ENGLISH

Variational methods in imaging

By Otmar Scherzer , Markus Grasmair , Harald Grossauer , Markus Haltmeier , Frank Lenzen (auth.)

Book information

Publisher
Springer-Verlag New York
Year
2009
ISBN
9780387309316, 0387309314, 9780387692777, 0387692770
DOI
10.1007/978-0-387-69277-7
LCC
TK8315 .V37 2009
Open Library ID
OL23631148M
Language
english
Format
PDF
Filesize
5 MB (5720228 bytes)
Series
Applied mathematical sciences 167
Edition
1
Pages
320\323
Library
Kolxo3
Time added
2009-07-20 03:45:11
Calculus of Variations and Optimal Control; OptimiImage and Speech Processing; Numerical Analysis; I

Description

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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