Please use this identifier to cite or link to this item:
Title: DALM-SVD: Accelerated sparse coding through singular value decomposition of the dictionary
Authors: Gonçalves,HR
Miguel Velhote Correia
Vítor Grade Tavares
Issue Date: 2014
Abstract: Sparse coding techniques have seen an increasing range of applications in recent years, especially in the area of image processing. In particular, sparse coding using l<inf>1</inf>-regularization has been efficiently solved with the Augmented Lagrangian (AL) applied to its dual formulation (DALM). This paper proposes the decomposition of the dictionary matrix in its Singular Value/Vector form in order to simplify and speed-up the implementation of the DALM algorithm. Furthermore, we propose an update rule for the penalty parameter used in AL methods that improves the convergence rate. The SVD of the dictionary matrix is done as a pre-processing step prior to the sparse coding, and thus the method is better suited for applications where the same dictionary is reused for several sparse recovery steps, such as block image processing. © 2014 IEEE.
metadata.dc.type: conferenceObject
Appears in Collections:C-BER - Articles in International Conferences
CTM - Articles in International Conferences

Files in This Item:
File Description SizeFormat 
  Restricted Access
399.51 kBAdobe PDFThumbnail
View/Open Request a copy

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.