Confocal Image super sampling high computational cost

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