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 eBook
• Language: English
• Published: New York, NY : Springer New York, 2010.
• Subjects: Mathematics.; Image processing.; Mathematical analysis.; Analysis (Mathematics).; Approximation theory.; Mathematical models.; Mathematical optimization.; Analysis.; Mathematical Modeling and Industrial Mathematics.; Optimization.; Approximations and Expansions.; Image Processing and Computer Vision.; Signal, Image and Speech 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...

Table of Contents:

• 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.