scipy.signal.wiener for audio processing
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  The Wiener filter is a simple deblurring filter for denoising images. This is not the Wiener filter commonly described in image reconstruction problems but instead it is a simple, local-mean filter. Let $x$ be the input signal, then the output is
  $$
y = \left\{  \begin{array}{cl} \frac{\sigma^2}{\sigma_x^2} m_x + ( 1 - \frac{\sigma^2}{\sigma_x^2}) x &amp; \sigma_x^2 \ge \sigma^2\\  
m_x &amp; \sigma_x^2 \lt \sigma^2
\end{array} \right.
$$
  where $m_{x}$ is the local estimate of the mean and $\sigma_{x}^{2}$ is the local estimate of the variance. The window for these estimates is an optional input parameter (default is $3\times3$ ). The parameter $\sigma^{2}$ is a threshold noise parameter. If $\sigma$ is not given then it is estimated as the average of the local variances.