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010   $a3-642-27795-0
024 7 $a10.1007/978-3-642-27795-5
035   $a(CKB)3710000000306363
035   $a(DE-He213)978-3-642-27795-5
035   $a(PPN)242974546
035   $a(EXLCZ)993710000000306363
100   $a20190617d2020      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aHandbook of Mathematical Methods in Imaging$b[electronic resource] /$fedited by Otmar Scherzer
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2020.
215   $a1 online resource (XVIII, 455 p. 150 illus.) 
327   $aIntroduction -- 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.
330   $aThe 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.
606   $aApplied mathematics
606   $aEngineering mathematics
606   $aOptical data processing
606   $aSignal processing
606   $aImage processing
606   $aSpeech processing systems
606   $aNumerical analysis
606   $aRadiology
606   $aApplications of Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M13003
606   $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021
606   $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051
606   $aNumerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M14050
606   $aImaging / Radiology$3https://scigraph.springernature.com/ontologies/product-market-codes/H29005
615  0$aApplied mathematics.
615  0$aEngineering mathematics.
615  0$aOptical data processing.
615  0$aSignal processing.
615  0$aImage processing.
615  0$aSpeech processing systems.
615  0$aNumerical analysis.
615  0$aRadiology.
615 14$aApplications of Mathematics.
615 24$aImage Processing and Computer Vision.
615 24$aSignal, Image and Speech Processing.
615 24$aNumerical Analysis.
615 24$aImaging / Radiology.
676   $a519
702   $aScherzer$b Otmar$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a996418273303316
996   $aHandbook of mathematical methods in imaging$91520292
997   $aUNISA