articles/Paper/endofterm-page3

Great Paper End of Term Report - part 3 of 1 2 3 4 5 6 7 8 9

by Mike McNamee Published 01/02/2010

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Measuring and reporting actual measurements is very much part of how we like to do things for Paper Chase. In the absence of objective data we would be reduced to arm-waving and thinking up suitable adjectives - it would be fun to describe a paper as a 'saucy little minx' but leave no clear idea of how a paper might suit your project! There is some considerable difficulty in assigning a single figure to describe the colour accuracy of a reproduction (unless the value is zero or very close to it). For example if a green is way out of whack in an otherwise excellent print then the average value will be low (the average of lots of very small numbers plus a single larger, green value). However, if green is vital to the picture and is a large area of the image then it is going to look dreadful in spite of the statistics. The statistics therefore need interpretation to explain what they represent (unless again they are so close to zero that nothing more need be said).


Certain parameters are universal across the colour range. The deepest black is governed by the limiting density of the ink/paper combination. This same limitation will carry across to all the very dark colours - they will all be too light. This is very evident with fine art, matt papers. The limiting density is around 16% luminance for the best, rising to 27% for the very 'soft' papers with their increased absorbency (which takes ink down into the body of the paper and thus reduces the depth of tone at the surface). The effect is demonstrated in the graph. The average error is reduced as the limiting density rises (ie goes more black). However, the average value cannot progress lower than about 2 ΔE₀₀ because the errors on the dark tones start to dominate. The outlying data points to the left are from a gloss paper, capable of reaching down to a limiting luminance of 5% (and lower in some cases). This at least removes this constraint from the dataset and slightly more accurate average values are the norm, other things being equal.


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1st Published 01/02/2010
last update 09/12/2022 14:53:49

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