histogram_equalization.py

from __future__ import division
import matplotlib.pyplot as plt
import numpy as np
from skimage import io, color, img_as_float

def histogram_equalization(A):
    rows = A.shape[0]
    columns = A.shape[1]
    histogram, bin_edges = np.histogram(A.flatten(), range=(0, 1), bins=256)
    histogram = histogram/np.max(histogram)
    c = histogram.cumsum()
    c = c/np.max(c)

    B = 255*A.copy()
    for i in xrange(rows):
        for j in xrange(columns):
           B[i, j] = c[B[i, j]]

    return B


def histogram_equalization_colour(A):
    B = A.copy()
    B[:, :, 0] = histogram_equalization(B[:, :, 0])
    B[:, :, 1] = histogram_equalization(B[:, :, 1])
    B[:, :, 2] = histogram_equalization(B[:, :, 2])

    return B


def histogram_equalization_point_transformation(A):
    B = A.copy()
    P1 = B[:, :, 0]
    P2 = B[:, :, 1]
    P3 = B[:, :, 2]
    G = (np.sum(B * (1/3, 1/3, 1/3), axis=2))/255

    rows = G.shape[0]
    columns = G.shape[1]
    histogram, bin_edges = np.histogram(G.flatten(), range=(0, 1), bins=256)
    histogram = histogram/histogram.max()
    c = histogram.cumsum()
    c = c/c.max()

    P1 = 255*P1
    P2 = 255*P2
    P3 = 255*P3
    for i in xrange(rows):
        for j in xrange(columns):
           P1[i, j] = c[P1[i, j]]
           P2[i, j] = c[P2[i, j]]
           P3[i, j] = c[P3[i, j]]

    return B
    

def rgb_hsi_conversion_equalize(A):
    B = A.copy()
    B = color.rgb2hsv(B)
    B[:, :, 0] = histogram_equalization(B[:, :, 0])
    B[:, :, 1] = histogram_equalization(B[:, :, 1])
    B[:, :, 2] = histogram_equalization(B[:, :, 2])
    B = color.hsv2rgb(B)
   
    return B


def rgb_hsi_conversion_equalizeI(A):
    B = A.copy()
    B = color.rgb2hsv(B)
    B[:, :, 2] = histogram_equalization(B[:, :, 2])
    B = color.hsv2rgb(B)

    return B


A = img_as_float(io.imread('spaghetti.jpg', plugin='pil'))

out = histogram_equalization_colour(A)
out1 = histogram_equalization_point_transformation(A)
out2 = rgb_hsi_conversion_equalize(A)
out3 = rgb_hsi_conversion_equalizeI(A)

f0, (ax0, ax1) = plt.subplots(1, 2)
f0.tight_layout()

ax0.imshow(A)
ax0.set_title('Input image')

ax1.imshow(out)
ax1.set_title('Histogram equalization on each colour panel seperately')

f1, (ax0, ax1) = plt.subplots(1, 2)
f1.tight_layout()

ax0.imshow(A)
ax0.set_title('Input image')

ax1.imshow(out1)
ax1.set_title('Histogram equalization point transformation applied to R, G and B panels')

f2, (ax0, ax1) = plt.subplots(1, 2)
f2.tight_layout()

ax0.imshow(A)
ax0.set_title('Input image')

ax1.imshow(out2)
ax1.set_title('Histogram equalization on the H, S and I panels')

f3, (ax0, ax1) = plt.subplots(1, 2)
f3.tight_layout()

ax0.imshow(A)
ax0.set_title('Input image')

ax1.imshow(out3)
ax1.set_title('Histogram equalization on the I-panel')

plt.show()