In [1]:

    

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt


    

In [2]:

    

im = plt.imread('testim3.png')
plt.imshow(im)


    

    
Out[2]:





<matplotlib.image.AxesImage at 0x7e12828>






    

In [3]:

    

def contrast_scaling(im, addNoise=False):
    im2 = im + np.random.normal(0, 0.25, im.shape) if addNoise else im
    rmin, rmax = np.min(im, axis=(0, 1)), np.max(im, axis=(0, 1))
    return (im2 - rmin) / (rmax - rmin)
    
plt.imshow(contrast_scaling(im, addNoise=True))


    

    
Out[3]:





<matplotlib.image.AxesImage at 0x764f9e8>






    

In [4]:

    

K = 64
im2 = np.zeros_like(im)
for i in range(K):
    im2 += contrast_scaling(im, addNoise=True)
plt.imshow(contrast_scaling(im2/K))


    

    
Out[4]:





<matplotlib.image.AxesImage at 0x81ba630>