Method proposed in "Simultaneous Sparse Dictionary Learning and Pruning" ( Qu and Wang (2016) <arXiv:1605.07870>) is implemented. The idea is to conduct a linear decomposition of a signal using a few atoms of a learned and usually over-completed dictionary instead of a pre-defined basis. A proper size of the to-be-learned dictionary is determining at the same time during the procedure. Application includes image denoising and image inpainting.
Version: | 0.1.0 |
Depends: | R (≥ 3.2.3) |
Imports: | Rcpp, Matrix, fields, methods |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2017-10-06 |
Author: | Simeng Qu [aut, cre], Xiao Wang [aut] |
Maintainer: | Simeng Qu <simengqu at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | yes |
CRAN checks: | GSCAD results |
Reference manual: | GSCAD.pdf |
Package source: | GSCAD_0.1.0.tar.gz |
Windows binaries: | r-devel: GSCAD_0.1.0.zip, r-release: GSCAD_0.1.0.zip, r-oldrel: GSCAD_0.1.0.zip |
OS X El Capitan binaries: | r-release: GSCAD_0.1.0.tgz |
OS X Mavericks binaries: | r-oldrel: GSCAD_0.1.0.tgz |
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