Superior discrimination for hue than for saturation and an explanation in terms of correlated neural noise

Danilova, Marina; Mollon, J. D.

doi:10.1098/rspb.2016.0164

Cited by 15 publications

(18 citation statements)

References 36 publications

(72 reference statements)

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“…For example, Krauskopf and Gegenfurtner (1992) found that detection thresholds for very small targets against large uniform chromatic backgrounds are constant and symmetric in the red and green directions for varying background chromaticities, while thresholds increase symmetrically in the blue and yellow directions for increasing levels of background S-cone stimulation. Another asymmetry that has been observed in chromatic discrimination experiments is between changes in hue and changes in saturation, with higher thresholds reported for the latter (Danilova & Mollon, 2016; Elliott, Werner, & Webster, 2012; Krauskopf & Gegenfurtner, 1992).…”

Section: Discussionmentioning

confidence: 99%

Illumination discrimination for chromatically biased illuminations: Implications for color constancy

et al. 2019

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We measured discrimination thresholds for illumination changes along different chromatic directions starting from chromatically biased reference illuminations. Participants viewed a Mondrian-papered scene illuminated by LED lamps. The scene was first illuminated by a reference illumination, followed by two comparisons. One comparison matched the reference (the target); the other (the test) varied from the reference, nominally either bluer, yellower, redder, or greener. The participant's task was to correctly select the target. A staircase procedure found thresholds for discrimination of an illumination change along each axis of chromatic change. Nine participants completed the task for five different reference illumination conditions (neutral, blue, yellow, red, and green). We find that relative discrimination thresholds for different chromatic directions of illumination change vary with the reference illumination. For the neutral reference, there is a trend for thresholds to be highest in the bluer illumination-change direction, replicating our previous reports of a “blue bias” for neutral reference illuminations. For the four chromatic references (blue, yellow, red, and green), the change in illumination toward the neutral reference is less well discriminated than changes in the other directions: a “neutral bias.” The results have implications for color constancy: In considering the stability of surface appearance under changes in illumination, both the starting chromaticity of the illumination and direction of change must be considered, as well as the chromatic characteristics of the surface reflectance ensemble. They also suggest it will be worthwhile to explore whether and how the human visual system has internalized the statistics of natural illumination changes.

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Section: Discussionmentioning

confidence: 99%

Illumination discrimination for chromatically biased illuminations: Implications for color constancy

et al. 2019

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“…In addition to the color difference, hue shifts were reported to provide more specific information about the color quality of the artwork. Because hue discrimination thresholds are lower than saturation discrimination thresholds (Danilova and Mollon 2016), hue shift calculations were added to capture the most essential dimension of the color quality of the artwork under optimized lighting conditions. Color (ΔE 00 ) and hue (ΔH′) differences were calculated using CIE 1976 (L*, a*, b*) and CIEDE2000 color difference formulae (CIE 2004b).…”

Section: Methodsmentioning

confidence: 99%

Spectral Optimization to Minimize Light Absorbed by Artwork

Durmus

Abdalla

Duis

et al. 2018

LEUKOS

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Light is needed to appreciate artwork, but visible radiation causes damage by photochemical action. Photons trigger photochemical action only when they are absorbed by the object. Damage to sensitive materials can be reduced by optimizing the spectrum of a light source to the reflectance factor of a museum artifact. Absorption minimization approaches can be utilized to quantify and optimize typically conflicting parameters, such as damage due to light absorption, color quality of artwork, and energy consumption. In this project, seven narrowband light emitting diodes (LEDs) are optimized using a multi-objective genetic algorithm to reduce light absorption and energy consumption, while maintaining the color appearance of five paints (blue, green, yellow, orange, red). Results indicate that optimized test spectra can reduce light absorption between 18% and 48%, without causing perceptible color or hue shifts in the paintings. Parallel to absorption, energy consumption is almost halved for all of the paints (between 42% and 48%). Optimizing the light source spectrum can aid in conservation of art collections in museums by reducing damage caused by optical radiation while preserving color fidelity.

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“…Finally, the third approach is to employ a multiplicative rather than an additive noise model. The precision of perceptual representations is often the highest at the current adaptation point [36–38]. This observation can be incorporated in the model by assuming that along each perceptual dimension noise scales as a function of test distance from the target.…”

Section: Discussionmentioning

confidence: 99%

The relative contribution of color and material in object selection

2019

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Object perception is inherently multidimensional: information about color, material, texture and shape all guide how we interact with objects. We developed a paradigm that quantifies how two object properties (color and material) combine in object selection. On each experimental trial, observers viewed three blob-shaped objects—the target and two tests—and selected the test that was more similar to the target. Across trials, the target object was fixed, while the tests varied in color (across 7 levels) and material (also 7 levels, yielding 49 possible stimuli). We used an adaptive trial selection procedure (Quest+) to present, on each trial, the stimulus test pair that is most informative of underlying processes that drive selection. We present a novel computational model that allows us to describe observers’ selection data in terms of (1) the underlying perceptual stimulus representation and (2) a color-material weight, which quantifies the relative importance of color vs. material in selection. We document large individual differences in the color-material weight across the 12 observers we tested. Furthermore, our analyses reveal limits on how precisely selection data simultaneously constrain perceptual representations and the color-material weight. These limits should guide future efforts towards understanding the multidimensional nature of object perception.

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Superior discrimination for hue than for saturation and an explanation in terms of correlated neural noise

Cited by 15 publications

References 36 publications

Illumination discrimination for chromatically biased illuminations: Implications for color constancy

Illumination discrimination for chromatically biased illuminations: Implications for color constancy

Spectral Optimization to Minimize Light Absorbed by Artwork

The relative contribution of color and material in object selection

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