Abstract:

Exploiting the persistence properties of signals leads to significant improvements in audio denoising. This contribution derives a novel denoising operator based on neighborhood smoothed, Wiener filter like shrinkage. Relations to the sparse denoising approach via thresholding are drawn. Further, a rationale for adapting the threshold level to a performance criterion is developed. Using a simple but efficient estimator of the noise level, the introduced operators with adaptive thresholds are demonstrated to act as attractive alternatives to the state of the art in audio denoising.