wiener(data, impulse_response=None, filter_params={}, K=0.25, predefined_filter=None)

Other Parameters

predefined_filter : LPIFilter2D

If you need to apply the same filter multiple times over different images, construct the LPIFilter2D and specify it here.

Parameters

data : (M,N) ndarray

Input data.

K : float or (M,N) ndarray

Ratio between power spectrum of noise and undegraded image.

impulse_response : callable `f(r, c, **filter_params)`

Impulse response of the filter. See LPIFilter2D.__init__.

filter_params : dict

Additional keyword parameters to the impulse_response function.

Minimum Mean Square Error (Wiener) inverse filter.

Examples

See :

Local connectivity graph

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

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File: /skimage/filters/lpi_filter.py#207
type: <class 'function'>
Commit: