FEATURE

We selected appropriate color-rendering indices and de-termined their recommended values for white LED lighting in ultrahigh-definition television (UHDTV) program pro-duction. Since UHDTV cameras have more accurate color reproduction capability than HDTV cameras, the color ren-dering properties of the lighting are more critical. By evalu-ating images taken under white LEDs with different color rendering indices, we found that the combination of Ra and R9 is the most appropriate color-rendering index and that the values Ra ≥ 90 and R9 ≥ 80 are to be recommended for white LED lighting in UHDTV program production.

1. IntroductionThe UHDTV color gamut specified in Recommendation

ITU-R BT.2020 (Rec. 2020)1) is wider than the HDTV color gamut specified by Recommendation ITU-R BT.709 (Rec. 709)2). UHDTV cameras have more accurate color repro-duction than HDTV cameras3). Because of this accurate color reproduction, higher color-rendering properties are required in lighting for UHDTV production. A transition in lighting from incandescent lamps and fluorescent lamps to white LED lighting is progressing concurrently with the transition of the television system from HDTV to UHDTV. Although white LED lighting is expected to be implement-ed in television studios and sports facilities, the appropriate color-rendering indices for evaluating white LED lighting in UHDTV production are still unknown.

The color-rendering index (CRI), which is defined by the International Commission on Illumination (CIE), is a quantitative measure of the ability of a light source to reveal the colors of various objects in comparison to a blackbody radiator or daylight4). The standard CRI values (R1-R8) are derived from CIE 1974 test-color samples consisting of eight low-saturation colors and six special CRI values (R9-R14) derived from the realistic colors red, yellow, green, blue, Caucasian skin color, and green foliage, respectively. In addition, Japanese Industrial Standards (JIS) has added the skin color of Japanese women as R15

5), but since this

addition is not internationally recognized, it is not taken up in this paper.

The general CRI value (CIE Ra) is derived as the arithme-tic mean of the eight standard CRI values (R1-R8). Standard organizations such as JIS6) and sports organizations7) 8) have specified recommended Ra values in broadcasting. These values have come to be used in HDTV production.

Although Ra is widely used internationally for evaluating illuminants, it is reported that highly saturated colors can-not be properly evaluated in terms of Ra under white LED lighting9) 10) since there are no high-saturation colors includ-ed in test-color samples R1-R8. To overcome the defect of Ra and to evaluate white LED lighting properly, numerous new methods for evaluating color rendition have been pro-posed as a replacement for Ra

10)-13), but none have yet been standardized. Therefore, we conducted a subjective evalua-tion to derive appropriate color-rendering indices and their recommended values for white LED lighting in UHDTV production. In this study, we evaluated the internationally recognized Ra and special color-rendering indices R9-R14 in consideration of the continuity with the conventional Ra. Furthermore, while various types of white LED lighting ex-ist, we focus on the white LED lighting that is based on a combination of a blue LED and phosphors and is expected to be widely used for television studios and sports facilities.

2. Subjective evaluation to select appropriate col-or-rendering indices and determine recommended values for UHDTV production

2.1 Method

(1) ParticipantsThirty-four nonexpert participants (18 females and 16

males; age range = 20-51 years; mean age = 36.1 years) with normal vision (in compliance with Recommendation ITU-R BT.500)14) participated in the subjective evaluation experiment.

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Appropriate Color-rendering Indices and Their Recommended Values for White LED Lighting in UHDTV Program ProductionTetsuya Hayashida

FEATURE

(2) ApparatusTo create different lighting conditions, we used a special

lighting booth consisting of LEDs with 24 different peak wavelengths. Three levels of correlated color temperature (CCT)*1 were employed: 3,000 K (studio lighting), 5,600 K (stadium lighting), and 6,500 K (reference white light of a television system). For each CCT, we configured five light-ing conditions, including four simulated white LED lighting conditions and one reference lighting condition, with dif-ferent CRI values. Four simulated white LED lights were selected considering their popularity and commercial avail-ability. The spectral power distributions of these 15 lighting conditions are shown in Fig. 1.

To shoot the materials, we used a prototype UHDTV cam-era3) 15) developed at NHK STRL. A linear matrix optimized under simulated daylight at a CCT of 5,600 K was used. The white balance of the camera was adjusted for each lighting condition using a color chart. The opto-electronic transfer function (OETF) defined by Rec. 709 was applied for gam-ma correction in the camera. For this subjective evaluation, we used a 50-inch 4K laser-backlight LCD covering 98% of the Rec. 2020 color gamut16).

(3) MaterialsTwo groups of objects -“Sports” and “Flowers”- were

prepared. Examples of evaluation images of these two groups and their respective chromaticity distributions are shown in Fig. 2. The “Sports” group represented outdoor sports scenes and included uniforms, an artificial lawn, ath-letic tracks, national flags, and a soccer ball. The “Flowers” group comprised a wide range of colors and included floral arrangements, fruits, toy blocks, wine glasses, and bottles. Each of these groups also included color charts that were used for adjusting the white balance. The color charts in-cluded in the “Sports” group were evaluated separately as an object group called “Charts”.

(4) ProcedureThe subjective evaluation experiment was conducted in

dim surroundings. The display brightness was adjusted so that the white patch on the ColorChecker Classic chart in the image was 150 cd/m2 when taking the patch to have a video level of 100%. The luminance of the wall behind the monitor was set to a value in the range of 2-10 cd/m2. This setup was used to ensure that the ratio of the peak luminance of the screen image to that of the monitor background re-mained within a range of approximately 1-5%. The view-ing distance was set to 1,900 mm, which is three times the screen height.

In the subjective evaluation, the reference image was

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Wavelength (nm) Wavelength (nm) Wavelength (nm)

i: Efficacy-oriented LED ii: High-saturation color rendering LED

iii: High Ra value and low R9 value LED

v: Reference lighting

iv: High-fidelity color rendering LED

Figure 1: Spectral power distributions for 15 lighting conditions

*1 The color temperature of blackbody radiation that appears to have a color nearest that of the target light source. The unit of CCT is degrees Kelvin (K), the thermodynamic temperature.

FEATURE

captured under simulated daylight conditions and four com-parative images were captured under the four white-LED-lighting conditions having different CRI values for each CCT. The reference image and one of the four comparative images captured under the same CCT lighting conditions

were displayed side by side, divided by a gray border. The participant was able to move the gray border horizontally using a dial (Fig. 3). The participants evaluated each com-parative image using the degradation category rating (DCR) method with a five-stage degradation scale, as shown in Table 1. In this method, a score of 3.5 is considered to be the acceptability limit, and this value was used to derive the recommended values described in the next section17) 18). Since the four comparative images were evaluated for each of the three groups (i.e., “Sports”, “Flowers”, and “Charts”) at three CCTs (3,000, 5,600, and 6,500 K), a total of 36

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“Sports” group: (b) chromaticity distributionx

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Figure 2: Example of evaluation images and their chromaticity distributions.

“Sports” group: (a) Evaluation image

“Flower” group: (c) Evaluation image “Flower” group: (d) chromaticity distribution

Figure 3: Photograph of subjective evaluation.A participant evaluates a reference image (left side) and a comparative image (right side) displayed side by side by controlling the gray border.

Score

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Evaluation Word

Imperceptible

Perceptible, but not annoying

Perceptible and slightly annoying

Perceptible and annoying

Perceptible and very annoying

Table 1: Five-stage degradation scale of DCR method

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trials per participant were performed. The order of present-ing images to a participant was randomized to eliminate any order effect.

2.2 Results and discussion

Figure 4 shows the degradation mean opinion scores (DMOSs) obtained by the DCR method with radar charts for each CCT. For all CCTs and object groups, it can be seen that DMOSs exceed the 3.5 acceptability limit for (iv) high-fidelity color-rendering LED and (ii) high-saturation LED lighting conditions. Figures 5 and 6 show the distri-butions of the correlation of DMOS with Ra and R9-R14, respectively, for each lighting condition. The correlation coefficient*2 r is shown on the upper left side of each graph. These results show that the correlation between DMOS and R9 is the highest.

This experiment confirmed that R9 correlates most strongly with the DMOS and that choosing R9 as an addi-tional index is valid. Considering the compatibility with the existing index of Ra, it is practically appropriate to use the combination of Ra and R9. Although it is not a perfect solu-

tion, it seems to be reasonable to use R9 to complement Ra until a new more appropriate index is standardized to pre-vent further mismatch with the conventional Ra. Therefore, we derived the recommended value for the combination of Ra and R9 by applying the DMOS acceptability limit of 3.5. To obtain the recommended value of each index, we plotted the distributions of each index value and the DMOSs with 95% confidence intervals*3, as shown in Fig. 7. In this fig-

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Figure 5: Distribution of correlation between DMOS and general CRI value of Ra.

The markers denote the four white LED lighting conditions, three CCTs, and three objects shown in Fig. 4.

Ra

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*2 An index indicating the strength of the linear relationship between two variables. The correlation coefficient is a dimen-sionless quantity with a value between -1 and 1. Values closer to 1 indicate a stronger relationship between the variables.

(a) CCT=3,000K (b) CCT=5,600K (c) CCT=6,500K

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i: Efficacy-oriented LED ii: High-saturation color rendering LED

iii: High Ra value and low R9 value LED iv: High-fidelity color rendering LED

Figure 4: Radar charts showing DMOS for the color differences in UHDTV imagery obtained in subjective evaluation for each CCT of (a) 3,000 K, (b) 5,600 K, and (c) 6,500 K. Marker shapes denote the three objects. Marker sizes denote the three CCTs.

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ure, the lighting conditions satisfying the acceptability limit including their 95% confidence intervals are indicated by red lines. It is sufficient to decide the recommended value so that only the lighting conditions indicated by one of the red lines are classified. For the combination of Ra and R9, Ra ≥ 90 and R9 ≥ 80 are considered appropriate. Although there

is a distribution that does not satisfy the acceptability limit with the condition of Ra ≥ 90 alone, adding the condition of R9 ≥ 80 causes the acceptability limit to be satisfied. This condition is consistent with the conventional practice of de-termining the recommended CRI values in 10 increments18).

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R 12 R 13 R 14

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Figure 6: Distributions of correlation between DMOS and special color-rendering indices R9-R14.The markers denote the four white LED lighting conditions, three CCTs, and three objects shown in Fig. 4.

Figure 7: Distributions of correlation of DMOS with general CRI value of Ra and special color-rendering index R9.The markers denote the four white LED lighting conditions, three CCTs, and three objects shown in Fig. 4.

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*3 A range of values within which the mean value of data tar-geted by statistical analysis has a 95% probability of being included.

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3. ConclusionsIn this study, we conducted a subjective evaluation to

derive the appropriate color-rendering indices and their recommended values required for white LED lighting in UHDTV program production. From the correlation analysis between the DMOS and the general CRI value of Ra and special color-rendering indices R9-R14 for each lighting type, the highest correlation was achieved by R9. Taking these analysis results and continuity with Ra into account, the combination of Ra and R9 was found to be practically appropriate and recommended values of Ra ≥ 90 and R9 ≥ 80 were obtained.

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