Page 62 - Computational Colour Science Using MATLAB

5

Computing Colour Difference

5.1 Introduction

Although the system of colour specification introduced in 1931 by the CIE and
augmented in 1964 has served the colour industry well, there remain a number of
problems. One of the main problems is that in terms of visual perception it is
very non-uniform. Equal changes in x, y or Y do not correspond to perceived
differences of equal magnitude. Most attempts to develop more uniform spaces
have sought to find linear or non-linear transforms of the tristimulus values or
chromaticity coordinates to give a more uniform colour space. In 1976 the CIE
recommended two new colour spaces for general use (CIE, 1986b): CIE L*a*b*
and CIE L*u*v*, also known as CIELAB and CIELUV. CIELUV was intended
to be used to specify the colours of lights and other self-luminous sources,
whereas CIELAB was intended to be used for the specification of surface
colours. It is possible to compute a colour difference for two stimuli in CIELAB
space by calculating the Euclidean distance in the space between the two points
that represent the stimuli in the space [Equation (1.6)]. The CIELAB colour-
difference formula has been used extensively for quality control in industry but
its application is limited because although CIELAB space is more perceptually
uniform than the tristimulus space on which it is based, it is still far from being
perfectly uniform. The consequence of this is that for equal perceptual colour
differences between pairs of samples, the values of CIELAB colour difference
DE* computed between points representing the pairs in CIELAB space can vary
ab
by an order of magnitude. Since 1976 attempts to generate better metrics for the
prediction of colour differences have concentrated on finding more sophisticated
measures of distance. A summary of the developments is not given in detail here
(see Smith, 1997; Berns 2000; Luo, 2002a) but the formulae for the three key
developments, CMC(l:c), CIE94 and CIEDE2000, are given. The CMC
equation, developed in the early 1980s, was a key development in colour science
and became a standard in certain countries and industries (Clarke et al., 1984). It

Computational Colour Science Using MATLAB. By Stephen Westland and Caterina Ripamonti.
& 2004 John Wiley & Sons, Ltd: ISBN 0 470 84562 7