Programming_Assignment 1.3

# -*- coding: utf-8 -*-
"""
Created on Wed Aug 31 16:29:33 2016
Reference: opencvpython.blogspot.com/2013/03/histograms-2-histogram-equalization.html
@author: sriharsha
"""

import cv2
import numpy as np
from matplotlib import pyplot as plt 
img = cv2.imread('Fig0228(a)(angiography_mask_image).tif')
cv2.imshow('Mask_image',img)
cv2.waitKey(100)
img1 = cv2.imread('Fig0228(b)(angiography_live_ image).tif')
cv2.imshow('live_image',img1)
cv2.waitKey(100)
diff = cv2.subtract(img,img1)
diff = np.absolute(diff-175)
[X,Y,Z]=diff.shape
#diff = cv2.resize(Diff,(2*X,2*Y))
cv2.imshow('Difference_2images',diff)
cv2.waitKey(1000)
cv2.imwrite('Digital subtraction Angiography.tif',diff)
#equ = cv2.equalizeHist(Diff)
#res = np.hstack(diff,equ)
#cv2.imwrite('res.tif',res)

# numpy implementation
hist,bins = np.histogram(diff.flatten(),256,[0,256])
cdf = hist.cumsum()
cdf_normalized = cdf*hist.max()/cdf.max() # this line is not necessary
plt.plot(cdf_normalized,color='b')
plt.hist(diff.flatten(),256,[0,256],color='r')
plt.xlim([0,256])
plt.legend(('cdf','histogram'),loc='upper left')
plt.show()
cdf_m = np.ma.masked_equal(cdf,0)
cdf_m = (cdf_m-cdf_m.min())*255/(cdf_m.max()-cdf_m.min())
cdf = np.ma.filled(cdf_m,0).astype('uint8')
img2 = cdf[diff]
cv2.imshow('img2',img2)
cv2.waitKey()