Get derivatives of a noisy surface
3 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
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
3 comentarios
Respuesta aceptada
Sean de Wolski
el 10 de Jun. de 2011
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.
0 comentarios
Más respuestas (0)
Ver también
Categorías
Más información sobre Get Started with Curve Fitting Toolbox en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!