SUMMARY Recent studies have shown that certain nocturnal insect and vertebrate species have true color vision under nocturnal illumination. Thus, their vision is potentially affected by changes in the spectral quality of twilight and nocturnal illumination, due to the presence or absence of the moon,artificial light pollution and other factors. We investigated this in the following manner. First we measured the spectral irradiance (from 300 to 700 nm) during the day, sunset, twilight, full moon, new moon, and in the presence of high levels of light pollution. The spectra were then converted to both human-based chromaticities and to relative quantum catches for the nocturnal hawkmoth Deilephila elpenor, which has color vision. The reflectance spectra of various flowers and leaves and the red hindwings of D. elpenor were also converted to chromaticities and relative quantum catches. Finally, the achromatic and chromatic contrasts (with and without von Kries color constancy) of the flowers and hindwings against a leaf background were determined under the various lighting environments. The twilight and nocturnal illuminants were substantially different from each other, resulting in significantly different contrasts. The addition of von Kries color constancy significantly reduced the effect of changing illuminants on chromatic contrast, suggesting that, even in this light-limited environment,the ability of color vision to provide reliable signals under changing illuminants may offset the concurrent threefold decrease in sensitivity and spatial resolution. Given this, color vision may be more common in crepuscular and nocturnal species than previously considered.

We have analyzed the colorimetric and spectral characteristics of 2600 daylight spectra (global spectral irradiances on a horizontal surface) measured for all sky states during a 2-year period at Granada, Spain. We describe in detail the chromaticity coordinates, correlated color temperatures (CCT), luminous efficacies, and relative UV and IR contents of Granada daylight. The chromaticity coordinates of Granada daylight lie far above the CIE locus at high CCTs (Ͼ9000 K), and a CCT of 5700 K best typifies this daylight. Our principalcomponents analysis shows that Granada daylight spectra can be adequately represented by using sixdimensional linear models in the visible, whereas seven-dimensional models are required if we include the UV or near-IR. Yet on average only three-dimensional models are needed to reconstruct spectra that are colorimetrically indistinguishable from the original spectra.

In a previous work [Appl. Opt.44, 5688 (2005)] we found the optimum sensors for a planned multispectral system for measuring skylight in the presence of noise by adapting a linear spectral recovery algorithm proposed by Maloney and Wandell [J. Opt. Soc. Am. A3, 29 (1986)]. Here we continue along these lines by simulating the responses of three to five Gaussian sensors and recovering spectral information from noise-affected sensor data by trying out four different estimation algorithms, three different sizes for the training set of spectra, and various linear bases. We attempt to find the optimum combination of sensors, recovery method, linear basis, and matrix size to recover the best skylight spectral power distributions from colorimetric and spectral (in the visible range) points of view. We show how all these parameters play an important role in the practical design of a real multispectral system and how to obtain several relevant conclusions from simulating the behavior of sensors in the presence of noise.

By the principal-value decomposition process, we have obtained two linear bases for representing the spectral power distributions of illuminants, applicable for algorithms of color synthesis and analysis in artificial vision: one from experimental measurements of daylight and another combining both natural and artificial illuminants. The first basis adequately represents daylight with dimension 3, in accordance with the previous results of Judd et al. [J. Opt. Soc. Am. 54, 1031 (1964)]; however, it does not adequately represent artificial illuminants, even with a higher dimension. In the case of the second basis, many good results are obtained in the reconstruction of the spectral power distribution both of daylight and of artificial illuminants, including some fluorescent lights, with dimension 7 or even less. In consequence, we show the possibility of obtaining linear bases of a low dimension, even when the set of illuminants that we try to represent presents a certain variability in shape.

Natural outdoor illumination daily undergoes large changes in its correlated color temperature (CCT), yet existing equations for calculating CCT from chromaticity coordinates span only part of this range. To improve both the gamut and accuracy of these CCT calculations, we use chromaticities calculated from our measurements of nearly 7000 daylight and skylight spectra to test an equation that accurately maps CIE 1931 chromaticities x and y into CCT. We extend the work of McCamy [Color Res. Appl. 12, 285-287 (1992)] by using a chromaticity epicenter for CCT and the inverse slope of the line that connects it to x and y. With two epicenters for different CCT ranges, our simple equation is accurate across wide chromaticity and CCT ranges (3000-10(6) K) spanned by daylight and skylight.

As part of our ongoing research into the clear daytime sky's visible structure, we analyze over 1,500 skylight spectra measured during a seven-month period in Granada, Spain. We use spectral radiances measured within 3 degrees fields of view (FOV's) to define colorimetric characteristics along four sky meridians: the solar meridian and three meridians at azimuths of 45 degrees, 90 degrees, and 315 degrees relative to it. The resulting clear-sky chromaticities in 44 different view directions (1) are close to but do not coincide with the CIE daylight locus, (2) form V-shaped meridional chromaticity curves along it (as expected from theory), and (3) have correlated color temperatures (CCT's) ranging from 3,800 K to infinity K. We also routinely observe that sky color and luminance are asymmetric about the solar meridian, usually perceptibly so. A principal-components analysis shows that three vectors are required for accurate clear-sky colorimetry, whereas six are needed for spectral analyses.

The commercialization of EnChroma glasses has generated great expectations for people to be able to see new colors or even correct color vision deficiency (CVD). We evaluate the effectiveness of these glasses using two complementary strategies for the first time. The first consists of using the three classical types of tests-recognition, arrangement and discrimination-with and without glasses, with a high number of individuals. In the second, we use the spectral transmittance of the glasses to simulate the appearance of stimuli in a set of scenes for normal observers and observers with CVD. The results show that the glasses introduce a variation of the perceived color, but neither improve results in the diagnosis tests nor allow the observers with CVD to have a more normal color vision.

In earlier work [J. Opt. Soc. Am. A 21, 13-23 (2004)], we showed that a combination of linear models and optimum Gaussian sensors obtained by an exhaustive search can recover daylight spectra reliably from broadband sensor data. Thus our algorithm and sensors could be used to design an accurate, relatively inexpensive system for spectral imaging of daylight. Here we improve our simulation of the multispectral system by (1) considering the different kinds of noise inherent in electronic devices such as change-coupled devices (CCDs) or complementary metal-oxide semiconductors (CMOS) and (2) extending our research to a different kind of natural illumination, skylight. Because exhaustive searches are expensive computationally, here we switch to a simulated annealing algorithm to define the optimum sensors for recovering skylight spectra. The annealing algorithm requires us to minimize a single cost function, and so we develop one that calculates both the spectral and colorimetric similarity of any pair of skylight spectra. We show that the simulated annealing algorithm yields results similar to the exhaustive search but with much less computational effort. Our technique lets us study the properties of optimum sensors in the presence of noise, one side effect of which is that adding more sensors may not improve the spectral recovery.