LEADER 05607nam 22007695 450 001 9910299787903321 005 20230810162202.0 010 $a1-4939-0790-5 024 7 $a10.1007/978-1-4939-0790-8 035 $a(CKB)3710000000416755 035 $a(SSID)ssj0001501508 035 $a(PQKBManifestationID)11848393 035 $a(PQKBTitleCode)TC0001501508 035 $a(PQKBWorkID)11446797 035 $a(PQKB)11439090 035 $a(DE-He213)978-1-4939-0790-8 035 $a(MiAaPQ)EBC6311484 035 $a(MiAaPQ)EBC5610492 035 $a(Au-PeEL)EBL5610492 035 $a(OCoLC)912394909 035 $a(PPN)186024932 035 $a(EXLCZ)993710000000416755 100 $a20150530d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aHandbook of Mathematical Methods in Imaging /$fedited by Otmar Scherzer 205 $a2nd ed. 2015. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2015. 215 $a1 online resource (472 illus., 200 illus. in color. eReference.) 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-4939-0791-3 311 $a1-4939-0789-1 320 $aIncludes bibliographical references and index. 327 $aLinear 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. 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. 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. 606 $aComputer science$xMathematics 606 $aComputer vision 606 $aSignal processing 606 $aNumerical analysis 606 $aRadiology 606 $aMathematical Applications in Computer Science 606 $aComputer Vision 606 $aSignal, Speech and Image Processing 606 $aNumerical Analysis 606 $aRadiology 615 0$aComputer science$xMathematics. 615 0$aComputer vision. 615 0$aSignal processing. 615 0$aNumerical analysis. 615 0$aRadiology. 615 14$aMathematical Applications in Computer Science. 615 24$aComputer Vision. 615 24$aSignal, Speech and Image Processing . 615 24$aNumerical Analysis. 615 24$aRadiology. 676 $a616.0754 702 $aScherzer$b Otmar$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299787903321 996 $aHandbook of mathematical methods in imaging$91520292 997 $aUNINA