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Re: Interpolating Irregular 2D Data [message #8606] Wed, 26 March 1997 00:00
peter is currently offline  peter
Messages: 80
Registered: February 1994
Member
Achim Hein (hein@nv.et-inf.uni-siegen.de) wrote:
: Bijan Pesaran wrote:
: >
: > I have z=(x,y) data on a spiral and I want to sample it on a
: > grid for further manipulations, specifically kernel smoothing.
: >

: But I think the faster way is to interpolate the irregular data down to
: equidistant twodimensional axis - simultaneously, you smooth your data
: because of the interpolating.

Achim's suggestion is a good way to go -- the data on the spiral can be
placed onto a grid and smoothed at the same time by the procedure known
as gridding (essentially, convolving the non-rectilinear data with a
smoothing kernel onto the grid points). Very hard to do fast in IDL,
due to required (?) nested loops, since potentially every data point
lies at unique distances from its surrounding grid points, and thus
requires calculation of the interpolation weights; I've used a
call_external program to do it rapidly (and, in fact, to do spiral to
rectilinear conversion).

Peter
Re: Interpolating Irregular 2D Data [message #8648 is a reply to message #8606] Fri, 21 March 1997 00:00 Go to previous message
Achim Hein is currently offline  Achim Hein
Messages: 42
Registered: February 1996
Member
Bijan Pesaran wrote:
>
> Hi,
>
> I have z=(x,y) data on a spiral and I want to sample it on a
> grid for further manipulations, specifically kernel smoothing.
>
> I don't see how to use interpolate or bilinear to do this. They both
> seem to require the input data to be on a grid already ...
>
I think there are two possibilities of soluting this problem:

First, you can oversample your signal by zero padding in the frequency
domain to get higher resolution in the time domain. If you take the
oversampling factor big enough, you can sample your data down to the
grid.
But I think the faster way is to interpolate the irregular data down to
equidistant twodimensional axis - simultaneously, you smooth your data
because of the interpolating.

Cheers

Achim
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