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