E-PLE: an Algorithm for Image Inpainting

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Communicated by Guillermo Sapiro
Demo edited by Yi-Qing Wang

Abstract

Gaussian mixture is a powerful tool for modeling the patch prior. In this work, a probabilisticview of an existing algorithm piecewise linear estimation (PLE) for image inpainting is presentedwhich leads to several theoretical and numerical improvements based on an effective use ofGaussian mixture.

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• full text manuscript: PDF (1.1M)
• source code: TGZ SWHID info
  Software Heritage Archive @softwareversion{sw-ipol.2013.54, title = {{E-PLE: an Algorithm for Image Inpainting}}, author = {Yi-Qing Wang}, date = {2012-12-22}, license = {BSD-2-Clause}, version = {1.1}, swhid = {swh:1:dir:197bf1a80d307facffbe8792af112538ee11e6e5;origin=https://doi.org/10.5201/ipol.2013.54;visit=swh:1:snp:1e802a6a4ffc9bc2142febb52eb2d8b675770786;anchor=swh:1:rev:f5edf83185d879f1d385feb2063fe9a805ceb71b}, related = {ipol.2013.54}, relatedtype = "Reference article: https://doi.org/10.5201/ipol.2013.54" } % the biblatex-software style extension is recommended for software bibitems
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History

• 2013-12-04: original publication - source code
• 2014-04-26: bugfix for the algorithm to exit gracefully if all the pixels are masked.
• 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.