scipy.signal.medfilt#
- scipy.signal.medfilt(volume, kernel_size=None)[source]#
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:
- volumearray_like
An N-dimensional input array.
- kernel_sizearray_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:
- outndarray
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
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
orfloat64
dtypes, the specialised functionscipy.signal.medfilt2d
may be faster.