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');
To find the histogram of an Image: http://angeljohnsy.blogspot.com/2011/06/histogram-of-image.html
Local histogram equalization of an Image: http://angeljohnsy.blogspot.com/2011/06/local-histogram-equalization.html
Local histogram equalization of an Image: http://angeljohnsy.blogspot.com/2011/06/local-histogram-equalization.html
Here is a simple Version of Histogram Equalization MATLAB CODE:
%Read a grayscale Image or a matrix mxn
A=imread('tire.tif');
figure,imshow(A);
%Specify the bin range[0 255]
bin=255;
%Find the histogram of the image.
Val=reshape(A,[],1);
Val=double(Val);
I=hist(Val,0:bin);
%Divide the result by number of pixels
Output=I/numel(A);
%Calculate the Cumlative sum
CSum=cumsum(Output);
%Perform the transformation S=T(R) where S and R in the range [ 0 1]
HIm=CSum(A+1);
%Convert the image into uint8
HIm=uint8(HIm*bin);
figure,imshow(HIm);
its nice that this space provides output too..and most importantly..the code works!!unlike most of the other sites!
ReplyDelete-thank u soo much for this code.
good, very good
ReplyDeleteA graphical representation which shows a visual impression of the distribution of data termed as Histogram . Histograms consists of tabular frequencies which are shown as adjacent rectangles, with an area equal to the frequency of the observations in the interval.
ReplyDelete@cool_images
ReplyDeletejust change the original image to gray-scale value, because the error occur and mention that only 2D
i had change in the end of the code as follows:
GIm1=rgb2gray(GIm);
subplot(2,2,2);
bar(GIm1);
title('Before Histogram equalization');
subplot(2,2,4);
bar(HIm);
title('After Histogram equalization');
Nice.... its very helpful
ReplyDeletecan i know, what is that mean with 1 and 2 in this code?
ReplyDeletenumofpixels=size(GIm,1)*size(GIm,2);
thanks.. ^^
@sumi
ReplyDeleteit represents the dimensions. For a matrix, 1 represents rows and 2 represents columns.
This is very nice tutorial here. Can you provide me with the code for CLAHE.
ReplyDeleteIs there a bit problem with code, because max value of uint8 is 255, then
ReplyDeletefreq(value+1)=freq(value+1)+1;
cannot apply for the case value = 255. Further more, you set max gray value is 255, it is only right in almost case, not all case.
@socksau
ReplyDeleteIn matlab, the array range can start from 1. So the actual range 0 to 255 is mapped as 1 to 256.
can anybody give me code of face recognition system using k-means clustering algorithm and PCA .
ReplyDeleteAfter changing image to grayscale also, the last output is not working.. uitable is showing as unrecognised parameter : units.
ReplyDelete@Aaron Angel 1 means rows and 2 means columns of the image
ReplyDeletei really doint understand how the freq funtion works someone care to explain?
ReplyDeletewhether histogram functions can be applied to rgb image or only to gray scale???
ReplyDeletenice, could you generalize median filter to any size of the window?
ReplyDeleteLove this blog. :) Good stuff! Keep it up!
ReplyDeleteUPLOAD SAME KIND PROBLEMS
ReplyDeleteCAN U GIVE ME CODE FOR COMPARING TWO IMAGES IN MATLAB I WANT TO DETECT FAULT IN FABRIC
ReplyDeleteCan you give me code for IMAGE FUSION using Improved Synthetic Variable Ratio method? Please sir...
ReplyDeletefreq=zeros(256,1);
ReplyDeleteprobf=zeros(256,1);
probc=zeros(256,1);
cum=zeros(256,1);
output=zeros(256,1);
what is the meaning of each line above??, please quick answer :) :)
@ahmed ali
ReplyDeletePre-allocation of the vectors or 1D arrays. The gray level is[0 255] so there are 256 elements in total.
how to write a function to equilize a 100-by-100 image of normal random numbers with mean 128 and std-dev of 50.
ReplyDeletecan anybody provide full coding for image enhancement using histogram equalizatio..its urgent
ReplyDeletehistogram are also found different from that obtained from imhist(histeq(HIm))
ReplyDeletehow about GIm,3 and GIm,4?
ReplyDeleteHow do i get the rgb for the pic?
its amazing; help us with a similar code for bi-histogram equalization also
ReplyDeleteI think there is an error with code "freq(value+1)=freq(value+1)+1" for the case value=255; when value=255, freq(value+1),that is, freq(256) cannot count correctly. freq(256) always gets "0" regardless of how i and j vary, instead freq(255) counts correctly. You may check the workspace for value of freq and compare the values of freq with that from the function imhist in Matlab.
ReplyDeleteCan i get a matlab code for multi peak generalized histogram equalisation?
ReplyDeletethis blog is just awesome :)
ReplyDeletei need program for comparing two images in face detection
ReplyDeleteThis code does NOT work. Yes, because the newest Matlab version RECOMMEND the use of HISTOGRAM instead of HIST (see: I=hist(Val,0:bin ). And, by using I = histogram (Val, 0:bin) you get the following error:
ReplyDeleteUndefined operator '/' for input arguments of type 'matlab.graphics.chart.primitive.Histogram'.
Error in histeq_test (line 15)
Output = I/numel(A);
By using I = histogram(Val,0:bin); and Output = double(I) /numel(A); The new error becomes:
Index exceeds matrix dimensions.
Error in histeq_test (line 21)
HIm = CSum(A + 1);
I therefore request the writer of this code to revise it, accordingly.
hello every one.... i need matlab code for adaptive contrast stretching without using of any built in matlab function.can any one help?
ReplyDeletei like it its the simplest code i see it
ReplyDelete@Aqeel Al-Surmi
ReplyDeleteIt still doesnt work
thanks verey good code
ReplyDelete