Evaluating colour preference by using multidimensional approaches

Colour preference is a key factor in the design and evaluation of lighting systems, particularly with the emergence of multichannel LED systems which allow for greater control over the spectrum of light emitted and therefore the colour appearance of the illuminated objects. To more accurately and objectively measure colour preference, there has been a growing interest in the development of multidimensional evaluation algorithms that consider multiple dimensions of colour rendering, such as chroma and hue shift. The purpose of this study was to compare and evaluate the performance of different multidimensional evaluation algorithms for colour preference in lighting applications. Using computer-generated images of a coloured object displayed on a computer monitor under a fixed white point, we simulated the colour shifts of the object under different light sources and test subjects evaluated the results using a range of multidimensional methods. Our analysis revealed that there are significant differences in the performance of these algorithms, with some providing more accurate and reliable measures of colour preference than others. Considering all relevant criteria, genetic algorithms seem to provide the most promising approach, as they lead to a result quickly and reliably. These findings have important implications for the selection and use of multidimensional algorithms for evaluating colour preference in lighting, particularly in the context of multichannel LED systems, and can inform future research in this area