Workaround for the norminv function in statistics toolbox

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Kyle Bryenton
Kyle Bryenton 2013년 7월 19일
I am working on some image processing software and to get rid of the background noise in the pictures I am working with, it was suggested I use the following code. I found that it worked, however the computer I want to process these images on does not have the statistics toolbox which contains the norminv function. I was wondering if there is a way to work around using that particular function
Here is what my code currently looks like:
im=rgb2gray(imread(input('What picture would you like to input: ','s')));
fmt=fspecial('gaussian',2*ceil(-norminv((1e-1)/2,0,4))+1,4.0);
im2=(double(im)-imfilter(double(im),fmt))./(sqrt(imfilter((double(im)-imfilter(double(im),fmt)).^2,fmt)));
im3=filter2(fspecial('average',10),im2);
im4=...
Any suggestions?

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Wayne King
Wayne King 2013년 7월 19일
편집: Wayne King 2013년 7월 19일
You can use the inverse complementary error function. You'll have to convert from a nonstandard normal distribution, but that should not be hard.
If you are dealing with the standard normal, N(0,1), then
p = 0.9;
norminv(p)
is equal to
-sqrt(2)*erfcinv(2*p)
If you have a Gaussian distribution other than the standard normal
mu = 1;
sigma = 4;
p = 0.9;
norminv(0.9,1,4)
equals
sigma.*(-sqrt(2)*erfcinv(2*p))+mu

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