Given a grayscale image X2


And its (under)quantised version with 3 bits depth 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');


  • 1
    $\begingroup$ I would suggest that you exchange the word "quantified" for the word "quantised". $\endgroup$ – A_A May 8 '18 at 7:09

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.

  • $\begingroup$ Because the two images are normalized independently, this probably doesn’t hold. $\endgroup$ – Cris Luengo May 10 '18 at 1:59
  • $\begingroup$ Thanks for your comment. It is probable you are right, I'll check again. $\endgroup$ – MimSaad May 10 '18 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 '18 at 14:45

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.