Get derivatives of a noisy surface

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Zhenhui
Zhenhui 2011-6-10
Hi everyone,
I still have trouble in getting derivatives of a surface. Is there any method to do this as the data are noisy? For the data z=f(x,y), how can I do the smoothing/ regularization to get the reliable derivatives. Someone suggested that regularizing the differentiation process to avoid the noise amplification of finite-difference methods. Is there any way to do that in matlab?
I found some ways to smooth and get derivatives for a curve fitting like z=f(x), but I don’t know how to deal with the 3D data.
Any suggestion? Your answer will be greatly appreciated.
Cheers Hui
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Zhenhui
Zhenhui 2011-6-10
yes, but i still didnt find ways to solve it...T-T
Zhenhui
Zhenhui 2011-6-10
sure, thanks for linking this ;)
i am wondering whether neural network will work somehow. anyway, i dont know much about that...

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Sean de Wolski
Sean de Wolski 2011-6-10
Perhaps a point-wise least squares method might be of interest to you?
This paper gives a fairly decent description of it for strain calculation in 2-dimensional images - numerical derivatives of a surface. http://www.sciencedirect.com/science/article/pii/S0143816609000189
It gave me good results for my work.

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