Re: A discussion on accurate color ...
Re: A discussion on accurate color ...
- Subject: Re: A discussion on accurate color ...
- From: Klaus Karcher <email@hidden>
- Date: Wed, 15 Jun 2011 06:13:26 +0200
Hello Ernst,
you wrote:
Given successive changes in pigment qualities through time I wonder how
it works if say you have several reds in that target that are based on
different pigments ranging from the 12th century up to now. They have to
be selected as an average of used pigments through time and by that are
a compromise again. Would it not be better to make more targets with
pigments that represent a certain period in time and/or type of art?
Still a rough classification considering the different speeds in
adapting new pigments per area. What was ground by Jan van Eyck in 1420
may not have been in use in Russia two centuries later.
As far as my experience goes, the properties of the "ideal" training set
are more affected by the properties of sensor and light source than by
typical pigments.
Sets of spectra that cover large parts of the metamer mismatch regions
of a sensor or observer can be found or produced with historic paints as
well as with modern colorants (e.g with color formulation systems,
printing inks, ...).
As soon as there are more than 3 basis colors to be considered, the
chances to improve reproduction accuracy by excluding "unrealistic"
areas from the metamer mismatch regions decrease dramatically. And at
least when we regard paintings, arbitrary mixes of more than 3 basis
colors even in one original are quite common.
Even if you restrict the basis of your training- and test-sets to just 4
colors (e.g. if you print all test- and training-sets with just one
particular CMYK printer), but make use of the whole space spanned by
this basis (i.e. if you don't use a fixed separation rule), you will
note that there are situations where different CMYK values result in the
same response for one of your "observers" (camera or human observer),
but in distinct responses for the other observer. As soon as this
happens, the mapping between camera and observer space can not be
unambiguous anymore. And as soon as there is more than one CMYK value
that induces a certain camera or observer response, you can find /an
infinite number/ of CMYK values that induce exactly the same response
for one of the observers (but different responses for the other one). If
you can e.g. print the same shade of gray once with pure black and once
with pure CMY, you can find an arbitrary number of CMYK combinations "in
between" that also result in the same Lab value, but in different RGB
values.
The set of spectra that result in the same camera or observer response
is the metamer set that induces this response. It is infinite, closed
and convex.
The projection of the metamer set for a certain camera response onto the
observer space is the metamer mismatch region. Also this region is
closed and convex.
There are several strategies to select patches for the training set: you
can e.g. select just one typical representative for each mismatch region
(e.g. a CMYK patch with an "average" separation), you can include
extrema (e.g. pure CMY and pure K) or you can create separate training
sets for different applications (separations).
Error-minimizing mappings can benefit from the fact that mismatch
regions are often elongated and oriented along a certain axis.
Klaus Karcher
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