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.