The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nous proposons, dans cette lettre, un nouveau type de filtre débruiteur d'image utilisant une technique d'analyse de données. Nous traitons les pixels en tant que données et extrayons le cluster le plus dominant des pixels dans la fenêtre de filtrage. Nous obtenons le centre de gravité du cluster extrait. Nous démontrons que ce filtre graphique-spectral peut réduire efficacement un mélange de bruit impulsif gaussien et aléatoire.
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Yu QIU, Zenggang DU, Kiichi URAHAMA, "Graph-Spectral Filter for Removing Mixture of Gaussian and Random Impulsive Noise" in IEICE TRANSACTIONS on Fundamentals,
vol. E94-A, no. 1, pp. 457-460, January 2011, doi: 10.1587/transfun.E94.A.457.
Abstract: We propose, in this letter, a new type of image denoising filter using a data analysis technique. We deal with pixels as data and extract the most dominant cluster from pixels in the filtering window. We output the centroid of the extracted cluster. We demonstrate that this graph-spectral filter can effectively reduce a mixture of Gaussian and random impulsive noise.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E94.A.457/_p
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@ARTICLE{e94-a_1_457,
author={Yu QIU, Zenggang DU, Kiichi URAHAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Graph-Spectral Filter for Removing Mixture of Gaussian and Random Impulsive Noise},
year={2011},
volume={E94-A},
number={1},
pages={457-460},
abstract={We propose, in this letter, a new type of image denoising filter using a data analysis technique. We deal with pixels as data and extract the most dominant cluster from pixels in the filtering window. We output the centroid of the extracted cluster. We demonstrate that this graph-spectral filter can effectively reduce a mixture of Gaussian and random impulsive noise.},
keywords={},
doi={10.1587/transfun.E94.A.457},
ISSN={1745-1337},
month={January},}
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TY - JOUR
TI - Graph-Spectral Filter for Removing Mixture of Gaussian and Random Impulsive Noise
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 457
EP - 460
AU - Yu QIU
AU - Zenggang DU
AU - Kiichi URAHAMA
PY - 2011
DO - 10.1587/transfun.E94.A.457
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E94-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2011
AB - We propose, in this letter, a new type of image denoising filter using a data analysis technique. We deal with pixels as data and extract the most dominant cluster from pixels in the filtering window. We output the centroid of the extracted cluster. We demonstrate that this graph-spectral filter can effectively reduce a mixture of Gaussian and random impulsive noise.
ER -