I’m writing a piece of code that has to transform from an RGB image to an rgb normalized space. I’ve got it working with a for format but it runs too slow and I need to evaluate lots of images. I’m trying to vectorize the full function in order to faster it. What I have for the moment is the following:
R = im(:,:,1);
G = im(:,:,2);
B = im(:,:,3);
r=reshape(R,[],1);
g=reshape(G,[],1);
b=reshape(B,[],1);
clear R G B;
VNormalizedRed = r(:)/(r(:)+g(:)+b(:));
VNormalizedGreen = g(:)/(r(:)+g(:)+b(:));
VNormalizedBlue = b(:)/(r(:)+g(:)+b(:));
NormalizedRed = reshape(VNormalizedRed,height,width);
NormalizedGreen = reshape(VNormalizedGreen,height,width);
NormalizedBlue = reshape(VNormalizedBlue,height,width);
The main problem is that when it arrives at VNormalizedRed = r(:)/(r(:)+g(:)+b(:)); it displays an out of memory error (wich is really strange because i just have freed three vectors of the same size). Were is the error? (solved)
Its possible to do the same process in a more efficiently way?
Edit:
After using Martin sugestions I found the reshape function was not necessary, being able to do the same with a simple code:
R = im(:,:,1);
G = im(:,:,2);
B = im(:,:,3);
NormalizedRed = R(:,:)./sqrt(R(:,:).^2+G(:,:).^2+B(:,:).^2);
NormalizedGreen = G(:,:)./sqrt(R(:,:).^2+G(:,:).^2+B(:,:).^2);
NormalizedBlue = B(:,:)./sqrt(R(:,:).^2+G(:,:).^2+B(:,:).^2);
norm(:,:,1) = NormalizedRed(:,:);
norm(:,:,2) = NormalizedGreen(:,:);
norm(:,:,3) = NormalizedBlue(:,:);
I believe you want
Note the dot in front of the
/, which specifies an element-by-element divide. Without the dot, you’re solving a system of equations — which is likely not what you want to do. This probably also explains why you’re seeing the high memory consumption.