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OFAI-TR-2012-07 ( 290kB PDF file)

Persistent Empirical Wiener Estimation With Adaptive Threshold Selection For Audio Denoising

Kai Siedenburg

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.

Keywords: Audio denoising

Citation: Siedenburg K.: Persistent Empirical Wiener Estimation With Adaptive Threshold Selection For Audio Denoising, Proceedings of the 9th Sound and Music Computing Conference (SMC 2012), Copenhagen, Denmark, 2012.