Histogram deviation or MDMF
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I am trying to calculate the histogram deviation(H.D) or Maximum Deviation Measuring Factor(M.D.M.F) as mentioned in
Two coding,I have done.one is
clear all
close all
clc
plain = imread('lena.bmp');% Read the input image
[M N] = size(plain);
r = uint8(randi([0,256],M,N)); % Generate a random matrix for encryption
cipher = bitxor(plain,r); % Encryption
% x = double(plain);
% y = double(cipher);
x = plain;
y = cipher;
x1 = imhist(x);
y1 = imhist(y);
%then calculate the difference between the two
diff = abs(x1-y1);
%then calculate D as follows
D1 = 0;
for i = 2:255
D1 = D1+diff(i);
end;
D2 = (diff(1)+diff(256))/2;
MDMF = D1+D2/(M*N)
and the other is
clear all
close all
clc
plain = imread('lena.bmp');% Read the input image
[M N] = size(plain);
r = uint8(randi([0,256],M,N)); % Generate a random matrix for encryption
cipher = bitxor(plain,r); % Encryption
% x = double(plain);
% y = double(cipher);
x = plain;
y = cipher;
hi = imhist(x);
hr = imhist(y);
subplot(211)
imhist(x);
title('Histogram of Original Image')
subplot(212)
imhist(y);
title('Histogram of Encrypted Image')
diff = imabsdiff(hi,hr);
% z = abs(hi-hr);
d = ((diff(1)+diff(256))/2);
d1 = sum(diff(2:255));
histogram_deviation = (d+d1)/(256*256)
Please help me to identify which code is correct according to the theoretical concepts
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