Computing an Exact Gaussian Scale-Space

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Communicated by Pascal Getreuer
Demo edited by Ives Rey Otero

Abstract

Gaussian convolution is one of the most important algorithms in image processing. The present work focuses on the computation of the Gaussian scale-space, a family of increasingly blurred images, responsible, among other things, for the scale-invariance of SIFT, a popular image matching algorithm. We discuss and numerically analyze the precision of three different alternatives for defining a discrete counterpart to the continuous Gaussian operator. This study is focused on low blur levels, that are crucial for the scale-space accuracy.

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  Software Heritage Archive @softwareversion{sw-ipol.2016.117, title = {{Computing an Exact Gaussian Scale-Space}}, author = {Ives Rey Otero, Mauricio Delbracio}, date = {2015-08-06}, license = {GPL-3.0-or-later}, version = {20150806}, swhid = {swh:1:dir:b1413bd5d3db494374beab3cbfd69056af614674;origin=https://doi.org/10.5201/ipol.2016.117;visit=swh:1:snp:e7cfec0cd643af365af2b118f187e12a47e8e020;anchor=swh:1:rev:6da30ded5a467754c58b33d74a760dafa213ed02}, related = {ipol.2016.117}, relatedtype = "Reference article: https://doi.org/10.5201/ipol.2016.117" } % the biblatex-software style extension is recommended for software bibitems
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History

• 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.