Hi Frederico,
I am trying "nldif" function, and find that there are two options for diffusion: one is "AOS" by aosiso.m and the other is "iso" by isodifstep.
For "AOS", the result is good when I choose stepSize = 2; But for "iso", I cannot get good result for any stepSize (from 0.01 to 1...).
I want to know what value of stepSize for "iso" case can get the same result as "aos". I suppose "aos" and "iso" should get the same result when choose proper stepSize. The only different should be the speed. Is it correct?
And when I try to feed back from "aos" result to "iso" stepSize ( (aosiso(y, g, 2) - y)/dy ), but I can not get a uniform stepSize value.
Can you help me to explain above case?
code for feedback:
========
% Calculate dy/dt
%if aos
% if plotflux
% yo = y;
% end
% y = aosiso(y,g,stepsize(i)); % updating
%else
% dy = isodifstep(y, g);
% y = y + stepsize(i) * dy; % updating
%end
tmp = y;
tmp1 = aosiso(y, g, 2) - tmp;
dy = isodifstep(y, g);
ios_step = tmp1 / dy;
=======
Thanks
I wish someone would implement "Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE’s"
By David Tschumperlé into this toolbox.
Hi Frederico,
I am translating your matlab code in to IDL, I find that in the convolution step ('gsderiv.m'), the gaussian kernel is not normalized. It is done in 1D 'kernel=kernel/sum(kernel)', however, it is important that you do it like this:
kernel_grid=meshgrid(kernel_index,kernel_index)
kernel = exp(-.5*(kernel_grid./sigma).^2)
kernel=kernel/sum(kernel)
then you do convolution
theres some problem in linear diffusion. I am getting colored images in nonlinear.
How can i reduce the diffusion and I am unable to undrstand the inputs takn can any one help me please aadarshmalviya@gmail.com
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