DCT Image Denoising: a Simple and Effective Image Denoising Algorithm

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Communicated by Bartomeu Coll
Demo edited by Jose-Luis Lisani

Abstract

This work presents a simple but effective denoising algorithm using a local DCT thresholding. This thresholding is applied separately to each color channel after decorrelation. Due to its simplicity and excellent performance, this contribution can be considered as a baseline for comparison and lower bound of performance for newly developed techniques.

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• full text manuscript: PDF (2.2M)
• source code: TAR/GZ SWHID info
  Software Heritage Archive @softwareversion{sw-ipol.2011.ys-dct, title = {{DCT Image Denoising: a Simple and Effective Image Denoising Algorithm}}, author = {Guoshen Yu, Guillermo Sapiro}, date = {2011-01-01}, license = {GPL-3.0-or-later}, version = {1.0}, swhid = {swh:1:dir:b8a2ab67f7d7220838a56477d8b490463cef5fa3;origin=https://doi.org/10.5201/ipol.2011.ys-dct;visit=swh:1:snp:a5b0f4d891e604a70a309da15a02ea8f1ba02b57;anchor=swh:1:rev:36a0b641586c6b47bc1bc0b1a89420c3d419641a}, related = {ipol.2011.ys-dct}, relatedtype = "Reference article: https://doi.org/10.5201/ipol.2011.ys-dct" } % the biblatex-software style extension is recommended for software bibitems
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History

• this article was converted to PDF on 2016-03-09
• the original version was published on 2011-10-24: manuscript, html version
• the original source code was modified on 2020-11-25 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.