Graph-Spectral Filter for Removing Mixture of Gaussian and Random Impulsive Noise
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E94-A No.1 pp.457-460
- Publication Date
- 2011/01/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E94.A.457
- Type of Manuscript
- LETTER
- Category
- Image
Authors
Keyword
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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 -
English
