Sparse and Redundant Representations : From Theory to Applications in Signal and Image Processing
The field of sparse and redundant representation modeling has gone through a major revolution in the past two decades. This started with a series of algorithms for approximating the sparsest solutions of linear systems of equations, later to be followed by surprising theoretical results that guarant...
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| Hlavní autor: | |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
New York, NY :
Springer New York
2010.
Cham : Springer Nature |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Sparse and redundant representations, from theory to applications in signal and image processing, Michael Elad,..., 2010, New York, Springer, 1 vol. (XX-376 p.), Mathematics, 978-1-441-97010-7 • Sparse and Redundant Representations, Texte imprimé, 9781441970121 • Sparse and redundant representations, from theory to applications in signal and image processing, Michael Elad,..., 2010, New York, Springer, 1 vol. (XX-376 p.), Mathematics, 978-1-441-97010-7 |
Obsah:
- Sparse and Redundant Representations Theoretical and Numerical Foundations
- Prologue
- Uniqueness and Uncertainty
- Pursuit Algorithms Practice
- Pursuit Algorithms Guarantees
- From Exact to Approximate Solutions
- Iterative-Shrinkage Algorithms
- Towards Average PerformanceAnalysis
- The Dantzig-Selector Algorithm
- From Theory to Practice Signal and Image Processing Applications
- Sparsity-Seeking Methods in Signal Processing
- Image Deblurring A Case Study
- MAP versus MMSE Estimation
- The Quest for a Dictionary
- Image Compression Facial Images
- Image Denoising
- Other Applications
- Epilogue.