Computerized simulation of color appearance for anomalous trichromats using the multispectral image: erratum

2020 ◽  
Vol 37 (7) ◽  
pp. 1075
Author(s):  
Hirohisa Yagchi ◽  
Junyan Luo ◽  
Miharu Kato ◽  
Yoko Mizokami
Keyword(s):  
Multispectral Image ◽  
Color Appearance ◽  
Computerized Simulation

Computerized simulation of color appearance for dichromats

1997 ◽  
Vol 14 (10) ◽  
pp. 2647 ◽  
Author(s):  
Hans Brettel ◽  
Françoise Viénot ◽  
John D. Mollon
Keyword(s):  
Color Appearance ◽  
Computerized Simulation

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.

Multispectral image observations of earthlimb clutter with the MSTI-3 medium wavelength infrared sensor

1998 ◽  
Author(s):  
James Fraser ◽  
Michael Winings ◽  
Robert Sears ◽  
Stephen Hearney
Keyword(s):  
Multispectral Image ◽  
Infrared Sensor
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