Wavelet shrinkage with correlated wavelet coefficients
نویسندگان
چکیده
This paper investigates the statistical characterization of multiscale wavelet coefficients corresponding to random signals and images. Virtually all approaches to wavelet shrinkage model the wavelet coefficients as independent; we challenge that assumption and demonstrate several cases where substantial correlations may be present in the wavelet domain. In particular, the correlation between scales can be surprisingly substantial, even for pixels separated by several scales. Our goal, initiated in this paper, is to develop an efficient random field model describing these statistical correlations, and demonstrate its effectiveness in the context of Bayesian wavelet shrinkage for signal and image denoising.
منابع مشابه
Bayesian Wavelet Shrinkage
Bayesian wavelet shrinkage methods are defined through a prior distribution on the space of wavelet coefficients after a Discrete Wavelet Transformation has been applied to the data. Posterior summaries of the wavelet coefficients establish a Bayes shrinkage rule. After the Bayes shrinkage is performed, an Inverse Discrete Wavelet Transformation can be used to recover the signal that generated ...
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