eprintid: 2415
rev_number: 8
eprint_status: archive
userid: 6
dir: disk0/00/00/24/15
datestamp: 2014-12-11 11:25:26
lastmod: 2014-12-11 11:34:03
status_changed: 2014-12-11 11:25:26
type: book_section
metadata_visibility: show
creators_name: Bevilacqua, Marco
creators_name: Roumy, Aline
creators_name: Guillemot, Christine
creators_name: Alberi-Morel, Marie Line
creators_id: marco.bevilacqua@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
title: K-WEB: Nonnegative dictionary learning for sparse image representations
ispublished: pub
subjects: QA75
subjects: Z665
divisions: CSA
full_text_status: none
keywords: Dictionary learning; K-SVD; NMF; sparse representations

note: 20th IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, 15-18 September 2013 
abstract: This paper presents a new nonnegative dictionary learning method, to decompose an input data matrix into a dictionary of nonnegative atoms, and a representation matrix with a strict ℓ0-sparsity constraint. This constraint makes each input vector representable by a limited combination of atoms. The proposed method consists of two steps which are alternatively iterated: a sparse coding and a dictionary update stage. As for the dictionary update, an original method is proposed, which we call K-WEB, as it involves the computation of k WEighted Barycenters. The so designed algorithm is shown to outperform other methods in the literature that address the same learning problem, in different applications, and both with synthetic and “real” data, i.e. coming from natural images.
date: 2013-09
publisher: IEEE
pagerange: 146-150
event_title: Image Processing (ICIP), 2013 20th IEEE International Conference on
id_number: 10.1109/ICIP.2013.6738031
refereed: TRUE
book_title: Proceedings of the 20th IEEE International Conference on Image Processing (ICIP)
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6738031&isnumber=6737993
citation:   Bevilacqua, Marco and Roumy, Aline and Guillemot, Christine and Alberi-Morel, Marie Line  K-WEB: Nonnegative dictionary learning for sparse image representations.   In:  Proceedings of the 20th IEEE International Conference on Image Processing (ICIP).   IEEE, pp. 146-150.       (2013)