Gerhard,

I appreciate your comments, very useful.

Sadly my images aren't optimal for what I want to do.
Your suggestion of using a bit of blur is interesting.

I think I need to try it and see what kind of results I get.

Do any of the lcms binary tools provide for creating a
profile from 2 files?

Thanks,
Kent

On 8/4/07, Gerhard Fuernkranz <[EMAIL PROTECTED]> wrote:
> Kent Tenney wrote:
> > My use case:
> >
> > Several thousand images which have been color adjusted and
> > sampled down.
> >
>
> Have they only been
>
>     * first downscaled by a well-know factor, using a downscaling method
>       which you can exactly reproduce now
>     * and then ONLY color adjusted
>
> or were they possibly
>
>     * downsampled by an not exacatly known factor, or with an unknown
>       method, which you cannot reproduce exactly now
>     * cropped
>     * denoised
>     * sharpened
>     * or first color corrected, and then downscaled
>     * etc.
>
> If the latter applies, this makes things more difficult. For
> establishing the color mapping you basically need two exactly registered
> images of the same size, which differ ONLY by the color transformation,
> but NO OTHER image manipulations, particularly no spatial ones, must
> have been applied to the second image. Otherwise you can only try to to
> register the source and destination image first, and/or to blur both
> ones before establishing the color mapping. But this would of course
> distort the resulting color mapping more or less.
>
> Regards,
> Gerhard
>
> > I want to color correct the originals and keep keep them full size.
> > I would want to script this using the Python lcms bindings and the
> > Python Imaging Library.
> > My guess is that I'd sample down the original to the same size as the
> > color adjusted image, derive a color map from those 2 files, then apply
> > the map to the original.
> >
> > So, it would not be necessary to map all colors, only the ones which
> > exist in the original.
> >
>
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