Document Type
Conference Proceeding
Publication Date
2010
Journal or Book Title
AIP Conference Proceedings
Volume
1211
First Page
806
Last Page
813
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.
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
Copyright Date
2010
Language
en
File Format
application/pdf
Recommended Citation
Dogandžić, Aleksandar and Qiu, Kun, "Automatic hard thresholding for sparse signal reconstruction from NDE measurements" (2010). Electrical and Computer Engineering Publications. 43.
https://lib.dr.iastate.edu/ece_pubs/43
Comments
The following article appeared in AIP Conference Proceedings 1211 (2010): 806 and may be found at doi:10.1063/1.3362486.