Given  a  grayscale  image,  its  histogram  consists  of  the  histogram  of  its  gray  levels;  that  is,  a  graph indicating the number of times each gray level occurs in the image.
 
We can infer a great deal about the appearance of an image from its histogram.
• In a dark image, the gray levels would be clustered at the lower end
• In a uniformly bright image, the gray levels would be clustered at the upper end.
• In a well contrasted image, the gray levels would be well spread out over much of the range.

Here is the Matlab Implementation:

function task1
a=imread('coins.png');
subplot(1,2,1)
imshow(a);
prob=zeros(1,255);
[r c]=size(a);
for h=1:255
 for i=1:1:r
 for j=1:1:c
 if (a(i,j)==h)
 prob(h)=prob(h)+1;
 end
 end
 end
end
subplot(1,2,2)
stem(prob)

Enjoy..!!!

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