Wiener Filter for image deblur

Question

I am trying to implement the Wiener Filter to perform deconvolution on blurred image. My implementation is like this

import numpy as np
from numpy.fft import         


        

Answer 1

For data comparison, you can find a sample implementation of Wiener filtering and unsupervisived Wiener filtering at

http://scikit-image.org/docs/dev/auto_examples/plot_restoration.html

If you give your original image data, we may be able to help further.

EDIT: Original link seems to be down, try this one: http://scikit-image.org/docs/dev/auto_examples/filters/plot_restoration.html

Answer 2

Use skimage.restoration.wiener, which is usually used like:

>>> from skimage import color, data, restoration
>>> img = color.rgb2gray(data.astronaut())
>>> from scipy.signal import convolve2d
>>> psf = np.ones((5, 5)) / 25
>>> img = convolve2d(img, psf, 'same')
>>> img += 0.1 * img.std() * np.random.standard_normal(img.shape)
>>> deconvolved_img = restoration.wiener(img, psf, 1100)

I have also used it in: Deblur an image using scikit-image.

Answer 3

We could try unsupervised weiner too (deconvolution with a Wiener-Hunt approach, where the hyperparameters are automatically estimated, using a stochastic iterative process (Gibbs sampler), as described here):

deconvolved, _ = restoration.unsupervised_wiener(im, psf)