The determination of the long-term memory colours of objects has been the subject of investigation for many years. Colour acceptance boundaries have been determined from the visual assessments of objects under variable illumination or by presenting manipulated images of objects on a calibrated computer display. However, a systematic and quantitative rating of the colour of real objects with respect to memory colour is not available at this moment. In this article, nine familiar real objects with colours distributed around the hue circle were positioned in a specially designed LED illumination box. For each object, approximately hundred real illumination spectra were synthesized in a random order keeping the luminance of the object approximately constant. Observers were asked to rate, on a five-point scale, the similarity of the perceived object colour to their idea of what the object looked like in reality. By avoiding specular reflections, the observer was unable to identify any clues as to the colour of the illumination. For each object, similarity ratings showed a good intraobserver and interobserver agreement. The ratings of all the observers were pooled and successfully modeled in IPT colour space by a bivariate Gaussian distribution. It was found that the chromaticity corresponding to the highest rating tended to be shifted toward higher chroma in comparison with the chromaticity calculated under D65 illumination. The bivariate distributions could be very useful in applications where the quantitative evaluation of the colour appearance of an object stimulus is required, such as in the evaluation of the colour rendering capabilities of a light source.

No abstract

Over the past years there has been increasing evidence that the CIE color rendering index R(a) fails to correspond to the perceived color quality of many light sources, especially some Light-Emitting-Diodes. Several proposals to update, complement or even replace the CIE R(a) have therefore been made. The performance of thirteen color quality metrics was evaluated by calculating the average correlation of the metric predictions with the visual scaling of the perceived color quality obtained in several psychophysical studies. Two aspects of perceived color quality were investigated, appreciation (preference or attractiveness) and naturalness. The memory color quality metric (S(a)) of Smet et al. was found to correlate highly with perceived appreciation (r = 0.88). It was found to be statistically better (p<0.0001) at it than all other metrics. The CIE R(a) performed the worst. A metric that combines the gamut area index (GAI) and the CIE R(a) using an arithmetic mean correlated highly with the perceived naturalness of a light source (r = 0.85). It was found to be statistically better at predicting naturalness than all other metrics (p<0.0001). A negative correlation was found, between the capabilities of a light source's ability to predict appreciation and naturalness, indicating that a complete description of the color quality of a light source probably requires more than one metric.

A colour quality metric based on memory colours is presented. The basic idea is simple. The colour quality of a test source is evaluated as the degree of similarity between the colour appearance of a set of familiar objects and their memory colours. The closer the match, the better the colour quality. This similarity was quantified using a set of similarity distributions obtained by Smet et al. in a previous study. The metric was validated by calculating the Pearson and Spearman correlation coefficients between the metric predictions and the visual appreciation results obtained in a validation experiment conducted by the authors as well those obtained in two independent studies. The metric was found to correlate well with the visual appreciation of the lighting quality of the sources used in the three experiments. Its performance was also compared with that of the CIE colour rendering index and the NIST colour quality scale. For all three experiments, the metric was found to be significantly better at predicting the correct visual rank order of the light sources (p < 0.1).

Optical and electrical characteristics of power light-emitting diodes (LEDs) are strongly dependent on the diode junction temperature. However, direct junction temperature determination is not possible and alternative methods must be developed. Current-voltage characteristics of commercial high power LEDs have been measured at six different temperatures ranging between 295 and 400 K. Modeling these characteristics, including variation in the bandgap with temperature, revealed a linear temperature dependence of the forward voltage if the drive current is chosen within a rather limited current range. Theoretically, the voltage intercept can be deduced from the bulk semiconductor bandgap. However, accurate junction temperature determination is only possible if at least two calibration measurements at a particular drive current are performed. The method described in this paper can be applied to calculate the thermal resistance from the junction to any other reference point for any particular LED configuration.

Based on an extensive magnitude estimation experiment, a new color appearance model for unrelated self-luminous stimuli, CAM15u, has been designed. With the spectral radiance of the stimulus as unique input, the model predicts the brightness, hue, colorfulness, saturation and amount of white. The main features of the model are the use of the CIE 2006 cone fundamentals, the inclusion of an absolute brightness scale and a very simple calculation procedure. The CAM15u model performs much better than existing models and has been validated by a validation experiment. The model is applicable to unrelated self-luminous stimuli with an angular extent of 10° and a photopic, but non-glare-inducing, luminance level.

Spectral radiant flux is the primary optical characteristic of a light source, determining the luminous flux and color. Much research is dedicated to the modeling of light-emitting diode (LED) spectra and their temperature dependence, allowing for the simulation of optical properties in various applications. Most of the spectral radiant flux models that have been published so far are purely mathematical. For this paper, spectral radiant fluxes of commercial single color LED packages have been measured in a custom made integrating sphere at several junction temperatures by active cooling and heating with a Peltier element. A spectrum model at 300 K is constructed where the Boltzmann free carrier distribution and carrier temperature are included. Subsequently, the model is extended with the carrier temperature variation, the band gap energy shift, and the nonradiative recombination rate decrease with junction temperature. As a result, the skewness variation, peak frequency shift, and peak value change in the spectrum with temperature can be predicted. The model has been validated by comparing flux and color coordinates of measured and simulated spectra at 340 K junction temperature. In practice, only two spectral flux measurements at different junction temperatures are needed to accurately simulate a single color spectrum at any temperature.

No abstract