Bayesian Denoising of Visual Images in the Wavelet Domain

E P Simoncelli

Published in Bayesian Inference in Wavelet Based Models, pages 291--308. Springer-Verlag, 1999.
© Springer-Verlag, New York, June 1999

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    • In this chapter, we examine the empirical statistical properties of visual images within two fixed multi-scale bases, and describe two statistical models for the coefficients in these bases. The first is a non-Gaussian marginal model, previously described in [ Simoncelli96c]. The second is a joint non-Gaussian Markov model for wavelet subbands, previous versions of which have been described in [ Buccigrossi97, Simoncelli97b, Simoncelli97a]. We demonstrate the use of each of these models in Bayesian estimation of an image contaminated by additive Gaussian white noise.
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