Testing the performance of CIECAM02 from 100 to 3500 cd/m²

Abstract

Color appearance models were developed to characterize the color attributes of stimuli under different viewing conditions based on data collected through magnitude estimation or color matching experiments. Although human beings experience very high light levels under daylight and the reproduction of colors under daylight is important in the color and imaging industries, the existing color appearance models were developed based on the data that were collected under the conditions with luminance levels below 700 cd/m 2 due to the lack of facilities to produce stable illumination at high light levels. A recent study investigating color preference of an artwork under a wide range of light levels from 20 to 15 000 lx suggested that CIECAM02 cannot accurately characterize the color appearance under extremely high light levels. This study was designed to directly test the performance of CIECAM02 from 100 to 3500 cd/m 2. Human observers performed color match for four hues under a series pairs of adapting conditions with a haploscopic viewing condition. It was found that CIECAM02 had the best performance in characterizing the hue angles but the worse performance in characterizing the brightness with a maximum underprediction around 200% across a wide range of luminance. This was mainly due to the fact that CIECAM02 was developed based on the data collected under relatively low adapting luminance levels. The color appearance model that was proposed to use the adapting luminance levels in characterizing the cone compression in the postadaptation process was found to have a much better performance in characterizing the brightness.

Colour Quality Evaluation of Bluish-Green Serpentinite Based on the CIECAM16 Model

“…Then, this model was modified to obtain a new version, the CIECAM02 model [35]. Researchers have conducted a lot of research on its uniformity [36,37], computational defects [38], and prediction performance [39,40], and the model has been widely used in the fields of medicine, textile, printing, etc. However, its calculation process is relatively complex, and its operational efficiency is rather low.…”

White appearance of virtual stimuli produced by augmented reality

“…It is well known that the color appearance of an object is affected by many factors 1 . For example, the spectrum of the illumination affects the color of a reflective object; the luminance and the chromaticities of the adapting condition affect the degree of chromatic adaptation 2‐6 and the colorfulness of the object 7‐9 ; the color of the background introduces the simultaneous color contrast, 10 and the luminance relationship between the adapting condition and the stimulus affects the viewing mode of the stimulus 6,11 . Some of these are well understood and have been considered in color appearance models (e.g., CIECAM02 12 ) for characterizing the color appearance of a stimulus under an adapting condition.…”