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_filterhas a more efficient implementation of a median filter and therefore runs much faster.- For 2-dimensional images with - uint8,- float32or- float64dtypes, the specialised function- scipy.signal.medfilt2dmay be faster.