histogram_equalization.py

gistfile1.txt

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
    
A = img_as_float(io.imread('spaghetti.jpg', plugin='pil'))
out1 = histogram_equalization_point_transformation(A)

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')