`skimage.restoration.deconvolution:richardson_lucy`

source: /dev/scikit-image/src/skimage/restoration/deconvolution.py :359

Signature

   def     richardson_lucy (    image    ,    psf    ,    num_iter    =  50   ,    clip    =  True   ,    filter_epsilon    =  None     )

Summary

Richardson-Lucy deconvolution.

Parameters

image : ([P, ]M, N) ndarray: Input degraded image (can be n-dimensional). If you keep the default clip=True parameter, you may want to normalize the image so that its values fall in the [-1, 1] interval to avoid information loss.
psf : ndarray: The point spread function.
num_iter : int, optional: Number of iterations. This parameter plays the role of regularisation.
clip : bool, optional: True by default. If true, pixel value of the result above 1 or under -1 are thresholded for skimage pipeline compatibility.
filter_epsilon : float, optional: Value below which intermediate results become 0 to avoid division by small numbers.

Returns

im_deconv : ndarray: The deconvolved image.

Examples

from skimage import img_as_float, data, restoration
camera = img_as_float(data.camera())
from scipy.signal import convolve2d
psf = np.ones((5, 5)) / 25
camera = convolve2d(camera, psf, 'same')
rng = np.random.default_rng()
camera += 0.1 * camera.std() * rng.standard_normal(camera.shape)
deconvolved = restoration.richardson_lucy(camera, psf, 5)

✓

Aliases

skimage.restoration.richardson_lucy