Abstract:The effect of cross-regional or cross-cultural differences on color appearance ratings and memory colors of familiar objects was investigated in seven different countries/regions -Belgium, Hungary, Brazil, Colombia, Taiwan, China and Iran. In each region the familiar objects were presented on a calibrated monitor in over 100 different colors to a test panel of observers that were asked to rate the similarity of the presented object color with respect to what they thought the object looks like in reality (memory color). For each object and region the mean observer ratings were modeled by a bivariate Gaussian function. A statistical analysis showed significant (p < 0.001) differences between the region average observers and the global average observer obtained by pooling the data from all regions. However, the effect size of geographical region or culture was found to be small. In fact, the differences between the region average observers and the global average observer were found to of the same magnitude or smaller than the typical within region inter-observer variability. Thus, although statistical differences in color appearance ratings and memory between regions were found, regional impact is not likely to be of practical importance.

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The method of evaluating color rendering using a visual, graphical metric is presented. A two-dimensional Color Rendering Map (CRM) of a light source's color-rendering capabilities is explained and demonstrated. Extension of this technique to three-dimensional CRMs of objects under illumination is explained, including the method of introducing numerical indices in order to evaluate standards for specific applications in lighting. Three diverse applications, having a range from subtle to significant color variation, are shown with their respective CRMs. These three applications are also used to demonstrate how three differing light sources produce different maps. The results show a flexible, simple method to obtain a clear, visual determination of color rendering performance from differing sources used in differing illumination applications. The use of numeric indices in these applications shows how specific standards can be imposed in assessing the applicability of a light source.

We present in this work a calculation of the theoretical limits attainable for natural light emulation with regard to the joint optimization of the Luminous Efficacy of Radiation and color fidelity by using multiple reflectance spectra datasets, along with an implementation of a physical device that approaches these limits. A reduced visible spectrum of blackbody radiators is introduced and demonstrated which allows lamps designed to emulate natural light to operate with excellent color fidelity and higher efficiency as compared to full visible spectrum sources. It is shown that even though 3,000K and 5,500K blackbody sources have maximum efficacies of 21 lm/W and 89 lm/W, respectively, reduced-spectrum artificial light sources can exceed those values up to 363 lm/W and 313 lm/W, respectively, while retaining excellent color fidelity. Experimental demonstration approaching these values is accomplished through the design and implementation of a 12-channel light engine which emits arbitrarily-tunable spectra. The color fidelity of the designed spectra is assessed through Color Rendering Maps, showing that color fidelity is preserved uniformly over a large spectral reflectance dataset, unlike other approaches to generate white light.

In this Letter, the main attributes known to affect color quality are treated statistically over a set of 118 spectra representing the current mainstream lighting technology. The color rendering index (CRI) is used to assess color fidelity while colorfulness is used to complement CRI-R(a), supported by the growing evidence that assessment of light spectra cannot overlook color preference inputs. Colorfulness is evaluated by our optimal color (O(c)) index, through a code that computes the (MacAdam) theoretical maximum volumetric gamut of objects under a given illuminant for all the spectra in our database. Pearson correlation coefficients for CRI-R(a), the (Y. Ohno's) color quality scale (CQS) and O(c) show a high correlation (0.950) between CRI-R(a) and CQS-Q(a), while O(c) shows the lowest correlation (0.577) with CRI-R(a), meaning that O(c) represents the best complement to CRI-R(a) and Q(a) for an in-depth study of color quality.