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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2011.
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| Edición: | 1st ed. 2011. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 245 | 1 | 0 | |a Handbook of Mathematical Methods in Imaging |h [electronic resource] / |c edited by Otmar Scherzer. |
| 250 | |a 1st ed. 2011. | ||
| 264 | 1 | |a New York, NY : |b Springer New York : |b Imprint: Springer, |c 2011. | |
| 300 | |a eReference. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 505 | 0 | |a 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. | |
| 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. 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. | ||
| 650 | 0 | |a Mathematics. | |
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a Signal processing. | |
| 650 | 0 | |a Numerical analysis. | |
| 650 | 0 | |a Radiology. | |
| 650 | 1 | 4 | |a Applications of Mathematics. |
| 650 | 2 | 4 | |a Computer Vision. |
| 650 | 2 | 4 | |a Signal, Speech and Image Processing . |
| 650 | 2 | 4 | |a Numerical Analysis. |
| 650 | 2 | 4 | |a Radiology. |
| 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 9780387929194 |
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| 950 | |a Reference Module Computer Science and Engineering (SpringerNature-43748) | ||