It is the re-distribution of gray level values uniformly. Let’s consider a 2 dimensional image which has values ranging between 0 and 255.
MATLAB CODE:
GIm=imread('tire.tif');
numofpixels=size(GIm,1)*size(GIm,2);
figure,imshow(GIm);
title('Original Image');
HIm=uint8(zeros(size(GIm,1),size(GIm,2)));
freq=zeros(256,1);
probf=zeros(256,1);
probc=zeros(256,1);
cum=zeros(256,1);
output=zeros(256,1);
%freq counts the occurrence of each pixel value.
%The probability of each occurrence is calculated by probf.
for i=1:size(GIm,1)
for j=1:size(GIm,2)
value=GIm(i,j);
freq(value+1)=freq(value+1)+1;
probf(value+1)=freq(value+1)/numofpixels;
end
end
sum=0;
no_bins=255;
%The cumulative distribution probability is calculated.
for i=1:size(probf)
sum=sum+freq(i);
cum(i)=sum;
probc(i)=cum(i)/numofpixels;
output(i)=round(probc(i)*no_bins);
end
for i=1:size(GIm,1)
for j=1:size(GIm,2)
HIm(i,j)=output(GIm(i,j)+1);
end
end
figure,imshow(HIm);
title('Histogram equalization');
%The result is shown in the form of a table
figure('Position',get(0,'screensize'));
dat=cell(256,6);
for i=1:256
dat(i,:)={i,freq(i),probf(i),cum(i),probc(i),output(i)};
end
columnname = {'Bin', 'Histogram', 'Probability', 'Cumulative histogram','CDF','Output'};
columnformat = {'numeric', 'numeric', 'numeric', 'numeric', 'numeric','numeric'};
columneditable = [false false false false false false];
t = uitable('Units','normalized','Position',...
[0.1 0.1 0.4 0.9], 'Data', dat,...
'ColumnName', columnname,...
'ColumnFormat', columnformat,...
'ColumnEditable', columneditable,...
'RowName',[]);
subplot(2,2,2); bar(GIm);
title('Before Histogram equalization');
subplot(2,2,4); bar(HIm);
title('After Histogram equalization');
Contact:
Mr. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +91-7276355704
Email: roshanphelonde@rediffmail.com
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