histogram_equalization_color

gistfile1.txt

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, range=(0,1), bins=255)
    c = (np.cumsum(histogram/np.max(histogram)))*255
    c = c/c[-1]
   
    for i in xrange(0, rows):
        for j in xrange(0, columns):
            A[i,j] = c[A[i, j]]

    return A


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

    return A

#def histogram_equalization_point_transformation(A):


  #  return A

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

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

    return A


A = img_as_float(io.imread('spaghetti.jpg', plugin='pil'))
C = np.empty_like(A)
C[:] = A

D = np.empty_like(A)
D[:] = A

E = np.empty_like(A)
E[:] = A


out = histogram_equalization_colour(A)
#out1 = 
out2 = rgb_hsi_conversion_equalize(D)
out3 = rgb_hsi_conversion_equalizeI(E)

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

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

ax1.imshow(out)
ax1.set_title('')

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

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

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

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-image')

plt.show()