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Accelerated graph-based spectral polynomial filters

BF, GF and CG filters on 1D signals
Abstract: 

Graph-based spectral denoising is a low-pass filtering using the eigendecomposition of the graph Laplacian matrix of a noisy signal. Polynomial filtering avoids costly computation of the eigendecomposition by projections onto suitable Krylov subspaces. Polynomial filters can be based, e.g., on the bilateral and guided filters. We propose constructing accelerated polynomial filters by running flexible Krylov subspace based linear and eigenvalue solvers such as the Block Locally Optimal Preconditioned Conjugate Gradient (LOBPCG) method. (arXiv:1509.02468 [cs.CV], DOI: 10.1109/MLSP.2015.7324315)

MLSP2015.pdf

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Paper Details

Authors:
Alexander Malyshev
Submitted On:
23 February 2016 - 1:44pm
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Presentation Slides
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Presenter's Name:
Alexander Malyshev
Document Year:
2015
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MLSP2015.pdf

(259 downloads)

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[1] Alexander Malyshev, "Accelerated graph-based spectral polynomial filters", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/297. Accessed: May. 28, 2017.
@article{297-15,
url = {http://sigport.org/297},
author = {Alexander Malyshev },
publisher = {IEEE SigPort},
title = {Accelerated graph-based spectral polynomial filters},
year = {2015} }
TY - EJOUR
T1 - Accelerated graph-based spectral polynomial filters
AU - Alexander Malyshev
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/297
ER -
Alexander Malyshev. (2015). Accelerated graph-based spectral polynomial filters. IEEE SigPort. http://sigport.org/297
Alexander Malyshev, 2015. Accelerated graph-based spectral polynomial filters. Available at: http://sigport.org/297.
Alexander Malyshev. (2015). "Accelerated graph-based spectral polynomial filters." Web.
1. Alexander Malyshev. Accelerated graph-based spectral polynomial filters [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/297