Appliquer un filtre médian sur une image avec du buit avec python

Exemple d'implémentation d'un filtre médian sur une image avec du buit avec python

from scipy import misc

import numpy as np
import matplotlib.pyplot as plt

import matplotlib.image as mpimg

#M = mpimg.imread('lena.png') 
M = mpimg.imread('lena_grayscale.png')

print M.shape, type(M)
print M

salt_value = 40

noise = np.random.randint(salt_value+1, size=(512, 512))

#---------- Add Noise ----------#

indexe = np.where(noise == 0)

A = indexe[0]
B = indexe[1]

M[A,B,0] = 0.0
M[A,B,1] = 0.0
M[A,B,2] = 0.0

#---------- Plot & Save ----------#

print M.shape

my_dpi=100

fig = plt.figure(figsize=(800/my_dpi, 800/my_dpi), dpi=my_dpi)

ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)

plt.imshow(M)   
plt.title("Noisy Lena Image")
plt.savefig("lena_noisy_NoAxis.png", dpi=my_dpi)
plt.show()



plt.imshow(M)   
plt.title("Noisy Lena Image")
plt.savefig("lena_noisy.png",bbox_inches='tight')


#---------- Median Filter ----------#

shape = M.shape

n_pixel = np.zeros((9))

for i in range(shape[0]-1):
    for j in range(shape[1]-1):
        if j > 0 and i > 0:
            n_pixel[0] = M[i-1,j-1,0]
            n_pixel[1] = M[i-1,j,0]
            n_pixel[2] = M[i-1,j+1,0]
            n_pixel[3] = M[i,j-1,0]
            n_pixel[4] = M[i,j,0]
            n_pixel[5] = M[i,j+1,0]
            n_pixel[6] = M[i+1,j-1,0]
            n_pixel[7] = M[i+1,j,0]
            n_pixel[8] = M[i+1,j+1,0]
            s = np.sort(n_pixel, axis=None)  
            M[i,j,0] = s[4]
            M[i,j,1] = s[4]
            M[i,j,2] = s[4]


plt.imshow(M)   
plt.title("Median Filter")
plt.savefig("MedianFilterLena.png",bbox_inches='tight')
plt.show()

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