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pixel bin relation imhist

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Sylvain Hauser
Sylvain Hauser 2017-8-22
回答： Image Analyst 2017-8-22
Hello,
I'm using imhist, and I would like to assign a default value to each pixel whose intensity appears less than a fixed number of times in the image. In other words, I would like a function whose input is an image and the output is its histogram and the concerned pixels (their location) for each bin of the histogram. I could write a script doing that, but I'm looking for a direct method, as optimized as possible.
Thanks for your help
Sylvain
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Adam
Adam 2017-8-22
Well, I'm pretty sure there isn't a single inbuilt function that will do it all for you so you'll have to write some code. It depends what you consider a 'direct' method vs whatever you think the alternative is.

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回答（3 个）

Jan
Jan 2017-8-22
The question is not clear. What are " concerned pixels (their location)" exactly?
I assume you want to start with:
[counts, binLocations] = imhist(I); % Or imhist(I, n) with a suitng n?
And now you want set all binLocations with counts<limit to a certain value? How would the script you have mentioned look like?
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Adam
Adam 2017-8-22
Well, you haven't shown your script so who knows if there is a better way or not until you do?!
Sylvain Hauser
Sylvain Hauser 2017-8-22
Sorry, here is my script, f being the grayscale image and F a factor to determine the threshold:
function [f] = imhist2(f,F)
bl=linspace(0,1,256);
bl1=zeros(size(bl));
bl1(2:end)=(bl(1:end-1)+bl(2:end))/2;
bl2=ones(size(bl));
bl2(1:end-1)=(bl(1:end-1)+bl(2:end))/2;
th=F*max(imhist(f));
cn=zeros(size(bl));
for i=1:length(bl)
ind=find(f>bl1(i)&f<bl2(i));
cn(i)=length(ind);
if cn(i)<th
f(ind)=mean2(f);
end
end
end

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Jan
Jan 2017-8-22
编辑：Jan 2017-8-22
Try this:
Edge = linspace(0,1,256);
[N, Edge, Bin] = histcounts(f, Edge);
V = (N < (F * max(N)));
Mask = V(Bin);
f(Mask) = mean(f(:));
histcounts determines the frequency of values. I've used the simpler linspace(0,1,256) here, because the intention of your bl1 and bl2 is not clear to me. You can adjust the wanted edges as you want. Then a mask is created, which is TRUE for all values, which appear less than F times the most frequent value.
Image Analyst
Image Analyst 2017-8-22
You can compute the color frequency image http://www.mathworks.com/matlabcentral/fileexchange/28164-color-frequency-image
Then simply threshold it and assign the new value you want.
pixelsToReplace = cfImage < someThresholdValue;
cfImage (pixelsToReplace) = desiredValue;

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