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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Scherzer, Otmar (Autor), Grasmair, Markus (Autor), Grossauer, Harald (Autor), Haltmeier, Markus (Autor), Lenzen, Frank (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Colección:Applied Mathematical Sciences, 167
Temas:
Mathematical optimization.
Calculus of variations.
Computer vision.
Signal processing.
Numerical analysis.
Radiology.
Calculus of Variations and Optimization.
Computer Vision.
Signal, Speech and Image Processing .
Numerical Analysis.
Acceso en línea:Texto Completo
Descripción
Sumario: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.
Descripción Física:XIV, 320 p. online resource.
ISBN:9780387692777
ISSN:2196-968X ;

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