https://doi.org/10.2352/issn.2169-2629.2020.28.3 ©2020 Society for Imaging Science and Technology Effect of Peak Luminance on Perceptual Color Gamut Volume Fu Jiang,∗ Mark D. Fairchild,∗ Kenichiro Masaoka∗∗; ∗Munsell Color Science Laboratory, Rochester Institute of Technology, Rochester, New York, USA; ∗∗NHK Science & Technology Research Laboratories, Setagaya, Tokyo, Japan Abstract meaningless in terms of color appearance. In this paper, two psychophysical experiments were con- Color appearance models, as proposed and tested by CIE ducted to explore the effect of peak luminance on the perceptual Technical Committee 1-34, are required to have predictive corre- color gamut volume. The two experiments were designed with lates of at least the relative appearance attributes of lightness, two different image data rendering methods: clipping the peak chroma, and hue [3]. CIELAB is the widely used and well- luminance and scaling the image luminance to display’s peak lu- known example of such a color appearance space though its orig- minance capability. The perceptual color gamut volume showed inal goal was supra-threshold color-difference uniformity. How- a close linear relationship to the log scale of peak luminance. ever, CIELAB does not take the other attributes of the view- The results were found not consistent with the computational ing environment and background, such as absolute luminance 3D color appearance gamut volume from previous work. The level, into consideration. CIECAM02 is CIE-recommended difference was suspected to be caused by the different perspec- color appearance model for more complex viewing situations tives between the computational 3D color appearance gamut vol- [4]. In the years since adoption of CIECAM02, there are sev- ume and the experimental color gamut volume/perceptual color eral new proposed color appearance models with some modifi- gamut volume. cations and improvements, e.g. CIECAM02-UCS [5], CAM16 [6], CAM16-UCS [6]. CIECAM02-USC is an adjustment of Introduction the CIECAM02 aiming at reconciling color appearance scales with supra-threshold small color difference equations, noting The CIE has a defined color gamut as ”volume, area, or that both perceptual phenomena cannot be predicted using the solid in a colour space, consisting of all those colours that are same perceptual scales. CAM16 includes a modification to either: (a) present in a specific scene, artwork, photograph, pho- solve occasional inconvenient negative values in CIECAM02 tomechanical, or other reproduction; (b) capable of being created through a simple adjustment to the chromatic adaptation trans- using a particular output device and/or medium” [1]. The most form. CAM16-UCS is the similar as CIECAM02-UCS but based well-known so-called color gamut is the chromaticity gamut area on CAM16. There is no significant change in perceptual predic- of a display in u0v0 or xy chromaticity diagram. In the recent tions of these new color spaces from the current CIE recommen- decades, the 2D gamut in xy and u0v0 chromaticity diagrams has dation, CIECAM02. Therefore, color gamut volume computed been widely utilized by display manufacturers to characterize the in CIELAB and CIECAM02 are representations for color appear- display’s color reproduction ability. However, it is well known ance models. that at least a three-dimensional color space is necessary to de- scribe a color precisely. This is also typically how color is en- Masaoka and Nishida reported an interesting finding about coded/recorded. Therefore, the 2D gamut is only an illustration the RGB-primary display’s 3D color gamut volume in CIELAB of part of color rendition capabilities, but inappropriate for char- and JCh in CIECAM02 [7]. That work demonstrated a high acterizing display’s color appearance reproduction. Another in- correlation between the 3D color gamut volume expressed in teresting usage of the 2D gamut is that the u0v0 is generally more CIELAB, CIELUV, JCh and the primary area coverage in the favored than the xy by the manufacturers due to it being slightly CIE xy chromaticity diagram, better than achieved using the CIE 0 0 more perceptually uniform for threshold discrimination despite u v chromaticity diagram. Later, Masaoka further analyzed the the fact that chromaticity diagrams do not describe perceptual causes of these correlations and showed that it was due to the appearance. This is based on CIE u0v0 having better uniformity relative weighting of various chromaticity regions with respect performance based on MacAdam’s experiment on the visual sen- to the display gamut volume in those regions [8]. Masaoka fol- sitivity to color difference in daylight experiments back in 1942, lowed up that work by illustrating the importance of 3D color based on matching variability [2]. The experimental data demon- gamut volume in CIELAB for the comparison of High Dynamic strated the better color threshold uniformity in CIE u0v0. How- Range (HDR) - Wide Color Gamut (WCG) displays [9]. In ever, the experiment was based on one observer with the colors particular, this is critical when comparing RGB displays with on constant luminance level. Obviously, this is not sufficient as RGBW displays or when comparing displays with disparate peak a strong evidence to support the superiority of CIE u0v0 over CIE luminance levels or ratios between peak luminance and rendered xy as an approximation to the 3D color spaces, especially when diffuse white luminance. Jiang proposed a simple mathematical neither describes color appearance directly. While the u0v0 or xy model for computing the 3D color gamut volume in CIELAB, chromaticy diagram can be very useful in illustrating color stim- JCh from CIECAM02 considering a wide peak luminance range, ulus capability in a convenient way, the lack of the higher dimen- and different RGB primary, as well as different RGBW config- sions of appearance and strong evidence of the well correlation uration [10]. The model predicts a close-to-linear relationship between the 2D gamut and 3D color space limit the possibility of between the 3D color gamut volume and the peak luminance. approximating 3D color volume using 2D chromaticity gamuts. Along with the development and widespread use of the Moreover, the area coverage by the primary of display on the HDR WCG displays, there have been color spaces proposed chromaticiy diagram is either an interval scale nor a linear scale, specifically for HDR WCG. Fairchild and Chen proposed and i.e. the area coverage of one display can be said to be larger evaluated hdr-LAB and hdr-IPT color spaces based on experi- than the other but statements such as ”30% larger or smaller” are mental data of lightness above the diffuse white level [11]. The 28th Color and Imaging Conference Final Program and Proceedings 13 extended CIELAB still showed a reasonable performance for culations used. For such a type of experiment design, single predicting the lightness above the diffuse white. Recently, there white point should be used for the entire display, i.e. for both are two interesting proposed color spaces for usage in HDR images. Therefore, it is questionable to use two diffuse white WCG applications, ICtCp [12, 13] and Jzazbz [14]. ICtCp was levels for the two images presented simultaneously on the same developed on the perceptual quantizer (PQ) nonlinear function display. The current work has aimed to address this limitation in recommended by Society of Motion Picture & Television En- perceptual evaluation of gamut volume. gineers (SMPTE) [15]. The PQ is proposed based on Barten’s Two psychophysical experiments were conducted to eval- Contrast Sensitivity Function (CSF) model [16] to avoid quan- uate the effect of peak luminance on the 3D color appearance tization artifacts. Jzazbz utilizes the similar structure as ICtCp gamut volume. In these two experiments, the perceptual color with a further optimization of some parameters based on a com- gamut volume is defined by ”colorful and detailed”. The larger prehensive experimental data. Both color spaces showed reason- color gamut volume display is supposed to display the same im- able performances on micro color difference uniformity and hue age data more colorful and detailed, without additional color linearity[14, 17]. enhancement, tone mapping operator (TMO) or any other addi- tional manipulation in the display pipeline. The two experiments Gamut volume can also be computed in such a micro-color- follow two different diffuse white settings, a constant 200 cd/m2 difference uniform space. Kunkel proposed an ICtCp-based and a relative 20% to the peak luminance. The result is analyzed, adaptation hull to evaluate the color difference dataset from Pieri and compared with different parameters. and Pytlarz [17]. Kunkel suggested a method of stacking disks with 1 unit just-noticeable-difference (JND) thickness of a cer- Experimental Setup tain adaptation level. Therefore, this is based on stacking vol- In the two experiments, a professional 30-inch 4K OLED umes from multiple adaptation states, a way to model the best- master monitor (Sony BVM-X300, Japan) was used for present- case sensitivity to dynamic adaptation rather than the steady-state ing images. The display is capable of reaching a stable 1000 appearance to a fixed adaptation as is done with most implemen- cd/m2 peak luminance level while accepting both HLG and PQ tations of CIELAB and CIECAM02. The study also showed the encoding format. Figure 1 shows the setup, with the display sided advantage of the adaptive hull of ICtCp in predicting micro color by the two black panels, blocking any possible ambient lighting. difference [17]. The good performance from ICtCp and J a b z z z During the experiment, all room lights were turned off. All ob- for the small color differences is not surprising given that is what servers sat on the chair about 75 cm from the display. This meets the spaces were designed for. Certainly, within a certain small the ITU-R suggestions on the viewing distance for 4K display number of JND steps, the JND’s additivity might be meaning- [19].