Graph-Spectral Filter for Removing Mixture of Gaussian and Random Impulsive Noise

Yu QIU  Zenggang DU  Kiichi URAHAMA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E94-A   No.1   pp.457-460
Publication Date: 2011/01/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E94.A.457
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Image
Keyword: 
graph-spectral method,  image denoising,  mixed noise,  clustering filter,  

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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.