Re: python PIL 16-bit tiff files

Hey guys,

Thanks for your input,

The image is only of a tiny cropped area of a long strip of color kodachrome
film - I will send a better example with some more color in it when I get a
chance.

I was under the impression that PIL handled 16 bit images (experimentally)
but does this only apply to 16-bit grayscale images?

Am I going up a dead end trying to read my images with PIL?





On 13 April 2010 08:09, Sebastian Haase <[email protected]> wrote:

> On Tue, Apr 13, 2010 at 2:16 AM, Guy K. Kloss <[email protected]>
> wrote:
> > On Mon, 12 Apr 2010 23:32:32 Sebastian Haase wrote:
> >> are you sure it makes even sense to save a 16-bit RGB image ? This is
> >> not meant as an excuse for PIL to not support it,
> >> but 16mio colors should likely be enough for any application (i.e.
> >> 8bit per R,G and B)
> >
> > It does make sense. Absolutely! Maybe not if you are *just* thinking in
> terms
> > of final output for an end user, but during the whole
> > capturing/processing/manipulation phase one can reduce many artifacts
> > introduced through rounding, etc. Also when images are touched up by
> changing
> > lightness or contrast images tend to expose "banding" quite severely.
> >
> > This and other effects are also the background behind the increasing
> > popularity of HDR (High Dynamic Range) imaging. Particularly in
> scientific
> > imaging subtle differences are much preserved this way. And it looked
> like
> > Dan's image is the result of a microscopic picture, or something like
> that,
> > with low contrast. So it could strongly benefit from a change in
> lightness and
> > contrast.
> >
> > Higher channel bit depth are important for these cases, and even more to
> keep
> > up with needed capabilities for the future!
> >
> > Guy
>
> I was talking only about the information content captured by
> physically collecting photons from a film with very short exposure
> times. That is, the "capturing" phase; for what you call the
> "processing/manipulation" phase I would always convert to
> single-precision float (numpy.float) if that fits into memory. This
> way you are save if values get negative or intermittently very small,
> for example.
> I'm just a bit confused here, because I am used to collecting gray
> scale images, not RGB images, (from a cooled CCD on a microscope).
> Those I also save as unsigned 16 bit integers.
> BTW, the original example image looked also pretty "gray" to me, could
> you tell the scanner to use 16-bit gray, maybe then the (physical)
> scanning quality might even be better - don't know, just wild guess...
>
> Sebastian
> _______________________________________________
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>

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