Image transformation.

[Stuart Mumford]

Hello,

While having a more thorough look at the transform module with respect to
the image registration discussion, I thought it might be worth picking your
brains on another solar based image processing issue we are having.

When images are collected from basically all telescopes, ground or space
based, a large amount of processing is required to get them to the point
where you can do science on them. This normally involves dark frame or
noise removal, scaling etc. The last step is to compensate for the
telescope pointing, which is generally a translate, rotate and rescale
operation.

It is this last step that we are currently trying to port from the
'standard' IDL package into SunPy for the AIA instrument on NASAs SDO
satellite.

A rotate, translate and rescale transform is not hard, the problem is we
really need to replicate the same algorithm as used in IDL so that the
processing of the data is the same irrespective of the language used to
process it.

Without trying to show you all the gritty detail of the pipeline there is a
function (for which the source code is available) called rot that is called
to do the transform (here:
http://www.astro.washington.edu/docs/idl/cgi-bin/getpro/library32.html?ROT)
this function however calls a closed source routine called poly_2D which is
described here: http://www.exelisvis.com/docs/POLY_2D.html

To my untrained eye this looks a little like
http://scikit-image.org/docs/dev/api/skimage.transform.html#polynomialtransform?
However for polynomial transform there is no discussion about
interpolation like there is for poly_2D?

We have implemented a routine in SunPy which does a cubic affine transform
in an attempt to replicate the behaviour but our testing so far is still a
fair way off from the IDL implementation.

Any advice would be as always much appreciated.

Stuart
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