
650 0 |a Optical data processing. 
650 0 |a Signal processing. 
650 0 |a Image processing. 
650 0 |a Speech processing systems. 
650 0 |a Numerical analysis. 
650 0 |a Radiology. 
650 1 4 |a Mathematical Applications in Computer Science.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/M13110 
650 2 4 |a Image Processing and Computer Vision.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I22021 
650 2 4 |a Signal, Image and Speech Processing.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/T24051 
650 2 4 |a Numerical Analysis.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/M14050 
650 2 4 |a Imaging / Radiology.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/H29005 
700 1 |a Scherzer, Otmar.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eReference 
776 0 8 |i Printed edition:  |z 9781493907915 
776 0 8 |i Printed edition:  |z 9781493907892 
856 4 0 |u https://doi.org/10.1007/978-1-4939-0790-8 
912 |a ZDB-2-SMA 
912 |a ZDB-2-SXRC 
950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Reference Module Computer Science and Engineering (SpringerNature-43748)