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
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;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2009.2026610