# standard deviation of image

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Hassan on 9 Dec 2011
I have a 3-dimensional image (image1) and a 2-dimensional image (image2) with values from 1 to 7 and want to find the standard deviation for specific values. I'm using the following code to calculate the mean value but dont know how to calculate the standard deviation. Any suggestion please?
for i=1:3
x=image1(:,:,i)
for j=1:7
L = bwlabel(image2==j);
STATS = regionprops(L,x,'MeanIntensity','Area','PixelValues');
n_stats = size(STATS,1);
area_=zeros(n_stats,1);
mean_=zeros(n_stats,1);
[m1,n1] = find(cat(1,STATS.Area) >=5);
for ii=1:n_stats
mean_(ii)=STATS(ii,:).MeanIntensity;
end
mean1=mean_(m1);
mean2(j,i)=mean(mean1);
end

Sean de Wolski on 9 Dec 2011
You can use regionprops to calculate the various fields requested of each label in a label image, e.g.:
A = uint8(rand(10)*10); %random label image
STATS = regionprops(A,'area');
areas = [STATS(:).Area]
And I don't understand what you want the standard deviation of. If youu want it of all objects with the same value, won't it be zero? Clarify your goal, I guess. (and look at stdfilt)
Hassan on 10 Dec 2011
Sorry guys for not desribing the problem clearly. You are right Walter 'Each of the areas in the 2D image acts as a mask to be applied to the 3D image.'
thats right Image Analyst.

Image Analyst on 9 Dec 2011
I don't have MATLAB on this computer so I can't test but I believe it would be something like
pixelValues = [STATS(k).PixelValues];
sd = std(pixelValues(:)); % StDev of kth blob
or something like that.
Hassan on 10 Dec 2011
I couldnt run the code. I got the following error messageç
??? Error using ==> bwlabel
Too many input arguments.
I think binary image should be the 2'dimensional categorized image and gray image should be the 3'dimensional image.
[labeledImage, numberOfBlobs] = bwlabel(image 2, image 1, 'PixelValues');
sd = zeros(1, numberOfBlobs);
for k = 1 : numberOfBlobs
pixelValues = [STATS(k).PixelValues];
sd(k) = std(pixelValues(:)); % StDev of kth blob
end