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 or float64 dtypes, the specialised function scipy.signal.medfilt2d may be faster.