richardson_lucy(image, psf, iterations=50, clip=True)
Input degraded image (can be N dimensional).
The point spread function.
Number of iterations. This parameter plays the role of regularisation.
True by default. If true, pixel value of the result above 1 or under -1 are thresholded for skimage pipeline compatibility.
The deconvolved image.
Richardson-Lucy deconvolution.
>>> from skimage import color, data, restorationSee :
... 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)
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.restoration.deconvolution.richardson_lucy
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