eprintid: 1530
rev_number: 6
eprint_status: archive
userid: 45
dir: disk0/00/00/15/30
datestamp: 2013-03-07 14:02:16
lastmod: 2013-03-12 14:58:11
status_changed: 2013-03-07 14:02:16
type: article
metadata_visibility: show
creators_name: Rusu, Cristian
creators_name: Dumitrescu, Bogdan
creators_id: cristian.rusu@imtlucca.it
creators_id: 
title: Stagewise K-SVD to Design Efficient Dictionaries for Sparse Representations
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
keywords: classification, coding, dataset, dictionaries, error constraint, pattern recognition, sparse representations, stagewise K-SVD 
abstract: The problem of training a dictionary for sparse representations from a given dataset is receiving a lot of attention mainly due to its applications in the fields of coding, classification and pattern recognition. One of the open questions is how to choose the number of atoms in the dictionary: if the dictionary is too small then the representation errors are big and if the dictionary is too big then using it becomes computationally expensive. In this letter, we solve the problem of computing efficient dictionaries of reduced size by a new design method, called Stagewise K-SVD, which is an adaptation of the popular K-SVD algorithm. Since K-SVD performs very well in practice, we use K-SVD steps to gradually build dictionaries that fulfill an imposed error constraint. The conceptual simplicity of the method makes it easy to apply, while the numerical experiments highlight its efficiency for different overcomplete dictionaries.
date: 2012
date_type: published
publication: IEEE Signal Processing Letters
volume: 19
number: 10
publisher: IEEE
pagerange: 631-634
id_number: 10.1109/LSP.2012.2209871
refereed: TRUE
issn: 1070-9908
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6247465&isnumber=6249741
citation:   Rusu, Cristian and Dumitrescu, Bogdan  Stagewise K-SVD to Design Efficient Dictionaries for Sparse Representations.  IEEE Signal Processing Letters, 19 (10).  pp. 631-634.  ISSN 1070-9908      (2012)