A robust separable image denoising based on relative intersection of confidence intervals rule (CROSBI ID 598274)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Seršić, Damir ; Sović, Ana
engleski
A robust separable image denoising based on relative intersection of confidence intervals rule
Many microscopy images, or 3D depth maps can be represented using piecewise constant models. They usually contain noise due to sensor imperfectness. In this paper, an improved separable denoising method based on the relative intersection of confidence intervals rule is proposed. The method uses median averaging and is robust to outliers and different noise distributions. It over-performs competitive methods in the sense of edge preservation.
Intersection of confidence intervals; Image denoising; Median; Adaptive filters
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Podaci o prilogu
89-96.
2013.
objavljeno
Podaci o matičnoj publikaciji
ISPA 2013
Gianni Ramponi, Sven Lončarić, Alberto Carini, Karen Egiazarian
Trst: University of Zagreb, University of Trieste
978-953-184-187-0
1845-5921
Podaci o skupu
8th International Symposium on Image and Signal Processing and Analysis
predavanje
04.09.2013-06.09.2013
Trst, Italija