Wavelet de-noising for highly noisy source separation
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This correspondence addresses the recovery of an image from its multiple noisy copies. The standard method is to compute the weighted average of these copies. Since the wavelet thresholding technique has been shown to effectively denoise a single noisy cop ...
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This paper addresses the source separation in strong noisy mixtures by wavelet de-noising processing. Experiments include the cases of white/correlated Gaussian and non- Gaussian noise, which correspond to various applications. The performance of BSS/ICA a ...
The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresh- olding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distr ...
The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on developing the best uniform threshold or best basis selection. However, not ...
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