Chromatic effects of metamers of D65 on art paintings

Pinto, Paulo; Felgueiras, Paulo Eduardo Reis; Linhares, João M. M.; Nascimento, Sérgio M. C.

doi:10.1111/j.1475-1313.2010.00726.x

Cited by 13 publications

(6 citation statements)

References 17 publications

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“…The paintings were from several epochs and artists and represent different subjects. More detailed information concerning these paintings is given elsewhere [35,42]. These 44 paintings were selected to minimize bias to a specific artist or painting style.…”

Section: Paintingsmentioning

confidence: 99%

“…Figure 5(a) shows the two distributions for the areas expressed in CIELAB units. Symbols [35,42]. For the analysis all paintings were digitalized with a hyperspectral system.…”

Section: A Gamut Analysismentioning

confidence: 99%

“…Hyperspectral data were used to create maps of pigment distribution in van Gogh's paintings [34]. Statistical studies of the colors of paintings were also carried out to evaluate some aspects of the color rendering of paintings [35] and to estimate aesthetic [36][37][38] and emotional [39] responses. Edge features, including color and texture, were used to discriminate paintings from photographs [40,41].…”

Section: Introductionmentioning

confidence: 99%

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Statistics of colors in paintings and natural scenes

et al. 2016

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Painters reproduce some spatial statistical regularities of natural scenes. To what extent they replicate their color statistics is an open question. We investigated this question by analyzing the colors of 50 natural scenes of rural and urban environments and 44 paintings with abstract and figurative compositions. The analysis was carried out using hyperspectral imaging data from both sets and focused on the gamut and distribution of colors in the CIELAB space. The results showed that paintings, like natural scenes, have gamuts with elongated shapes in the yellow-blue direction but more tilted to the red direction. It was also found that the fraction of discernible colors, expressed as a function of the number of occurrences in the scene or painting, is well described by power laws. These have similar distribution of slopes in a log-log scale for paintings and natural scenes. These features are observed in both abstract and figurative compositions. These results suggest that the underlying chromatic structure of artistic compositions generally follows the main statistical features of the natural environment.

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Section: Paintingsmentioning

confidence: 99%

“…Figure 5(a) shows the two distributions for the areas expressed in CIELAB units. Symbols [35,42]. For the analysis all paintings were digitalized with a hyperspectral system.…”

Section: A Gamut Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Statistics of colors in paintings and natural scenes

et al. 2016

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“…Implemented with intelligently controlled LED clusters that generate metamers of white light, the illuminants with continuously tunable color rendition properties have been developed [7] . Such intelligent light sources have been applied to many practical needs, including improving visual impression of art work [8][9][10] and restoring the original colors of aged paintings [11] . Also they can meet specific color-quality requirements of people with different subjective needs, including those depending on cultural backgrounds.…”

Section: Introductionmentioning

confidence: 99%

LED illuminant on the ambient light

2014

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We develop an approach for combining illuminance and spectral power distribution of the LED and ambient light and apply our technique for developing an LED camera flashlight balancing the illuminance contrast between object and background. Our method uses the closed loop, multiobjective optimization comprising: (1) characterizing the lighting task by illuminance, correlated color temperature (CCT), and statistical color quality indices that include a set of Statistical Color Quality Metrics and the Color Rendition Index (CRI) implemented with indexes of S (saturation) or D (dulling); (2) measuring the illuminance and the spectrum of the ambient light on the target lighting surface, which might depend on all the sources proving illumination and on the reflected light; (3) determining the desired illuminance of the LED source on the target lighting surface; (4) calculating the desired luminous flux of the LED source according to the desired illuminance; (5) constituting the SPD of the LED source; (6) calculating the relative spectra counts of the LED source and the ambient light on the target lighting surface (7) calculating the CCT and statistical color quality indexes of the combined light; (8) repeating the above steps until the resulting SPD is close enough to the expectation. Using the above method, an LED camera flashlight has been designed, which works together with usual fluorescent ambient light and generates working lighting environment with high fidelity and high CCT (6000K). The spectrum and luminous flux of the LED lamp is automatically tunable with a change of the ambient light.

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“…the color rendering index (CRI) 5 . The chromatic diversity 6,7 is generally not evaluated although the effects of spectrally structure spectra on color diversity have been studied 8,9 . Several other limitations on current rendering indices are well described [10][11][12][13][14][15] .…”

Section: Introductionmentioning

confidence: 99%

Color diversity index: the effect of chromatic adaptation

Linhares

Nascimento

2011

SPIE Proceedings

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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.

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Chromatic effects of metamers of D65 on art paintings

Cited by 13 publications

References 17 publications

Statistics of colors in paintings and natural scenes

Statistics of colors in paintings and natural scenes

LED illuminant on the ambient light

Color diversity index: the effect of chromatic adaptation

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