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2008

Image Restoration Using Space-Variant Gaussian Scale Mixtures in Overcomplete Pyramids

8 years 8 months ago
Image Restoration Using Space-Variant Gaussian Scale Mixtures in Overcomplete Pyramids
In recent years Bayes Least Squares - Gaussian scale mixtures (BLS-GSM) has emerged as one of the most powerful methods for image restoration. Its strength relies on providing a simple and yet very effective local statistical description of oriented pyramid coefficient neighborhoods via a GSM vector. This can be viewed as a fine adaptation of the model to the signal variance at each scale, orientation and spatial location. Here we present an enhancement of the model by introducing a coarser adaptation level, where a larger neighborhood is used to estimate the local signal covariance within every subband. We formulate our model as a Bayes least squares estimator using space-variant Gaussian scale mixtures. The model can be also applied to image deconvolution, by first performing a global blur compensation, and then doing local adaptive denoising. We demonstrate through simulations that the proposed method, besides being model-based and non-iterative, it is also robust and efficient. Its...
Jose A. Guerrero-Colon, Luis Mancera, Javier Porti
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where TIP
Authors Jose A. Guerrero-Colon, Luis Mancera, Javier Portilla
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