Difference between revisions of "Publications/esteban.20.seminar"

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(Created page with "{{CSIReport | authors = Baptiste Esteban | title = Estimation of the Noise Level Function in Multivariate Images using the Tree of Shapes and non-parametric statistics | year...")
 
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| year = 2020
 
| year = 2020
 
| number = 2002
 
| number = 2002
| abstract = Nowadays, a lot of image processing application needs to know the noise level of an image to take it into account in these processes or to remove it. To do that, we developed a method to estimate the noise level, modelised by a functionthe noise level function, for grayscale images, and then for multivariate imagesusing simplified hypotheses. This semester, we introduced new tools to improve this method and to remove the simplified hypotheses defined the last semester.
+
| abstract = Nowadays, a lot of image processing applications need to know the noise level of an image to take it into account in these processes or to remove it. To do so, we developed a method to estimate the noise level, modeled by the noise level function, for grayscale images, and then for multivariate imagesusing simplifying hypotheses. This semester, we introduced new tools to improve this method and to remove the simplifying hypotheses defined the last semester.
 
| type = techreport
 
| type = techreport
 
| id = esteban.20.seminar
 
| id = esteban.20.seminar

Revision as of 14:40, 13 January 2020

Abstract

Nowadays, a lot of image processing applications need to know the noise level of an image to take it into account in these processes or to remove it. To do so, we developed a method to estimate the noise level, modeled by the noise level function, for grayscale images, and then for multivariate imagesusing simplifying hypotheses. This semester, we introduced new tools to improve this method and to remove the simplifying hypotheses defined the last semester.