# scipy.signal.medfilt

scipy.signal.medfilt(volume, kernel_size=None)

  Perform a median filter on an N-dimensional array.

  Apply a median filter to the input array using a local window-size given by kernel_size. The array will automatically be zero-padded.

  Parameters
    volume array_like

      An N-dimensional input array.

    kernel_size array_like, optional

      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. Default size is 3 for each dimension.

  Returns
    out ndarray

      An array the same size as input containing the median filtered result.

  Warns
    UserWarning

      If array size is smaller than kernel size along any dimension

  See also

  `scipy.ndimage.median_filter`
  `scipy.signal.medfilt2d`

  Notes

  The more general function `scipy.ndimage.median_filter` has a more efficient implementation of a median filter and therefore runs much faster.

  For 2-dimensional images with `uint8`, `float32` or `float64` dtypes, the specialised function `scipy.signal.medfilt2d` may be faster.

scipy.signal.order_filter scipy.signal.medfilt2d