% Title:  Histogram Equalization Simulation
%
% Author: Ronald Bazillion
%
% Module Description:
%
% This simulation performs histogram equalization on an input image.
% Histogram equalization is used in many signal processing applications
% to enhance images so that certain characteristics of an image which might
% have appeared too dark or too light in the original image will show up 
% in the enhanced image. The procedure of equalization is shown below:
%
% 1) Obtain the histogram of the image.
% 2) Calculate the normalized sum of the histogram. This is the Cumulative
%    Density Function (CDF) or the Translation function T(r)
% 3) Reconstruct the image using the Translation function T(r).
%
% The remapped intensity values are calculated by:
%
%        k
%      -----
% Sk = \      Ni / N       where Ni = number of occurances of intensity
%      /                              level i
%      -----                     N = Number of pixels in image
%       i=0

clear

NUM_OF_BITS = 8;
max_value = 2^NUM_OF_BITS; % maximum value used in image
input = imread('f:/ron_b/images/opajess.jpg','jpg'); %read in the image
rowsize = size(input,1); 
colsize = size(input,2);
d_input = double(input); %convert to double precision
hist_data = zeros(max_value,1); %create histogram bin
mp = linspace(0,1,256); %linespace used for color-mapping images
mp = [mp' mp' mp'];


for r = 1:rowsize               %calculate global histogram of image. The bin houses
   for s = 1:colsize            %the number of occurances of values ranged 0-255.
      for t = 1:max_value       
         if (d_input(r,s) == t-1)
            hist_data(t) = hist_data(t) + 1;
         end
      end
   end
end
        
for i=1:max_value %Obtain Cumulative Density Function (CDF)
   if i==1
      new_hist(i,1) = hist_data(i,1);
   else
      new_hist(i,1) = (new_hist(i-1,1)+ hist_data(i,1));
   end
end

normalization = (max_value)/(rowsize*colsize); %calculate normalization
new_hist = new_hist .* normalization; %normalize CDF
new_hist = round(new_hist); %round CDF to nearest integer

for i=1:rowsize  % reconstruct new image using translation function
   for j = 1:colsize
      vector = double(input(i,j));
      new_image(i,j) = new_hist(vector+1);
   end
end

%plot histograms and images
figure(1),hist(d_input,max_value),title('Histogram of original image');
figure(2),hist(new_image,max_value),title('Histogram of equalized image');
figure(3),plot(new_hist),title('Plot of CDF function');
figure(4),image(input),title('original image'),colormap(mp);
figure(5),image(new_image),title('equalized image'),colormap(mp);

%create image file of enhanced image
%new_image = uint8(new_image); %convert to unsigned 8-bit integer
%imwrite(new_image,'c:/MATLABR11/bin/images/new_image.jpg','jpg');<!--'"</title></head>-->

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