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:

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

See also

scipy.ndimage.median_filter

scipy.signal.medfilt2d

Notes

Array API Standard Support

medfilt has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	✅
PyTorch	✅	⛔
JAX	⚠️ no JIT	⛔
Dask	⚠️ computes graph	n/a

See Support for the array API standard for more information.