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Determine the intensity value, "T", in a 2D image for which 99.9% of all intensity values are less than "T"

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Ed Principe
Ed Principe on 30 Oct 2020
Commented: Ed Principe on 30 Oct 2020
% I can read in an image and calculate a threshold for which the pixels are above some value, i.e., 6000.
% I can count the number of those pixels above that value
PixelCount = sum(Threshold(:))
% ratio the PixelCount over the total # of pixels in an image with dimensions X1, Y1 to determine a fraction, or percent of pixels above that value
But if I wish to calculate the intensity value that represents a desired fraction, i.e. 0.001, - instead of choosing an arbitrary number, like 6000........... how do I program to extract the intensity value that represents cutoff for which 99.9% of pixels have a lower intensity ?
I should mention these are uint16 images.
  1 Comment
Ed Principe
Ed Principe on 30 Oct 2020
I think I have something that works for me..... Q is an image from an image stack extracted in a for loop wih index 'p':
title(['Sorted Pixel Intensities:',F,': image #: ', num2str(p),'/',num2str(l.noimages)],'Interpreter', 'none');

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Accepted Answer

Akira Agata
Akira Agata on 30 Oct 2020
I believe prctile function will be helpful to this task, like:
% Read sample gray scale image
I = imread('cameraman.tif');
% Calculate threshold value (99.9% cut-off)
th = prctile(I(:),99.9);
Check the result:
>> nnz(I<th)/numel(I)
ans =
Ed Principe
Ed Principe on 30 Oct 2020
Yes, that works, that is essentially what I came up with in my comment on the original post above. Thank you very much!!

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