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Variational Methods in Imaging
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.Detailed info »« Brief info
Additional Information
| Publisher: | Springer |
| Publication Date: | 10/31/2008 |
| ISBN: | 9780387309316 |
| EAN: | 0387309314 |
| Paperback: | 320 pages |
| Language: | English |
| Physical Info: | 6.10 x 0.80 x 9.20 inches, (1.30 lbs) |
| Categories: | Applied | Imaging Systems |
| LC Subjects: | Variational principles, Imaging systems |
| Dewey: | 621.367 |
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