DocumentCode :
1678684
Title :
Adaptive Wiener denoising using a Gaussian scale mixture model in the wavelet domain
Author :
Portilla, Javier ; Strela, Vasily ; Wainwright, Martin J. ; Simoncelli, Eero P.
Author_Institution :
Dept. de Ciencias de la Comput., Granada Univ., Spain
Volume :
2
fYear :
2001
Firstpage :
37
Abstract :
We describe a statistical model for images decomposed in an overcomplete wavelet pyramid. Each coefficient of the pyramid is modeled as the product of two independent random variables: an element of a Gaussian random field, and a hidden multiplier with a marginal log-normal prior. The latter modulates the local variance of the coefficients. We assume subband coefficients are contaminated with additive Gaussian noise of known covariance, and compute a MAP estimate of each multiplier variable based on observation of a local neighborhood of coefficients. Conditioned on this multiplier, we then estimate the subband coefficients with a local Wiener estimator. Unlike previous approaches, we (a) empirically motivate our choice for the prior on the multiplier; (b) use the full covariance of signal and noise in the estimation; (c) include adjacent scales in the conditioning neighborhood. To our knowledge, the results are the best in the literature, both visually and in terms of squared error
Keywords :
Gaussian noise; covariance analysis; image representation; image restoration; interference suppression; maximum likelihood estimation; wavelet transforms; Gaussian random field; Gaussian scale mixture model; MAP estimate; Wiener estimator; adaptive Wiener denoising; additive Gaussian noise; image decomposition; image representation; image restoration; log-normal prior; multiplier variable; overcomplete wavelet pyramid; statistical model; wavelet domain; Additive noise; Band pass filters; Data mining; Gaussian noise; Humans; Image restoration; Noise reduction; Probability; Wavelet domain; White noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.958418
Filename :
958418
Link To Document :
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