2pm, Thursday 21, September 2006
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Statistical Modeling of Images with Fields of Gaussian Scale Mixtures

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Siwei Lyu
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The local statistical properties of photographic images,
when represented in a multi-scale basis, have been described using
scale mixtures of Gaussians (GSM).  Here, we use this local
description to construct a global field of Gaussian scale mixtures
(FoGSM) model.  Specifically, we model subbands of wavelet
coefficients as a product of a homogeneous Gaussian Markov random
field (hGMRF) and a second, exponentiated, hGMRF.  We show that
parameter estimation for FoGSM is feasible, and that samples drawn
from an estimated FoGSM model have marginal and joint statistics
similar to wavelet coefficients of photographic images.  We develop an
algorithm for image denoising based on the FoGSM model, and
demonstrate significant improvements over current state-of-the-art
denoising method based on the local GSM model.


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