medfilt(volume, kernel_size=None)
Apply a median filter to the input array using a local window-size given by :None:None:`kernel_size`. The array will automatically be zero-padded.
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.
An N-dimensional input array.
A scalar or an N-length list giving the size of the median filter window in each dimension. Elements of :None:None:`kernel_size` should be odd. If :None:None:`kernel_size` is a scalar, then this scalar is used as the size in each dimension. Default size is 3 for each dimension.
An array the same size as input containing the median filtered result.
Perform a median filter on an N-dimensional array.
If array size is smaller than kernel size along any dimension
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._signaltools.medfilt2d
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them