Confocal Image super sampling high computational cost
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Good morning to everybody, I have several confocal images captured by a Zeiss microscope. The x,y resolution is higher that z one and to perform binary volumetric operations the resolution on the three axis should be the same.
For this reason I extract from the input information matrix{} the vectorZ, than compute the supersampling using imresize to create the new 3D structure matrixZ
x = [1,1,1];
h = @(x) gaussmf(x,[4,0]);
Zplanes = planes * 7;
[r,c] = size(matrix{1,1});
matrixZ = zeros (r,c, Zplanes);
for i = 1: r
for j = 1 : c
vectorZ = zeros(1,6);
for z = 1 : planes
vectorZ(1,z) = matrix{1,z}(i,j);
end
vectorCZ(1,:) = filter(h(x),2,vectorZ(1,:));
V2 = imresize(vectorCZ, [1 Zplanes], 'bilinear');
matrixZ(i,j,:) = V2(1,:);
end
i
end
It works good, but it take a long long time to be computed, any suggestion to spare time?
Thanks a lot! Emanuele
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