How to make image intensity equalization for multiple images.

Given: I have 9 gray-scale images of the same size with slightly different intensity.

Want: I want to make uniform intensity for all the images.

Currently done: Just now I'm doing image adjustment followed be image equalization for each single image, by using code below

for x=1:9
    eq_image(:,:,x)=histeq(imadjust(some_image(:,:,x)));                           
    figure(x); imshow(eq_image(:,:,x), []);
end

Needed: How to make intensity the same for all 9 images?

[ACKNOWLEDGMENTS]

Thank you for help: Kerem tezcan, Image Analyst

Answer 1

[Kerem tezcan]

Hey,

When you do histogram equalization, you do that separately for each image, which is not what you want, as you have also stated.

You can normalize the images to one of them. For example choose the first image as the reference, and then calculate the mean intensities of all the images, and find the scaling between each image with the reference image by the formula: sc(n) = mean_of_ref / mean_of_ims(n). Then you can multiply all the images with the corresponding individualized scaling and you will have the same mean intensity for all the images.

Other approaches would be to normalize them according to their maximum values, or similarly to the minimum values, or to the median values.

For the scaling according to the mean of the first image, the code would look like this:

for x=1:9
    mns(x) = mean2(some_image(:, :, x));                           
    scaled_image(:, :, x) = some_image(:, :, x) * (mns(1) / mns(x));
end

You can do the histogram equalization independently of the scaling, but doing that afterwards will change the mean of any image you do it to.

[Ivan Shorokhov]

That is what I wanted to hear. Thank you very much for such an open answer!

[Soum]

Thank you very much for your pretty answer Kerem tezcan

Answer 2

[Ivan Shorokhov]

Another example/code for histogram equalization – might be useful.

M = zeros(256,1,'uint8'); % Store mapping - Cast to uint8 to respect data type
hist1 = imhist(img1);        % Compute histograms
hist2 = imhist(img2);
cdf1 = cumsum(hist1) / numel(img1);  %Compute CDFs
cdf2 = cumsum(hist2) / numel(img2);

% Compute the mapping
for idx = 1 : 256
    [~,ind] = min(abs(cdf1(idx) - cdf2));
    M(idx) = ind-1;
End

%Now apply the mapping to get first image to make
%the image look like the distribution of the second image
out = M(double(img1)+1);

Answer 3

[Image Analyst]

You can do linear scaling like kerem suggested. Another option is to use imhistmatch() to match images 2 and higher to image #1.

[Ivan Shorokhov]

Thank you!

[mohd akmal masud]

Hi all

i want try open multiple images using implay. but want to change contrast first. Below is my code, but still error. anyone can help me.

P = zeros(512, 512, 313);
  for K = 1 : 313
     petname = sprintf('TRANSA001_CT%03d.dcm', K);
     P(:,:,K) = dicomread(petname);
  end
  Out(:,:,K) = imadjust(P(:,:,K));
 implay(Out, [-182 292]);