• DocumentCode
    1125369
  • Title

    Parametric Dictionary Design for Sparse Coding

  • Author

    Yaghoobi, Mehrdad ; Daudet, Laurent ; Davies, Mike E.

  • Author_Institution
    Res. Inst. for Signal & Image Process., Edinburgh Univ., Edinburgh, UK
  • Volume
    57
  • Issue
    12
  • fYear
    2009
  • Firstpage
    4800
  • Lastpage
    4810
  • Abstract
    This paper introduces a new dictionary design method for sparse coding of a class of signals. It has been shown that one can sparsely approximate some natural signals using an overcomplete set of parametric functions. A problem in using these parametric dictionaries is how to choose the parameters. In practice, these parameters have been chosen by an expert or through a set of experiments. In the sparse approximation context, it has been shown that an incoherent dictionary is appropriate for the sparse approximation methods. In this paper, we first characterize the dictionary design problem, subject to a constraint on the dictionary. Then we briefly explain that equiangular tight frames have minimum coherence. The complexity of the problem does not allow it to be solved exactly. We introduce a practical method to approximately solve it. Some experiments show the advantages one gets by using these dictionaries.
  • Keywords
    approximation theory; encoding; equiangular tight frames; minimum coherence; parametric dictionary design; sparse approximation context; sparse coding; Dictionary design; Gammatone filter banks; exact sparse recovery; incoherent dictionary; parametric dictionary; sparse approximation;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2009.2026610
  • Filename
    5153350