hi,
On Mon, Feb 24, 2014 at 11:44 PM, Deryk Lister
<[email protected]>wrote:
> Fraser - oh I missed that part. Oh well, it produced comprehensive
> results and didn't take long!
>
> junkyard - derp, I completely forgot about the ND filter 6_9 (the camera
> has one built-in!)
>
> Johannes - glad to help, the speed of you guys I was reading about
> somewhere seems quite true
> I got close to the in-camera jpeg processing (on top of the existing base
> curve) with a very short/tight 'flattening' at the bottom of the tone
> curve, i.e. it just basically fades anything at the far dark end to pretty
> much black and reduces noise that way, as far as I can tell.
>
if you want to really get the same base curve as in-camera jpg, you can try
to measure it via our little fitting tool in the git repo (
http://www.darktable.org/2013/10/about-basecurves/).
> Though the denoise strength also needs tweaking down to 0.3-0.5 or so at
> high ISOs, at least in the firework images I was testing with.
>
the profiled denoising is based on assumptions (the noise model) which
break down in dark areas for quite a few cameras. in my experience images
with dark background and piecewise-constant characteristics, the non-local
means denoising module can work better (starry skies, probably fireworks,
too). in case you want more fine grained control over the wavelet shrinkage
used in profiled denoising in wavelet mode, it's basically the same method
as employed in the equalizer. it's also a good idea to try color-only blend
modes (hsv color, as described here
http://www.darktable.org/usermanual/ch03s04s04.html.php#denoise_profiled).
-jo
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