University of Surrey

Test tubes in the lab Research in the ATI Dance Research

A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing

Abolghasemi, V, Ferdowsi, S and Sanei, S (2012) A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing Signal Processing, 92 (4). pp. 999-1009.

[img] Text
A gradient-based alternating minimization approach for optimization of the measurement matrix in compressive sensing.pdf
Restricted to Repository staff only
Available under License : See the attached licence file.

Download (559kB)
[img]
Preview
Text (licence)
SRI_deposit_agreement.pdf

Download (33kB)

Abstract

In this paper the problem of optimization of the measurement matrix in compressive (also called compressed) sensing framework is addressed. In compressed sensing a measurement matrix that has a small coherence with the sparsifying dictionary (or basis) is of interest. Random measurement matrices have been used so far since they present small coherence with almost any sparsifying dictionary. However, it has been recently shown that optimizing the measurement matrix toward decreasing the coherence is possible and can improve the performance. Based on this conclusion, we propose here an alternating minimization approach for this purpose which is a variant of Grassmannian frame design modified by a gradient-based technique. The objective is to optimize an initially random measurement matrix to a matrix which presents a smaller coherence than the initial one. We established several experiments to measure the performance of the proposed method and compare it with those of the existing approaches. The results are encouraging and indicate improved reconstruction quality, when utilizing the proposed method. © 2011 Elsevier B.V. All rights reserved.

Item Type: Article
Authors :
AuthorsEmailORCID
Abolghasemi, VUNSPECIFIEDUNSPECIFIED
Ferdowsi, SUNSPECIFIEDUNSPECIFIED
Sanei, SUNSPECIFIEDUNSPECIFIED
Date : April 2012
Identification Number : https://doi.org/10.1016/j.sigpro.2011.10.012
Depositing User : Symplectic Elements
Date Deposited : 01 Mar 2017 13:45
Last Modified : 01 Mar 2017 13:45
URI: http://epubs.surrey.ac.uk/id/eprint/742925

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800