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Local scene colour can influence the visual detectability of an object or target, but so can the familiarity, meaning, and global organisation of the scene. The aim of this study was to test whether the effects of local scene colour on target detectability are secondary to global effects. A target-detection task was undertaken by human observers with coloured images of natural scenes that were cut into quarters, randomly rearranged, and then reassembled. The target was a small, shaded, neutral grey sphere located randomly within the scene and matched in mean luminance to its local surround. It was found that observers’ target-detection performance with the rearranged images was about as good as with the original images. The combination of local colour properties, namely, lightness and the red-green and yellow-blue components of chroma, accounted, respectively, for 55% and 50% of observers’ detection performance with the original and rearranged images. Despite the disruption of global organisation, local scene colour continued to influence target detection.

The findings of Nadi Vijnana of 53 asymptomatic adult males were compared with the results of the blood examinations and the radial pulse pressure wave analysis conducted concomitantly. K pulse had elongated fatty pulse wave contour which is opposite to the slime V one, on the other hand, P pulse had the vibratory contour as the basic principles of Ayurveda. K pulse or K/P pulse had the largest inertia resistance. All these results were characterstic circulatory conditions and sympathetic tones for each pulse.

How well can categorical colour perception be maintained in natural environments with varying illuminants? To address this question, a colour-naming experiment was performed with colour-monitor images of natural scenes simulated under two different daylights of correlated colour temperature 6500 K and 25000 K. Images were obtained from a set of hyperspectral data to enable the accurate control of illuminant and reflectance spectra. Each scene contained a spherical test surface whose digitally manipulated spectral reflectance coincided with that of a sample drawn randomly from approximately 430 Munsell reflectances grouped into eight colour categories, namely, red, green, blue, yellow, pink, purple, brown, and orange. Observers had to name the colour of the test surface in each image, presented for 1 s, by pressing one of nine computer keys corresponding to the eight categorical colour names and a neutral category. Focal colours were estimated from the peaks of the smoothed distributions of observers’ naming responses in the CIE 1976 (u′, v′) chromaticity diagram. The effect of the illuminant change was quantified by a focal colour constancy index, with values 0 and 1 corresponding to no constancy and perfect constancy. Average levels of focal colour constancy were close to those from traditional measures of colour constancy, but with variation across categories and surface lightness. For blue and purple surfaces levels approached 0.9. For many surface colours, colour naming seems to be robust under illuminant changes and may help to anchor non-categorical judgements of arbitrary surface colours in natural scenes.

Estimates were made of the efficiency with which color spaces code color information from images of natural scenes. Six spaces were tested, namely, CIE XYZ tristimulus space, and the spaces CIELUV, CIELAB, CIELAB and S-CIELAB after chromatic adaptation with CMCCAT2000, and the space CIECAM02. For each space, the information available and the information retrieved in color matching were calculated for images of 50 natural scenes under different daylight illuminants. The information available was decomposed into components associated with the individual variables of the space and the interactions between them, including redundancy and illuminant-dependence. It was found that the information retrieved was much less than the information available, and that its decomposition depended on the space. The differing efficiencies of the spaces were interpreted in relation to the effectiveness of opponent-color and chromatic-adaptation transformations, and the statistics of images of natural scenes.

Although the total number of discernible colours in natural scenes has been estimated from physical data, the distribution of colours has received little attention. To address this issue, an analysis was made of hyperspectral images taken from a database of 50 urban and rural scenes. The colour volume of the database was computed by expressing each pixel of each image in CIELAB space. To derive the distribution of colours, the volume was segmented into just distinguishable sub-volumes, approximated by unit cubes, with each non-empty sub-volume assumed to represent one discernible colour and its pixel population the total number of times it occurs over the 50 scenes. It was found that the fraction of discernible colours expressed as a function of occurrence could be described by a negative power-law and that most discernible colours appeared only rarely. Thus, 70% of the total number of discernible colours constituted only about 3% of the pixels sampled, implying that most of the natural chromatic distribution fell within a small colour gamut, info:eu-repo/semantics/publishedVersion

Estimates of the frequency of metameric surfaces, which appear the same to the eye under one illuminant but different under another, were obtained from 50 hyperspectral images of natural scenes. The degree of metamerism was specified with respect to a color-difference measure after allowing for full chromatic adaptation. The relative frequency of metameric pairs of surfaces, expressed as a proportion of all pairs of surfaces in a scene, was very low. Depending on the criterion degree of metamerism, it ranged from about 10^-6 to 10^-4 for the largest illuminant change tested, which was from a daylight of correlated color temperature 25,000 K to one of 4000 K. But, given pairs of surfaces that were indistinguishable under one of these illuminants, the conditional relative frequency of metamerism was much higher, from about 10^-2 to 10^-1, sufficiently large to affect visual inferences about material identity. © 2006 Optical Society of America OCIS codes: 330.5030, 330.6180.