Common descriptors of light quality fail to predict the chromatic diversity produced by the same illuminant in different
contexts. The aim of this paper was to study the influence of the chromatic adaptation in the context of the development
of the color diversity index, a new index capable of predicting illuminant-induced variations in several types of images.
The spectral reflectance obtained from hyperspectral images of natural, indoor and artistic paintings, and the spectral
reflectance of 1264 Munsell surfaces were converted into the CIELAB color space for each of the 55 CIE illuminants
and 5 light sources tested. The influence of the CAT02 chromatic adaptation was estimated for each illuminant and for
each scene. The CIELAB volume was estimated by the convex hull method and the number of discernible colors was
estimated by segmenting the CIELAB color volume into unitary cubes and by counting the number of non-empty cubes.
High correlation was found between the CIELAB volume occupied by the Munsell surfaces and the number of
discernible colors and the CILEAB color volume of the colors in all images analyzed. The effects of the chromatic
adaptation were marginal and did not change the overall result. These results indicate that the efficiency of the new
illuminant chromatic diversity index is not influenced by chromatic adaptation.
The advent of modern solid-state sources enabled almost any spectrum for lighting and a wide range of possibilities in
color rendering. The quality of the lighting has been typically evaluated by the color rendering index which measures
how much the colors of objects illuminated by the light under test look similar to those produced when the objects are
illuminated by the daylight or a conventional incandescent light. On the other hand, how colorful or vivid the colors
under the illumination are perceived is also an important quality to evaluate lighting. We investigated, computationally,
the spectral profiles of the illumination that maximizes the theoretical limit of the perceivable object colors. A large
number of metamers with various degree of smoothness were generated using the Schmitt's elements method at
chromaticity points on and around the Planckian locus ranging from 2,222 K to 20,000 K. The general color rendering
index (CRI) and MacAdam volumes in CIELAB color space were calculated for each metamer. The metamers
maximizing the CRI had smoother spectra than the metamers maximizing the MacAdam volume. These results show that
maximum colorfulness in nature can only be obtained with spectrally non-smooth illumination.
Color perception in real conditions is determined by the spectral and spatial properties of objects and illumination. These
properties are best evaluated by spectral imaging, a technique that records the reflecting spectral profile for each point of
the scene. Using this technique on a set of natural scenes it was found that the color gamut expressed in the CIELAB
color space is much smaller than the theoretical limits defined for the object colors. Moreover, the colors more frequent
are those around the white point and their frequency of occurrence can be well described by a power law. Spatial
variations of the spectral composition of the illumination across natural scenes were also quantified by placing small
reflecting spheres in different locations of the scenes. The extent of these variations across scenes was found to be large
and of the same order of magnitude as the variations of daylight along the day. These findings show that colors in nature
are considerable constrained and that constancy mechanisms must be efficient over a wide range of stimuli variations to
compensate for large natural variations of illumination.
We report a hyperspectral imaging system to measure the reflectance spectra of real human irises with high spatial resolution. A set of ocular prosthesis was used as the control condition. Reflectance data were decorrelated by the principal-component analysis. The main conclusion is that spectral complexity of the human iris is considerable: between 9 and 11 principal components are necessary to account for 99% of the cumulative variance in human irises. Correcting image misalignments associated with spontaneous ocular movements did not influence this result. The data also suggests a correlation between the first principal component and different levels of melanin present in the irises. It was also found that although the spectral characteristics of the first five principal components were not affected by the radial and angular position of the selected iridal areas, they affect the higher-order ones, suggesting a possible influence of the iris texture. The results show that hyperspectral imaging in the iris, together with adequate spectroscopic analyses provide more information than conventional colorimetric methods, making hyperspectral imaging suitable for the characterization of melanin and the noninvasive diagnosis of ocular diseases and iris color.