[Numpy-discussion] Update for IM. a small image processing system

Peter Verveer verveer at embl-heidelberg.de
Wed Jan 7 04:45:01 CST 2004


On Wednesday 07 January 2004 07:50, RJS wrote:
>  >  I have uploaded a new version of my small image processing system IM to
>  >  "http://members.tripod.com/~edcjones/IM-01.01.04.tar.gz". Most of the
>  > code in IM (pronounced "I'm") is inferior to "nd_image" so I will
>  > eventually convert it all to "nd_image".
>
> ...
>
>  > nd_image is however also still being developed and I am looking for
>
> directions to
>
>  > further work on. I wondered if there is anything you would like to see
>
> in there?
>
> I have been working with Pythonmagic and numarray for a particular
> astronomy project/technique, and IM has a few things I might use; nd_image
> also has some interesting functions as well.
>
> I want to align and specially stack 8-bit grayscale images from a FITS
> cube, or BMP set, currently. So, my suggestions (hint, hint) are:
> 1. A method to shift an array to efficiently give the best alignment with
> another. My brute force shifting and subtracting from the main image is
> slow... Most programs I have seen align a selected sub-image, then shift
> the whole image/array (without rotation, although that would be desirable)

If I understand you well, you essentially want to estimate a shift between two 
images. I have some code that can do that. I do not intend to include that in 
nd_image for now, but I can send you the code.

> My _main_ objective is to stack progressively-longer-exposure 8-bit images
> into 16-bits, with the clipped pixels of longer exposures ignored in the
> summing process. The value of each pixel must be weighted inversely
> proportionately to it's exposure length (so shorter exposures "fill in" the
> clipped areas of the long exposures).
>
> So:
> 2. A fast method(ology) to do weighted sums of 2D arrays with a mask
> available for each array.

I think this can be achieved relatively easily with standard numarray 
operations.

Cheers, Peter





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