An Implementation and Detailed Analysis of the K-SVD Image Denoising Algorithm

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Communicated by Jean-Michel Morel
Demo edited by Miguel Colom

Abstract

K-SVD is a signal representation method which, from a set of signals, can derive a dictionary able to approximate each signal with a sparse combination of the atoms. This paper focuses on the K-SVD-based image denoising algorithm. The implementation is described in detail and its parameters are analyzed and varied to come up with a reliable implementation.

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• source code: TAR/GZ SWHID info
  Software Heritage Archive @softwareversion{sw-ipol.2012.llm-ksvd, title = {{An Implementation and Detailed Analysis of the K-SVD Image Denoising Algorithm}}, author = {Marc Lebrun, Arthur Leclaire}, date = {2011-01-01}, license = {GPL-3.0-or-later}, version = {1.0}, swhid = {swh:1:dir:7bfdc807fe14a8873fd457690cfa7ba11e957a86;origin=https://doi.org/10.5201/ipol.2012.llm-ksvd;visit=swh:1:snp:3fc5444c549cc45a6b285a3a5a4eb34d31de8b66;anchor=swh:1:rev:c78cdcf65f9f2fd89008647de7d7776cb2454f08}, related = {ipol.2012.llm-ksvd}, relatedtype = "Reference article: https://doi.org/10.5201/ipol.2012.llm-ksvd" } % the biblatex-software style extension is recommended for software bibitems
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History

• this article was converted to PDF on 2012-07-02
• the original version was published on 2012-05-19: manuscript, source code
• the source code was modified on 2021-02-05 to include the possibility to denoise with the given STD parameter without re-noising the input image. The original version of the code is available here
• the README file of the source code was updated on 2021-02-20. The previous version of the code is available here
• Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.