skimage 0.17.2

ParametersReturnsBackRef
richardson_lucy(image, psf, iterations=50, clip=True)

Parameters

image : ndarray

Input degraded image (can be N dimensional).

psf : ndarray

The point spread function.

iterations : int, optional

Number of iterations. This parameter plays the role of regularisation.

clip : boolean, optional

True by default. If true, pixel value of the result above 1 or under -1 are thresholded for skimage pipeline compatibility.

Returns

im_deconv : ndarray

The deconvolved image.

Richardson-Lucy deconvolution.

Examples

This example is valid syntax, but we were not able to check execution
>>> from skimage import color, data, restoration
... camera = color.rgb2gray(data.camera())
... from scipy.signal import convolve2d
... psf = np.ones((5, 5)) / 25
... camera = convolve2d(camera, psf, 'same')
... camera += 0.1 * camera.std() * np.random.standard_normal(camera.shape)
... deconvolved = restoration.richardson_lucy(camera, psf, 5)
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.restoration.deconvolution.richardson_lucy

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


File: /skimage/restoration/deconvolution.py#329
type: <class 'function'>
Commit: