Visual Scaling of Image Quality for CRT displays. Tsuneo Kusunoki. Sony Corp., Kanagawa, Japan. Roy S. Berns. Munsell Color Science Laboratory, Rochester ...
Visual Scaling of Image Quality for CRT displays Tsuneo Kusunoki Sony Corp., Kanagawa, Japan
Roy S. Berns Munsell Color Science Laboratory, Rochester Institute of Technology Rochester, New York, USA
Abstract Two computer-controlled monitors with different peak luminances and faceplate reflectances, but with identical calculated contrast, were evaluated visually to determine which had higher perceived contrast and which was preferred. The results of the visual experiment indicated that photometric-based contrast measurements did not predict perceived contrast whereas monitor peak luminance was more closely correlated. Also, there was no significant difference in visual preference between the two monitors. Objective and Background Computer-controlled CRT (cathode ray tube) displays play a major role in multimedia systems as a manmachine interface. Clearly, it is worthwhile to look for opportunities to improve their image quality. Contrast, which is the difference between light and dark areas in an image, is one of the important characteristics in determining image quality, particularly when monitors are used in ambient illuminated environments. Accordingly many techniques have been developed to improve contrast, including low transmittance faceplate glass, anti-reflective surface coatings [1, 2], pigmented phosphors [3], and color filters [4]. There are a number of definitions for contrast; see for example references [2 - 6]. Equation 1 is often used:
C = ( B + R × L / π ) /( R × L / π ) = B /( R × L / π ) + 1
Eq. 1
where C is contrast, B is the peak luminance of a CRT display (cd/m2), R is the reflectance of a CRT’s surface, and L is the illuminance of ambient light (lx). Thus contrast depends on three parameters: peak luminance, the reflection properties of the faceplate, and ambient illumination. In practice, the display’s set up and graphics display controller also have an effect by altering the black level. If the black level is well above the cut-off voltage, contrast will be
reduced. However, it is reasonable to assume when performing contrast calculations that the black level is set at or below the display’s cut-off voltage. Greater C means that the CRT display has higher contrast. According to this equation, however, there are many combinations of B and R that achieve the same contrast for a fixed ambient illumination. Furthermore, from psychophysics, it is well known that the relationship between the physical parameters and perception is nonlinear, often governed by logarithmic or power function relationships, such as Fechner’s Law [7]. Thus, it is likely that contrast, obtained by Eq. 1, may not correlate well with visual observations. In this research this point was addressed, and two combinations of B and R leading to the same contrast, C, were evaluated to determine which had greater perceived contrast and which was preferred based on a psychophysical experiment. One combination required that the monitor had higher luminance and higher surface reflectance, referred to as “monitor A.” The other combination required that the monitor had lower luminance and lower surface reflectance, referred to as “monitor B.” Monitors and Viewing Environment The two monitors were set up side by side in a room illuminated by three-band fluorescent lamps. Table 1 shows luminance, defuse reflectance of the faceplate, ambient illuminance at the plane of the CRT faceplate, and calculated contrast. Under these conditions the values of contrast of the two monitors were nearly the same. In order to minimize the difference of the Monitor A Monitor B Luminance, B (cd/m2) 104 71 Reflectance, R (%) 9.65 6.27 Illuminance, L (lux) 152 158 Contrast C 23.3 23.5 Table 1. Setting of the monitors color balance between the two monitors, each
monitor was colorimetrically characterized using the method described Berns, et al. [8, 9]. The characterizations were used to redefine images for monitor A such that the colorimetry was matched to monitor B. For example Figure 1 shows the relationships between the digital input and relative luminance for the green channel both before and after the calibration. 1
0 .8
Gre e n o ut put
Moni to r A 0 .6
Moni to r B
0 .4
0 .2
0 0
50
1 00
1 50
200
2 50
300
digital input
(a) Green output before calibration
monitors, respectively, and were asked to answer the following questions: “Which of the two computers has the greater difference between light and dark areas?” “Which image do you prefer for a computercontrolled monitor?” In the first question the expression “difference between light and dark areas” was used instead of the word “contrast” in order to avoid ambiguity caused by different definitions of contrast (e.g. dynamic range vs. gamma). Before the visual experiment observers were trained to understand the meaning of the difference between light and dark areas by displaying sample image with very different ranges between black and white image areas. Thirty color-normal observers participated in the experiments. Using Thurstone’s law of comparative judgment [10], the binary decisions were converted to an interval scale. Figure 2 shows average interval scale results of the visual experiment for contrast and preference. A 95% confidence interval was calculated as
1
Z±
0 .8
Gre e n o ut put
Moni to r A
Eq.2
1
Moni to r B
0 .6
1.38 units N
0 .4
0 .2
0 0 0
50
1 00
1 50
200
2 50
Monitor A
300
Monitor B
digital input
(b) Green output after calibration Figure 1. Relationship between digital input and relative luminous output for green before (a) and after (b) the calibration. This result means that the tone reproduction was matched for the two displays. The performance of the calibration throughout the color gamut was checked by 27 sets of digital input ( a 3×3×3 RGB sampling). The data were converted to CIELAB and CIELUV color differences. The average ∆E* ab was 5.5 and ∆E*uv was 1.7.
-1 (a) Contrast 1
0 Monitor A
Monitor B
Visual experiment In the visual experiment eight pictorial and two computer graphic images were used. Observers compared an image displayed on each of the two
-1 (b) Preference Figure 2. Average interval scale results of the visual experiment for contrast (a) and preference (b).
P i ctri al # 1 1.5
Pi ctr i al # 2 1. 5
Pi ct ri al # 3 1 .5
1
1
1
0.5
0. 5
0 .5
0 - 0.5
0
Monit or A
Monit or B
- 0. 5
0
Moni to r A
Monit or B
- 1
-1 - 1.5
P i ctri al # 4
Pi ctr i al # 5 1. 5
Pi ct ri al # 6 1 .5
1
1
0.5
0. 5
0 .5
0
0
Monit or A
Monit or B - 0. 5
-1
0
Moni to r A
Monit or B
- 1
- 1.5
-0 .5
Pi ctr i al # 8
CG i mage # 1
1. 5
1
1
1
0.5
0. 5
0 .5
1 .5
0
0
Monit or A
Monit or B
-1
- 0. 5 - 1
- 1.5
- 1. 5
Moni t or B
-1 .5
1.5
- 0.5
Moni t or A
-1
- 1. 5
P i ctri al # 7
Moni t or B
-1 .5
1
- 0.5
Moni t or A
-1
- 1. 5
1.5
-0 .5
0
Moni to r A
Monit or B
-0 .5
Moni t or A
Moni t or B
-1 -1 .5
CG i mage # 2 1.5 1 0.5 0 - 0.5
Monit or A
Monit or B
-1 - 1.5
Figure 3. Interval scale results of the two monitors for each image. The interval scale value of each image for preference is shown with an 95% confidence interval. where Z is a Z-score and N is the number of contrast since monitor A had significantly greater observations. Since the number of observations contrast than monitor B in nine of the ten images. totalled 300 in this experiment, the confidence However preference depended on the images interval around each scale value was 0.080. If the (Figure 3). In order to know what caused the interval scale values were within 0.080 of each other, dependence of preference on the images the authors there was not a significant difference between the assumed that the observers might choose monitor B monitors A and B. It is seen in Figure 2 (a) that when the image contained more dark areas than light monitor A had the greater difference between the light areas and monitor A when the image contained more and dark areas than monitor B even though these light areas than dark areas. Lightness of a pixel in monitors were photometrically adjusted to the same each image was calculated and classified into three calculated contrast (Eq.1). It means that peak ranges: L*=0-5, 6-70, and 71-100. In Figure 3 the luminance was dominant over faceplate reflectance in images of CG image #1 and CG image #2 had almost governing observers’ perceived contrast. Figure 2 (b) the same distribution; however, the monitor B was preferred for CG image #1 and the monitor A was shows that there was no significant difference in preference between monitor A and monitor B. preferred for CG image #2. The assumption based on Furthermore there was no image dependence on lightness distribution was not in agreement with the dependence of preference on the images.
10 0% 9 0% 8 0% 7 0% 6 0%
L* =71 ~100 L* =6~ 70
5 0%
L* =0~ 5
4 0% 3 0% 2 0% 1 0%
CG im age#2
CG image#1
Pi ctri al#8
Pi ctri al#7
Pic t ria l #6
Pi ctri al#5
Pic t ria l #4
Pi ctri al#3
Pic t ria l #2
Pi ctri al#1
0%
Figure 4. Lightness histogram of the images Conclusions The commonly used definition of contrast was evaluated by performing a visual experiment. Perceived contrast was highly correlated with peak luminance but not with the usual industry-accepted definiton. Based on these results, this definition (Eq. 1) is a poor quality criterion when used to make engineering decisions such as the trade offs between peak luminance and faceplate reflectance properties. Alternate metrics should be sought. Finally, correlation between perceived contrast and visual preference was not observed. Acknowledgment The authors are grateful to Dr. Mark D. Fairchild, Mr. Koichi Iino and the staff at the Munsell Color Science Laboratory for their helpful suggestions. The time and patience of the observers exhibited during the visual experiment are also greatly appreciated. Reference [1] H. Tohda,et al., Anti-Glare, Anti-Reflection and Anti-Static(AGRAS) Coating for CRTs, JAPAN DISPLAY ‘92, 289-292(1992) [2] M. Onodera, H. Matsuda, H. Mori, and T. Ito, A Color Display Tube with a High-Contrast and Anti-Reflection Coating, SID 94 DIGEST, 823826(1994) [3] M. Wakatsuki, T. Takahara and T. Nishimura; ITEJ Technical Report, ED 492 IPD 50-1.1
[4] K. Ohno, T. Kusunoki, K. Ozawa, O. Dobashi, and K. Takayanagi, The effect of ultra fine pigment color filters on CRT brightness, contrast and color purity, EURO DISPLAY ‘93, 31(1993) [5] T. Kawamura, H. Kawamura, K. Kobara, A. Saitoh, and Y. Endo, Antireflection Coating for Inner Surface of CRT Faceplate, SID 91 DIGEST 49-52 (1991) [6] G. C. de Vries, Contrast-Enhancement Under Low Ambient Illumination, SID 95 DIGEST 32-35 (1995) [7] Fechner, G. T. Element der Psychophysik, Leipzig: Breitkopf & Harterl, 1860. [8] R. S. Berns, R. J. Motta, and M. E. Gorzynski, CRT Colorimetry. Part I: Theory and Practice, Color Res. Appl., Vol. 18, 299-314, (1993) [9] R. S. Berns, M. E. Gorzynski, and R. J. Motta, CRT Colorimetry. Part II: Metrology, Color Res. Appl., Vol. 18, 315-325, (1993) [10] L. L. Thurstone, A low of comparative judgment, Psych. Rev. 34, 273-286 (1927)
