Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing /

• Main Author: Elad, Michael. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York, 2010.
• Subjects: Mathematics.; Computer vision.; Mathematical optimization.; Approximations and Expansions.; Image Processing and Computer Vision.; Signal, Image and Speech Processing.; Optimization.; Applications of Mathematics.; Mathematical Modeling and Industrial Mathematics.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-7011-4

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...

Table of Contents:

• 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.