Using hue scaling to specify color appearance and to derive color differences

1990 ◽  
Author(s):  
Israel Abramov ◽  
James Gordon ◽  
Hoover Chan
Keyword(s):  
Color Appearance ◽  
Color Differences ◽  
Hue Scaling

scholarly journals A Novel Method of Color Appearance Simulation Using Achromatic Point Locus With Lightness Dependence

i-Perception ◽  
2018 ◽  
Vol 9 (2) ◽  
pp. 204166951876173 ◽  
Author(s):  
Ichiro Kuriki
Keyword(s):  
Dynamic Range ◽  
Simple Algorithm ◽  
Color Difference ◽  
Color Appearance ◽  
Proposed Model ◽  
Color Differences ◽  
Cone Response ◽  
Human Color Vision ◽  
Conventional Models ◽  
Cie Lab

The purpose of the present study is to propose a simple algorithm for color appearance simulation under a color illuminant. Achromatic point is a chromaticity of rays that appear neither red nor green, neither blue nor yellow under a given illuminant condition. Saturation and hue of surface colors are evaluated with respect to the achromatic point of the same lightness, while the achromatic point under a colored illuminant depends on the lightness tested. We previously found that this achromatic point locus can be simply approximated as a line with a parallel offset from the lightness axis of CIE LAB space normalized to daylight. We propose a model that applies shifts in the lightness direction after applying hue/saturation shifts using the cone-response (von Kries) transformation under an iso-lightness constraint, such that achromatic points would be aligned with the lightness axis in the CIE LAB space under daylight normalization. We tested this algorithm, which incorporates evaluation of color appearance in different lightness levels, using #theDress image. Resemblance between our simulation and subjective color-matching results implies that human color vision possibly processes shifts in color and lightness independently, as a previous study reported. Changes in the chromaticity distribution of the images were compared with conventional models, and the proposed model preserved relative color difference better, especially at the lower lightness levels. The better performance in lower lightness levels would be advantageous in displays with wider dynamic range in luminance. This implies that the proposed model is effective in simulating color appearance of images with nonnegligible lightness and color differences.

Transitions between color categories mapped with a reverse Stroop task

2006 ◽  
Vol 23 (3-4) ◽  
pp. 453-460 ◽  
Author(s):  
HANNAH E. SMITHSON ◽  
SABAH S. KHAN ◽  
LINDSAY T. SHARPE ◽  
ANDREW STOCKMAN
Keyword(s):  
Stroop Task ◽  
Color Word ◽  
Color Space ◽  
Reaction Times ◽  
Color Appearance ◽  
Target Color ◽  
Color Category ◽  
Color Categories ◽  
Distractor Color ◽  
Hue Scaling

In the reverse Stroop task, observers are instructed to ignore the ink color in which a color word is printed (the distractor color) and to respond to the meaning of the color word (the target). Reaction times (RTs) are faster with congruent combinations when the ink color matches the word than with incongruent combinations when the ink color does not match the word. We manipulated the distracting ink color from congruent to incongruent and measured the transition from facilitation to interference. In Experiment 1, we confirmed that this transition could be assessed independently from the contextual influence of particular sets of stimuli and responses, implying that the color space in which interference and facilitation occurs is generalizable. In Experiment 2, we obtained reverse Stroop data for transitions between red and yellow, yellow and green, green and blue, and blue and red, and compared them with independent estimates of color appearance obtained by hue scaling for the same chromaticity samples. We find that the magnitude of the reverse Stroop effect can provide a reliable index of the similarity of color appearance between the distracting chromaticity and the color category represented by the target color word. Moreover, it will allow us to quantify the mapping between the chromaticity space defined at the cone photoreceptors and a cognitive color space defined at an advanced level of neural processing.

Large and small color differences: predicting them from hue scaling

1991 ◽  
Author(s):  
Hoover Chan ◽  
Israel Abramov ◽  
James Gordon
Keyword(s):  
Color Differences ◽  
Hue Scaling

Change of color appearance due to extremely high light level: corresponding colors under 100 and 3000 cd/m2

2019 ◽  
Vol 2019 (1) ◽  
pp. 320-325 ◽  
Author(s):  
Wenyu Bao ◽  
Minchen Wei
Keyword(s):  
Light Level ◽  
Limited Range ◽  
High Light ◽  
Color Preference ◽  
Color Appearance ◽  
Appearance Model ◽  
Color Matching ◽  
Light Levels ◽  
Appearance Models ◽  
Psychophysical Study

Great efforts have been made to develop color appearance models to predict color appearance of stimuli under various viewing conditions. CIECAM02, the most widely used color appearance model, and many other color appearance models were all developed based on corresponding color datasets, including LUTCHI data. Though the effect of adapting light level on color appearance, which is known as "Hunt Effect", is well known, most of the corresponding color datasets were collected within a limited range of light levels (i.e., below 700 cd/m2), which was much lower than that under daylight. A recent study investigating color preference of an artwork under various light levels from 20 to 15000 lx suggested that the existing color appearance models may not accurately characterize the color appearance of stimuli under extremely high light levels, based on the assumption that the same preference judgements were due to the same color appearance. This article reports a psychophysical study, which was designed to directly collect corresponding colors under two light levels— 100 and 3000 cd/m2 (i.e., ≈ 314 and 9420 lx). Human observers completed haploscopic color matching for four color stimuli (i.e., red, green, blue, and yellow) under the two light levels at 2700 or 6500 K. Though the Hunt Effect was supported by the results, CIECAM02 was found to have large errors under the extremely high light levels, especially when the CCT was low.

Real-world environment affects the color appearance of virtual stimuli produced by augmented reality

2019 ◽  
Vol 2019 (1) ◽  
pp. 237-242
Author(s):  
Siyuan Chen ◽  
Minchen Wei
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Mixed Reality ◽  
Rapid Development ◽  
Light Level ◽  
Color Appearance ◽  
Chromatic Adaptation ◽  
Lighting Condition ◽  
The Real ◽  
World Environment

Color appearance models have been extensively studied for characterizing and predicting the perceived color appearance of physical color stimuli under different viewing conditions. These stimuli are either surface colors reflecting illumination or self-luminous emitting radiations. With the rapid development of augmented reality (AR) and mixed reality (MR), it is critically important to understand how the color appearance of the objects that are produced by AR and MR are perceived, especially when these objects are overlaid on the real world. In this study, nine lighting conditions, with different correlated color temperature (CCT) levels and light levels, were created in a real-world environment. Under each lighting condition, human observers adjusted the color appearance of a virtual stimulus, which was overlaid on a real-world luminous environment, until it appeared the whitest. It was found that the CCT and light level of the real-world environment significantly affected the color appearance of the white stimulus, especially when the light level was high. Moreover, a lower degree of chromatic adaptation was found for viewing the virtual stimulus that was overlaid on the real world.

Color Constancy

2017 ◽  
Author(s):  
Joshua Gert
Keyword(s):  
Visual Representation ◽  
Color Constancy ◽  
Color Appearance ◽  
Fine Grained ◽  
Hybrid View

This chapter presents an account of color constancy that explains a well-known division in the data from color-constancy experiments: So-called “paper matches” exhibit a much higher level of constancy than so-called “hue-saturation matches.” It argues that the visual representation of objective color is the representation of something associated with a function from viewing circumstances to color appearances. Thus, a relatively robust constancy in the representation of objective color is perfectly consistent with a relatively less robust level of constancy in color appearance. The account also endorses Hilbert’s idea that we can represent the color of the illumination on a surface as well as the color of the surface itself. Finally, the chapter addresses an objection to the hybrid view that notes our capacity to make very fine-grained distinctions between the objective colors of surfaces.

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