Magnitude Estimation for Scaling Saturation
Lu-Yin Grace Juan and M. Ronnier Luo
Colour & Imaging Institute
University of Derby
Derby, DE22 3HL
UK
Abstract
A psychophysical experiment was carried out for describing colour appearance under different
viewing conditions [1]. Attempts were made to estimate the magnitude of saturation for a number
of samples. The CIE defines saturation as the colourfulness of an area judged in proportion of its
brightness. The viewing parameters in the 12 phases investigated were: three different neutral
backgrounds (white, mid-grey and black), sample sizes (2o and 10 o), textures (textile and paint),
sample types (flat and cube) and colour attributes. Only 6 phases of results were used in this
study associated with saturation percept. One hundred and thirty-two semi-matte enamel paint
samples were chosen from a commercial version of the NCS Colour Order System [2]. For
scaling saturation, only the cube samples were used because observers recognised that the
same colour was covered the whole cube but they have quite different lightness and colourfulness
percepts. However, each side should have quite similar saturation according to CIE definition.
Before carried out the experiment, a training session was conducted. The saturation is the
most difficult percept to be scaled in comparison with the others: lightness, colourfulness and hue.
The details of training method will be given in the full paper. The experiment was carried out in a
VeriVide viewing cabinet using a D65 simulator against 3 neutral backgrounds: white, grey and
black. Each sample was displayed one at each time together with a reference white sample for
scaling lightness, or with a chromatic reference colourfulness sample for scaling colourfulness.
The results of three colour attributes lightness, colourfulness and saturation were used in this
study. The 132 cube samples was used to scale only saturation. The lightness and colourfulness
visual data were collected from the estimation using flat samples having the same 132 colours.
Seven to 9 observers participated in each phase. Magnitude estimation method was employed to
judge the colour attributes. Totally 6336 estimations observations were collected in this project, in
which 1848, 2244 and 2244 for saturation, lightness and colourfulness scales respectively.
A Minolta CS1000 tele-spectroradiometer with a 5nm bandwidth was used for measuring all
samples under different sets of viewing conditions used in the experiment. The data were used to
test the performance of models.
The data analysis was carried out using the same method as Luo et al [3-4]. The coefficient of
variation (CV) was used to investigate the agreement between each individual observer and the
mean visual results, or between mean visual results and a colour model’s predictions. For perfect
agreement between each individual and mean visual result, the CV value should be zero. The
observer precision in terms of CV values for saturation, lightness and colourfulness attributes
were calculated for each phase. The mean CV values were 16, 13 and 19 for saturation, lightness
and colourfulness respectively. The observer precision in terms of CV values for lightness,
colourfulness and saturation attributes were calculated for each phase. This implies that for a
satisfactory colour appearance model it is difficult to achieve better than 84%, 87% and 81%
agreement with saturation, lightness and colourfulness visual results respectively. The lightness
and colourfulness figures agree well with those found by Luo et al. [3-4].
The results indicate that the observers can be trained to scale saturation with a great accuracy.
There are little differences in saturation against the three different backgrounds.
The comparisons between saturation and lightness, and between saturation and colourfulness
were made. The results showed that lightness and colourfulness are independent attributes, but
not for saturation, i.e. when saturation increases, the colourfulness will increase and lightness will
decrease. The saturation results in general agree well with colourfulness results except for some
dark and saturated colours.
The experimental results were used to test the performance of 10 existing colour appearance
models and colour spaces: CIELAB, CIELUV, Nayatani97, CIECAT94LAB, RLAB96, Hunt94,
Hunt96, LLAB96, CIECAM97s, CAM97c and CAM97s2. Only CIELAB and RLAB96 do not include
a saturation scale. Hence, two equations approximating saturation were introduced to these
models: chroma divided by lightness, and/or colourfulness divided by brightness. A new equation
based upon CIECAM97s was derived to give the best fit to the visual results.
Reference
1. L. G. Juan & M. R. Luo, “New Magnitude Estimation Data for Evaluating Colour Appearance
Models”, Proceedings of Colour and Visual Scales 2000, 3~5 April 2000, Egham, UK.
2. FŠrginstitutet, Natural Color System A4 binders. Scandinavian Colour Institute AB, 8 volumes
(1990).
3. M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, C. J. Tait, Quantifying
Colour Appearance Part I. LUTCH Colour Appearance Data, Color Res. Appl., 16:3, 166-180
(1991).
4. M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, C. J. Tait, Quantifying
Colour Appearance Part II. Testing Colour Models Performance Using LUTCH Colour
Appearance Data Color Res. Appl., 16:3, 181-1970(1991).