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Publications/esteban.19.caip - Revision history
2024-03-28T14:18:18Z
Revision history for this page on the wiki
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https://www.lrde.epita.fr/index.php?title=Publications/esteban.19.caip&diff=128711&oldid=prev
Bot at 11:30, 13 July 2023
2023-07-13T11:30:46Z
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Bot
https://www.lrde.epita.fr/index.php?title=Publications/esteban.19.caip&diff=128594&oldid=prev
Bot at 17:07, 7 April 2023
2023-04-07T17:07:18Z
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https://www.lrde.epita.fr/index.php?title=Publications/esteban.19.caip&diff=125855&oldid=prev
Bot at 10:47, 24 November 2020
2020-11-24T10:47:13Z
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| id = esteban.19.caip</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>@InProceedings<nowiki>{</nowiki> esteban.19.caip,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> address = <nowiki>{</nowiki>Salerno, Italy<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> month = sep,</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> doi = <nowiki>{</nowiki>10.1007/978-3-030-29891-3_33<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> abstract = <nowiki>{</nowiki>The knowledge of the noise level within an image is a</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> abstract = <nowiki>{</nowiki>The knowledge of the noise level within an image is a</div></td>
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https://www.lrde.epita.fr/index.php?title=Publications/esteban.19.caip&diff=124242&oldid=prev
Bot at 09:56, 2 September 2019
2019-09-02T09:56:31Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:56, 2 September 2019</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| title = Estimating the noise level function with the tree of shapes and non-parametric statistics</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| booktitle = Proceedings of the 18th International Conference on Computer Analysis of Images and Patterns (CAIP)</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| booktitle = Proceedings of the 18th International Conference on Computer Analysis of Images and Patterns (CAIP)</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| pages = 377 to 388</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| series = Lecture Notes in Computer Science Series</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| series = Lecture Notes in Computer Science Series</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| volume = 11679</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>| publisher = Springer</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| address = Salerno, Italy</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| address = Salerno, Italy</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| abstract = The knowledge of the noise level within an image is a valuableinformation for many image processing applications. Estimating the noise level function (NLF) requires the identification of homogeneous regions, upon which the noise parameters are computed. Sutour et al. have proposed a method to estimate this NLF based on the search for homogeneous regions of square shape. We generalize this method to the search for homogeneous regions with arbitrary shape thanks to the tree of shapes representation of the image under study, thus allowing a more robust and precise estimation of the noise level function.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>| abstract = The knowledge of the noise level within an image is a valuableinformation for many image processing applications. Estimating the noise level function (NLF) requires the identification of homogeneous regions, upon which the noise parameters are computed. Sutour et al. have proposed a method to estimate this NLF based on the search for homogeneous regions of square shape. We generalize this method to the search for homogeneous regions with arbitrary shape thanks to the tree of shapes representation of the image under study, thus allowing a more robust and precise estimation of the noise level function.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> Computer Analysis of Images and Patterns (CAIP)<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> Computer Analysis of Images and Patterns (CAIP)<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> year = 2019,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> year = 2019,</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> pages = <nowiki>{</nowiki>377--388<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> series = <nowiki>{</nowiki>Lecture Notes in Computer Science Series<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> series = <nowiki>{</nowiki>Lecture Notes in Computer Science Series<nowiki>}</nowiki>,</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> volume = <nowiki>{</nowiki>11679<nowiki>}</nowiki>,</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> publisher = <nowiki>{</nowiki>Springer<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> address = <nowiki>{</nowiki>Salerno, Italy<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> address = <nowiki>{</nowiki>Salerno, Italy<nowiki>}</nowiki>,</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div> month = sep,</div></td>
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https://www.lrde.epita.fr/index.php?title=Publications/esteban.19.caip&diff=123444&oldid=prev
Bot: Created page with "{{Publication | published = true | date = 2019-06-07 | authors = Baptiste Esteban, Guillaume Tochon, Thierry Géraud | title = Estimating the noise level function with the tre..."
2019-06-27T11:28:53Z
<p>Created page with "{{Publication | published = true | date = 2019-06-07 | authors = Baptiste Esteban, Guillaume Tochon, Thierry Géraud | title = Estimating the noise level function with the tre..."</p>
<p><b>New page</b></p><div>{{Publication<br />
| published = true<br />
| date = 2019-06-07<br />
| authors = Baptiste Esteban, Guillaume Tochon, Thierry Géraud<br />
| title = Estimating the noise level function with the tree of shapes and non-parametric statistics<br />
| booktitle = Proceedings of the 18th International Conference on Computer Analysis of Images and Patterns (CAIP)<br />
| series = Lecture Notes in Computer Science Series<br />
| address = Salerno, Italy<br />
| abstract = The knowledge of the noise level within an image is a valuableinformation for many image processing applications. Estimating the noise level function (NLF) requires the identification of homogeneous regions, upon which the noise parameters are computed. Sutour et al. have proposed a method to estimate this NLF based on the search for homogeneous regions of square shape. We generalize this method to the search for homogeneous regions with arbitrary shape thanks to the tree of shapes representation of the image under study, thus allowing a more robust and precise estimation of the noise level function.<br />
| lrdepaper = http://www.lrde.epita.fr/dload/papers/esteban.19.caip.pdf<br />
| lrdekeywords = Image<br />
| lrdenewsdate = 2019-06-07<br />
| type = inproceedings<br />
| id = esteban.19.caip<br />
| bibtex = <br />
@InProceedings<nowiki>{</nowiki> esteban.19.caip,<br />
author = <nowiki>{</nowiki>Baptiste Esteban and Guillaume Tochon and Thierry<br />
G\'eraud<nowiki>}</nowiki>,<br />
title = <nowiki>{</nowiki>Estimating the noise level function with the tree of<br />
shapes and non-parametric statistics<nowiki>}</nowiki>,<br />
booktitle = <nowiki>{</nowiki>Proceedings of the 18th International Conference on<br />
Computer Analysis of Images and Patterns (CAIP)<nowiki>}</nowiki>,<br />
year = 2019,<br />
series = <nowiki>{</nowiki>Lecture Notes in Computer Science Series<nowiki>}</nowiki>,<br />
address = <nowiki>{</nowiki>Salerno, Italy<nowiki>}</nowiki>,<br />
month = sep,<br />
abstract = <nowiki>{</nowiki>The knowledge of the noise level within an image is a<br />
valuableinformation for many image processing applications.<br />
Estimating the noise level function (NLF) requires the<br />
identification of homogeneous regions, upon which the noise<br />
parameters are computed. Sutour et al. have proposed a<br />
method to estimate this NLF based on the search for<br />
homogeneous regions of square shape. We generalize this<br />
method to the search for homogeneous regions with arbitrary<br />
shape thanks to the tree of shapes representation of the<br />
image under study, thus allowing a more robust and precise<br />
estimation of the noise level function.<nowiki>}</nowiki><br />
<nowiki>}</nowiki><br />
<br />
}}</div>
Bot