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Given a grayscale image X2

X2

And its (under)quantised version with 3 bits depth X3

X3

What information does the abs(X2_normalized - X3_normalized) carry?
As an example the following image X5 generated with the code below

X2norm= X2-min(X2(:)); X2norm = X2norm / max(X2norm(:));
X3norm= X3-min(X3(:)); X3norm = X3norm / max(X3norm(:));
X5 = abs(X2norm - X3norm);
image5=figure;imagesc(X5);title('image 5');
saveas(image5,'image5.jpg');

X5

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    $\begingroup$ I would suggest that you exchange the word "quantified" for the word "quantised". $\endgroup$
    – A_A
    May 8, 2018 at 7:09

1 Answer 1

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Assuming your image is a $K$ bits depth image, and the quantized version is a $3$ bits version, pixels of the difference image, represent $(K-3)$ least significant bits of pixels of the original image. It means it completely is similar to original image in darker parts and completely masks the brighter parts.

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  • $\begingroup$ Because the two images are normalized independently, this probably doesn’t hold. $\endgroup$
    – Cris Luengo
    May 10, 2018 at 1:59
  • $\begingroup$ Thanks for your comment. It is probable you are right, I'll check again. $\endgroup$
    – MimSaad
    May 10, 2018 at 7:54
  • $\begingroup$ @Cris Luengo I could not find it, I am interested to know. would you give some hints? $\endgroup$
    – MimSaad
    May 19, 2018 at 14:45

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