In [1]:

    

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


    

In [2]:

    

im = plt.imread('testim.png')
print(im.dtype, im.shape, np.min(im), np.max(im))
plt.imshow(im)


    

    




float32 (267, 477, 3) 0.0 1.0






    
Out[2]:





<matplotlib.image.AxesImage at 0x7e76a90>






    

In [3]:

    

def contrast_adjustmenst(im, c, l):
    return (c * (im ** l))


    

In [4]:

    

plt.imshow(contrast_adjustmenst(im, 1, 0.37))


    

    
Out[4]:





<matplotlib.image.AxesImage at 0x7f5ff98>






    

In [5]:

    

plt.imshow(contrast_adjustmenst(im, 1, 1.37))


    

    
Out[5]:





<matplotlib.image.AxesImage at 0x7cbb7f0>






    

In [6]:

    

def contrast_scaling(im):
    rmax, rmin = np.max(im, axis=(0, 1)), np.min(im, axis=(0, 1))
    return (im - rmin) / (rmax - rmin)


    

In [7]:

    

im = plt.imread('testim.png')
im[im<0.2] = 0.2  # for illustration purpose
im[im>0.8] = 0.8 # for illustration purpose
plt.figure(figsize=(8, 8))
plt.subplot(121)
plt.imshow(im)
plt.subplot(122)
plt.imshow(contrast_scaling(im))


    

    
Out[7]:





<matplotlib.image.AxesImage at 0x7ff1710>






    

In [ ]: