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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Elad, Michael (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York, 2010.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.