Bayesian Denoising of Visual Images in the Wavelet Domain
In:
Bayesian Inference in Wavelet Based Models.
eds. P Müller and B Vidakovic.
Chapter 18, pages 292-308.
Lecture Notes in Statistics, vol 141
© Springer-Verlag, New York, June 1999.
Related journal article:
Image denoising using a scale mixture of Gaussians in the wavelet domain, Fall 2003.
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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