This book presents recent mathematical methods in the area of inverse problems in imaging with a particular focus on the computational aspects and applications. The formulation of inverse problems in imaging requires accurate mathematical modeling in order to preserve the significant features of the image. The book describes computational methods to efficiently address these problems based on new optimization algorithms for smooth and nonsmooth convex minimization, on the use of structured (numerical) linear algebra, and on multilevel techniques. It also discusses various current and challenging applications in fields such as astronomy, microscopy, and biomedical imaging. The book is intended for researchers and advanced graduate students interested in inverse problems and imaging.
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Marco Donatelli is an Associate Professor of Numerical Analysis at the Department of Science and High Technology, University of Insubria (Italy). He was awarded a Ph.D. in Applied Mathematics by the University of Milan in 2006. His research interests include regularization methods of inverse problems, preconditioning and multigrid methods for structured matrices. He is author of more than 70 papers and he serves on the editorial boards of three international journals.
Stefano Serra-Capizzano is a Full Professor of Numerical Analysis at the Department of Humanities and Innovation, Deputy Rector of the University of Insubria (Italy) and long-term Visiting Scholar at Uppsala University (Sweden). He has authored over 200 research papers in different areas of mathematics, including numerical linear algebra, spectral theory, approximation theory, and inverse problems, with more than 100 collaborators around the globe. He is the founder of the Ph.D. Program "Mathematics of Computation" and of the Department of Science and High Technology at the University of Insubria.
This book presents recent mathematical methods in the area of inverse problems in imaging with a particular focus on the computational aspects and applications. The formulation of inverse problems in imaging requires accurate mathematical modeling in order to preserve the significant features of the image. The book describes computational methods to efficiently address these problems based on new optimization algorithms for smooth and nonsmooth convex minimization, on the use of structured (numerical) linear algebra, and on multilevel techniques. It also discusses various current and challenging applications in fields such as astronomy, microscopy, and biomedical imaging. The book is intended for researchers and advanced graduate students interested in inverse problems and imaging.
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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents recent mathematical methods in the area of inverse problems in imaging with a particular focus on the computational aspects and applications. The formulation of inverse problems in imaging requires accurate mathematical modeling in order to preserve the significant features of the image. The book describes computational methods to efficiently address these problems based on new optimization algorithms for smooth and nonsmooth convex minimization, on the use of structured (numerical) linear algebra, and on multilevel techniques. It also discusses various current and challenging applications in fields such as astronomy, microscopy, and biomedical imaging. The book is intended for researchers and advanced graduate students interested in inverse problems and imaging. 176 pp. Englisch. Bestandsnummer des Verkäufers 9783030328818
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Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents structured regularizing preconditioners for image deblurringDiscusses applications in astronomical and medical imagingIncludes a chapter on variable metric first-order methodsMarco Donatelli is an Associate Profes. Bestandsnummer des Verkäufers 448679166
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