- your images are integer data
- your images are lossy-compressed JPG
Histogram Equalisation creating pixelated images
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jlouise2022
le 5 Juil 2022
Commenté : jlouise2022
le 6 Juil 2022
Hi there,
I am using histeq to transform a set of images. However, while some of the images are transformed fine, a fair few are looking too pixelated. I will input an example below. First, here is my code:
filenames = dir(fullfile(Stimuli, '*.jpg'));
for k = 1:numel(filenames)
images = filenames(k).name;
equalHist = imread(images);
gsImg = histeq(equalHist, 255);
[~,name,~] = fileparts(filename);
gsFilename = sprintf('%s_histeq.jpg', name);
imwrite(gsImg,gsFilename);
end
This is how some of the images are looking. E.g. edges are pixelated.
I have tried adjusting the intensity availibility , e.g. 255, 127, etc, but the problem persists.
Any ideas welcomed!
Thanks
2 commentaires
DGM
le 5 Juil 2022
Two things:
What happens when you take a roughly-quantized shallow gradient and stretch its range?
A = imread('shallowgrad.jpg'); % a shallow JPG gradient
A = rgb2gray(A);
imshow(A)
B = imadjust(A); % stretch the range
imshow(B)
IA is right about not using histeq(), but the problem is more fundamental. Images have limited information. They look grossly quantized because they are. Regardless of the method, extreme contrast changes will emphasize the deficiencies of the source image.
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Image Analyst
le 5 Juil 2022
Yes, you've learned that histogram equalized images look crappy. It's not surprising. So just don't do it. There is no need to. There are ways to get it to look less posterized (by adding a half gray level of noise) but they will still look bad so don't bother.
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