DocumentCode :
2153335
Title :
Image Denoising With Gaussian Mixture Model
Author :
Cao, Yang ; Luo, Yupin ; Yang, Shiyuan
Volume :
3
fYear :
2008
fDate :
27-30 May 2008
Firstpage :
339
Lastpage :
343
Abstract :
In this paper, we present a Gaussian mixture model (GMM) based method for image denoising. The method partitions an image into a set of overlapping patches, and assumes that the image patches are random variables described by a GMM. The distribution parameters of the noise free image patches are estimated from the noisy parameters which are calculated by expectation maximization (EM). Minimum mean square error (MMSE) estimation technique is used to estimate the clean image patches. The experimental results show that new method can effectively suppress additive noise and preserve details of image signal.
Keywords :
Colored noise; Degradation; Filters; Gaussian distribution; Gaussian noise; Image denoising; Image processing; Noise reduction; Pixel; Principal component analysis; Expectation maximization; Gaussian mixture model; Image denoising; Minimum mean square error estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2008. CISP '08. Congress on
Conference_Location :
Sanya, China
Print_ISBN :
978-0-7695-3119-9
Type :
conf
DOI :
10.1109/CISP.2008.312
Filename :
4566502
Link To Document :
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