### Navigation

- index
- modules |
- next |
- SciPy v0.7 Reference Guide (DRAFT) »
- Signal processing (`scipy.signal`) »

# scipy.signal.wiener

`scipy.signal.``wiener`(im, mysize=None, noise=None)

  Perform a Wiener filter on an N-dimensional array.

  Description:

  > Apply a Wiener filter to the N-dimensional array in.

  Inputs:

  > in – an N-dimensional array. kernel_size – A scalar or an N-length list giving the size of the

  > > median filter window in each dimension. Elements of kernel_size should be odd. If kernel_size is a scalar, then this scalar is used as the size in each dimension.

  > noise – The noise-power to use. If None, then noise is estimated as
  >   the average of the local variance of the input.

  Outputs: (out,)

  > out – Wiener filtered result with the same shape as in.

### Navigation

- index
- modules |
- next |
- SciPy v0.7 Reference Guide (DRAFT) »
- Signal processing (`scipy.signal`) »