Variational methods in imaging
This book is devoted to the study of variational methods in imaging. The presentation is mathematically rigorous and covers a detailed treatment of the approach from an inverse problems point of view. Key Features: - Introduces variational methods with motivation from the deterministic, geometric, a...
Tallennettuna:
| Päätekijät: | , , , , |
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| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Sarja: | Applied Mathematical Sciences
167 |
| Aiheet: | |
| Linkit: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Huomautus: |
Description d'après consultation du 06 juillet 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Variational methods in imaging, Otmar Scherzer, Markus Grasmair, Harald Grossauer... [et al.], New York, Springer, 2009, 1 vol. (XIII-320 p.), Applied mathematical sciences, 978-0-387-30931-6 |
| Yhteenveto: | This book is devoted to the study of variational methods in imaging. The presentation is mathematically rigorous and covers a detailed treatment of the approach from an inverse problems point of view. Key Features: - Introduces variational methods with motivation from the deterministic, geometric, and stochastic point of view - Bridges the gap between regularization theory in image analysis and in inverse problems - Presents case examples in imaging to illustrate the use of variational methods e.g. denoising, thermoacoustics, computerized tomography - Discusses link between non-convex calculus of variations, morphological analysis, and level set methods - Analyses variational methods containing classical analysis of variational methods, modern analysis such as G-norm properties, and non-convex calculus of variations - Uses numerical examples to enhance the theory This book is geared towards graduate students and researchers in applied mathematics. It can serve as a main text for graduate courses in image processing and inverse problems or as a supplemental text for courses on regularization. Researchers and computer scientists in the area of imaging science will also find this book useful |
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| Huomautukset: | Description d'après consultation du 06 juillet 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Bibliografia: | Bibliogr. Index |
| ISBN: | 9780387692777 |
| ISSN: | 0066-5452 |
| Pääsy: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |