richardson-lucy

richardson_lucy

skimage.restoration.richardson_lucy(image, psf, iterations=50, clip=True) [source]

Richardson-Lucy deconvolution.

Parameters:	image : ndarray Input degraded image (can be N dimensional). psf : ndarray The point spread function. iterations : int 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.

References

[R336]

http://en.wikipedia.org/wiki/Richardson%E2%80%93Lucy_deconvolution

Examples

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>>> 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)