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Book Categories |
Preface | ||
1 | Introduction | 1 |
Pt. 1 | Image deconvolution | 17 |
2 | Some mathematical tools | 19 |
3 | Examples of image blurring | 50 |
4 | The ill-posedness of image deconvolution | 75 |
5 | Regularization methods | 98 |
6 | Iterative regularization methods | 137 |
7 | Statistical methods | 168 |
Pt. 2 | Linear inverse imaging problems | 189 |
8 | Examples of linear inverse problems | 191 |
9 | Singular value decomposition (SVD) | 220 |
10 | Inversion methods revisited | 247 |
11 | Fourier-based methods for specific problems | 268 |
12 | Comments and concluding remarks | 295 |
Pt. 3 | Mathematical appendices | 309 |
A | Euclidean and Hilbert spaces of functions | 311 |
B | Linear operators in function spaces | 317 |
C | Euclidean vector spaces and matrices | 322 |
D | Properties of the DFT and the FFT algorithm | 328 |
E | Minimization of quadratic functionals | 335 |
F | Contraction and non-expansive mappings | 339 |
G | The EM method | 343 |
References | 346 | |
Index | 347 |
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Add Introduction to inverse problems in imaging, This is a graduate textbook on the principles of linear inverse problems, methods of their approximate solution and practical application in imaging. The level of mathematical treatment is kept as low as possible to make the book suitable for a wide range, Introduction to inverse problems in imaging to the inventory that you are selling on WonderClubX
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Add Introduction to inverse problems in imaging, This is a graduate textbook on the principles of linear inverse problems, methods of their approximate solution and practical application in imaging. The level of mathematical treatment is kept as low as possible to make the book suitable for a wide range, Introduction to inverse problems in imaging to your collection on WonderClub |