Color constancy in a scene with bright colors that do not have a fully natural surface appearance

Fukuda, Koichiro; Uchikawa, Keiji

doi:10.1364/josaa.31.00a239

Cited by 7 publications

(8 citation statements)

References 30 publications

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“…In its extreme form, a specular highlight would be particularly helpful because they directly convey an illuminant to the eye [9]. However, Fukuda and Uchikawa [10] found that colors appearing in the aperture-color mode do not significantly contribute to the degree of color constancy, suggesting that the visual system primarily exploits the colors in the surface-color appearance to estimate an illuminant.…”

Section: Introductionmentioning

confidence: 99%

Effects of surrounding stimulus properties on color constancy based on luminance balance

2016

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The visual system needs to discount the influence of an illuminant to achieve color constancy. Uchikawa et al. [J. Opt. Soc. Am. A29, A133 (2012) showed that the luminance-balance change of surfaces in a scene contributes to illuminant estimation; however, its effect was substantially less than the chromaticity change. We conduct three experiments to reinforce the previous findings and investigate possible factors that can influence the effect of luminance balance. Experimental results replicate the previous finding; i.e., luminance balance makes a small, but significant, contribution to illuminant estimation. We find that stimulus dimensionality affects neither the degree of color constancy nor the effect of luminance balance. Unlike chromaticity-based color constancy, chromatic variation does not influence the effect of luminance balance. It is shown that luminance-balance-based estimation of an illuminant performs better for scenes with reddish or bluish surfaces. This suggests that the visual system exploits the optimal color distribution for illuminant estimation [J. Opt. Soc. Am. A 29, A133(2012)].

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Section: Introductionmentioning

confidence: 99%

Effects of surrounding stimulus properties on color constancy based on luminance balance

2016

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“…In a series of previous papers, we have demonstrated the importance of the luminance-chromaticity association (Uchikawa et al, 2012;Morimoto, Fukuda, & Uchikawa, 2016). It was also shown that observers seem to ignore surfaces that appear self-luminous from the consideration of illuminant influence (Fukuda & Uchikawa, 2014). We also suggested that the optimal color model might describe bistable perception in the #TheDress phenomenon (Uchikawa, Morimoto, & Matsumoto, 2017).…”

Section: Introductionmentioning

confidence: 76%

Human color constancy based on the geometry of color distributions

et al. 2021

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The physical inputs to our visual system are dictated by the interplay between lights and surfaces; thus, for surface color to be stably perceived, the influence of the illuminant must be discounted. To reveal our strategy to infer the illuminant color, we conducted three psychophysical experiments designed to test our optimal color hypothesis that we internalize the physical color gamut under various illuminants and apply the prior to estimate the illuminant color. In each experiment, we presented 61 hexagons arranged without spatial gaps, where the surrounding 60 hexagons were set to have a specific shape in their color distribution. We asked participants to adjust the color of a center test field so that it appeared to be a full-white surface placed under a test illuminant. Results and computational modeling suggested that, although our proposed model is limited in accounting for estimation of illuminant intensity by human observers, it agrees fairly well with the estimates of illuminant chromaticity in most tested conditions. The accuracy of estimation generally outperformed other tested conventional color constancy models. These results support the hypothesis that our visual system can utilize the geometry of scene color distribution to achieve color constancy.

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“…This example highlights that generation of luminous percept needs to be incorporated into a process of color constancy. In fact, Fukuda & Uchikawa (2014) showed that a surface appearing in aperture-color mode does not have a strong influence on observers’ estimates of illuminant.…”

Section: Discussionmentioning

confidence: 99%

“…This physical gamut can be visualized by hypothetical surface called optimal colors (MacAdam 1935a, MacAdam 1935b) which will be detailed in General Method section. This hypothesis was specifically led up based on the observation made in a series of color constancy experiments (Uchikawa et al, 2012; Fukuda & Uchikawa 2014; Morimoto et al, 2016; Morimoto et al, 2021). In these studies, we developed a model for illuminant estimation that operated on the assumption that visual system internalizes the gamut of surface colors under various illuminants (i.e.…”

Section: Introductionmentioning

confidence: 99%

Luminosity thresholds of colored surfaces are determined by their upper-limit luminances empirically internalized in the visual system

Morimoto

Numata

Fukuda

et al. 2021

Preprint

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Some objects in the real world themselves emit a light, and we typically have a fairly good idea as to whether a given object is self-luminous or illuminated by a light source. However, it is not well understood how our visual system makes this judgement. This study aimed to identify determinants of luminosity threshold, a luminance level at which the surface begins to appear self-luminous. We specifically tested a hypothesis that our visual system knows a maximum luminance level that a surface can reach under the physical constraint that surface cannot reflect more lights that incident lights and apply this prior to determine the luminosity thresholds. Observers were presented a 2-degree circular test field surrounded by numerous overlapping color circles, and luminosity thresholds were measured as a function of (i) the chromaticity of the test field, (ii) the shape of surrounding color distribution and (iii) the color of illuminant lighting surrounding colors. We found that the luminosity thresholds strongly depended on test chromaticity and peaked around the chromaticity of test illuminants and decreased as the purity of the test chromaticity increased. However, the locus of luminosity thresholds over chromaticities were nearly invariant regardless of the shape of surrounding color distribution and generally well resembled the locus drawn from theoretical upper-limit luminance but also the locus drawn from the upper boundary of real objects. These trends were particularly evident for test illuminants on blue-yellow axis and curiously did not hold under atypical illuminants such as magenta or green. Based on these results, we propose a theory that our visual system empirically internalizes the gamut of surface colors under illuminants typically found in natural environments and a given surface appears self-luminous when its luminance exceeds this heuristic upper-limit luminance.

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Color constancy in a scene with bright colors that do not have a fully natural surface appearance

Cited by 7 publications

References 30 publications

Effects of surrounding stimulus properties on color constancy based on luminance balance

Effects of surrounding stimulus properties on color constancy based on luminance balance

Human color constancy based on the geometry of color distributions

Luminosity thresholds of colored surfaces are determined by their upper-limit luminances empirically internalized in the visual system

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