[argyllcms] Re: Determining proper error value for -r
- From: Gerhard Fuernkranz <nospam456@xxxxxx>
- To: argyllcms@xxxxxxxxxxxxx, argyllcms@xxxxxxxxxxxxx
- Date: Wed, 24 May 2006 11:39:36 +0200
> -------- Original-Nachricht --------
> Datum: Wed, 24 May 2006 11:02:51 +1000
> Von: Graeme Gill <graeme@xxxxxxxxxxxxx>
>
> > Like I said, I used 39 test patches from an Argyll 39-patch chart,
> > with eight copies of each patch.
>
> OK, seems pretty reasonable then.
Except probably, that a sample size of 8 per color is rather very small to
estimate the population variance by the sample variance reliably. I have done
basicallly the same experiment some time ago (also with about 50 patches and 10
replications each) in order to get an estimate of the reproducibility of my
laser printer. Basically there is a trend in evidence that some colors are
reproduced with a lower and others with a larger variance, however one must be
very careful judging this, since for such a small sample size, a difference
between say 1.8dE and 2dE is statistically not really significant; i.e. the
color with 1.8dE sample standard deviation and the other color with the 2dE
sample standard deviation could very likely also be just two different samples
from the same population, or the color with the 1.8 dE sample standard
deviation could even come from a population with a larger population standard
deviation then the color with the 2dE sample standard deviation.
I'm in fact wondering whether it might be worth to attempt to fit a very smooth
RGB/CMYK -> variance RSPL mapping to this data, and to use this RSPL during
profile generation to obtain an individual weight for each training set data
point (i.e. weight[i]=1/variance[i], probably normalized such that the sum of
the weights is 1.0 in order that the per data point weights do not interfere to
much with the existing avgdev -> raw smoothness mapping).
Regards,
Gerhard
> The real overhead is in making
> several separate prints to exercise that source of error.
--
Gerhard Fuernkranz
nospam456@xxxxxx
Bis zu 70% Ihrer Onlinekosten sparen: GMX SmartSurfer!
Kostenlos downloaden: http://www.gmx.net/de/go/smartsurfer
Other related posts:
