In [1]:

    

%matplotlib inline

import numpy as np
from matplotlib import pyplot as plt


    

In [2]:

    

from scipy.ndimage.filters import gaussian_filter

def smooth_noise(shape, sigma):
    return gaussian_filter(np.random.normal(size=shape),sigma)

shape = (500,500)

S1 = smooth_noise(shape, 8)
S2 = smooth_noise(shape, 32)

fig, (ax1, ax2) = plt.subplots(ncols=2,figsize=(12,12))

ax1.imshow(S1)
ax2.imshow(S2)


    

    
Out[2]:





<matplotlib.image.AxesImage at 0x7f9cc0041c50>






    

In [3]:

    

from skimage.filter import threshold_otsu

fig, (ax1, ax2) = plt.subplots(ncols=2,figsize=(12,12))

S1t = S1 > threshold_otsu(S1)
S2t = S2 > threshold_otsu(S2)

ax1.imshow(S1t, cmap='gray')
ax2.imshow(S2t, cmap='gray')


    

    
Out[3]:





<matplotlib.image.AxesImage at 0x7f9caa094950>