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Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing - Softcover
Synopsis
Preface.- Part I. Theoretical and Numerical Foundations.- 1. Introduction.- 2. Uniqueness and Uncertainty.- 3. Pursuit Algorithms - Practice.- 4. Pursuit Algorithms - Guarantees.- 5. From Exact to Approximate Solution.- 6. Iterated Shrinkage Algorithms.- 7.Towards Average Performance Analysis.- 8. The Danzig Selector Algorithm.- Part II. Signal and Image Processing Applications.- 9. Sparsity-Seeking Methods in Signal Processing.- 10. Image Deblurring - A Case Study.- 11. MAP versus MMSE Estimation.- 12. The Quest For a Dictionary.- 13. Image Compression - Facial Images.- 14. Image Denoising.- 15. Other Applications.- 16. Concluding Remarks.- Bibliography.- Index
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