Asked by Kyle Bryenton
on 19 Jul 2013

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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Answer by Wayne King
on 19 Jul 2013

Edited by Wayne King
on 19 Jul 2013

Accepted answer

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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