2011/5/31 Stéfan van der Walt <stefan@sun.ac.za>
On Fri, May 27, 2011 at 6:22 PM, Ralf Gommers <ralf.gommers@googlemail.com> wrote:
Fast interpolation algorithms using PyOpenCL may be worth looking at. I heard today of an interesting interpolation method that does not go exactly through data-points, but is extremely efficient to implement--will look into that some more. Either way, being able to size up and down large images efficiently would certainly be useful.
Is it just going "close enough" to the data points or does it do something like least-squares fitting to noisy data? If the latter, do you have a reference for this method?
http://dip.sun.ac.za/~herbst/research/publications/modeling.pdf
Have a look at the new paragraph starting on p. 337.
This stuff is really interesting :)
It is.
The technique is called subdivision surfaces, which I also didn't hear of before but which seems to be common in computer graphics. A good summary of related techniques and their applications is given in Chapter 2 of Krishnamurthy, "FITTING SMOOTH SURFACES TO DENSE POLYGON MESHES"; http://graphics.stanford.edu/papers/surfacefitting/surf_fit.pdf Cheers, Ralf