Лаба 3(6) КГ

import numpy as np
import matplotlib.pyplot as plt

from scipy.signal import convolve2d as conv2
from scipy import misc
from tkinter.filedialog import askopenfilename
from skimage import color, data, restoration

def RL_deconv(image, PSF, iterations):
    latent_est = image
    PSF_HAT = PSF[::-1,::-1]
    for i in range(1,iterations):
        est_conv      = conv2(latent_est,PSF,'same');
        relative_blur = image/est_conv;
        error_est     = conv2(relative_blur,PSF_HAT,'same');
        latent_est    = latent_est* error_est;
    result = latent_est;
    return result

#astro = color.rgb2gray( misc.imread(askopenfilename()))
astro = color.rgb2gray(data.astronaut())


psf = np.ones((5, 5)) / 25
astro = conv2(astro, psf, 'same')
# Add Noise to Image
astro_noisy = astro.copy()
astro_noisy += (np.random.poisson(lam=25, size=astro.shape) - 10) / 255.

# Restore Image using Richardson-Lucy algorithm
#deconvolved_RL = restoration.richardson_lucy(astro_noisy, psf, iterations=30)
deconvolved_RL = RL_deconv(astro_noisy, psf, iterations=30)

fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(8, 5))
plt.gray()

for a in (ax[0], ax[1], ax[2]):
       a.axis('off')

ax[0].imshow(astro)
ax[0].set_title('Исходное изображение')

ax[1].imshow(astro_noisy)
ax[1].set_title('Зашумленное изображение')

ax[2].imshow(deconvolved_RL, vmin=astro_noisy.min(), vmax=astro_noisy.max())
ax[2].set_title('Восстановление при помощи\n алгоритма Люси-Ричардсона')


fig.subplots_adjust(wspace=0.02, hspace=0.2,
                    top=0.9, bottom=0.05, left=0, right=1)
plt.show()