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Article
Automatic hard thresholding for sparse signal reconstruction from NDE measurements
AIP Conference Proceedings
  • Aleksandar Dogandžić, Iowa State University
  • Kun Qiu, Iowa State University
Document Type
Conference Proceeding
Publication Date
1-1-2010
DOI
10.1063/1.3362486
Abstract
We propose an automatic hard thresholding (AHT) method for sparse‐signal reconstruction. The measurements follow an underdetermined linear model, where the regression‐coefficient vector is modeled as a superposition of an unknown deterministic sparse‐signal component and a zero‐mean white Gaussian component with unknown variance. Our method demands no prior knowledge about signal sparsity. Our AHT scheme approximately maximizes a generalized maximum likelihood (GML) criterion, providing an approximate GML estimate of the signal sparsity level and an empirical Bayesian estimate of the regression coefficients. We apply the proposed method to reconstruct images from sparse computerized tomography projections and compare it with existing approaches.
Comments

The following article appeared in AIP Conference Proceedings 1211 (2010): 806 and may be found at doi:10.1063/1.3362486.

Rights
Copyright 2010 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.
Copyright Owner
American Institute of Physics
Language
en
Date Available
2014-10-08
File Format
application/pdf
Citation Information
Aleksandar Dogandžić and Kun Qiu. "Automatic hard thresholding for sparse signal reconstruction from NDE measurements" AIP Conference Proceedings Vol. 1211 (2010) p. 806 - 813
Available at: http://works.bepress.com/aleksandar_dogandzic/35/