Computing an Exact Gaussian Scale-Space
Ives Rey Otero, Mauricio Delbracio
→ BibTeX
@article{ipol.2016.117,
    title   = {{Computing an Exact Gaussian Scale-Space}},
    author  = {Rey Otero, Ives and Delbracio, Mauricio},
    journal = {{Image Processing On Line}},
    volume  = {6},
    pages   = {8--26},
    year    = {2016},
    doi     = {10.5201/ipol.2016.117},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2016.117}}
published
2016-02-02
reference
Ives Rey Otero, and Mauricio Delbracio, Computing an Exact Gaussian Scale-Space, Image Processing On Line, 6 (2016), pp. 8–26. https://doi.org/10.5201/ipol.2016.117

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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