In the experiment, the CR was measured by using a luminance analyzer, CA210 [11], with a measuring area of 27mm in diameter (covering 12,834 pixels approximately).
The CA210 uses an optical system for measuring luminance and chromaticity of LCD panels. The main components of the optical system are the objective lens, optical fiber block, on-chip lenses, and sensor, as shown in Fig. 4-2. The light form the light source is focused on the receiving window of the optical fiber block. The focused light is mixed inside the optical fiber block and split into three parts, which are then guided to the receiving areas of the x, y, z sensors. Here, the light is further focused by the on-chip lenses onto the sensors themselves.
Fig. 4-2 Optical system of CA210
Two color backlight control algorithms were applied on a 37” HDR-LCD TV supported by AU Optronics (AUO) Corporation. This panel is 1920×1080 (HDTV) resolution with 8×8 backlight zones. Each backlight zone can locally dim three primary LEDs (R, G, and B) independently, as shown in Fig. 4-3.
Backlight and liquid crystal signals were controlled by the FPGA control systems of the 37” HDR-LCD panel. The backlight signal was controlled by using I2C-Bus which is internal bus that provides the communication between integrated circuits in a system to control FPGA [12]. Besides, liquid crystal signal was delivered by Digital Visual Interface (DVI), as shown in Fig. 4-4.
Fig. 4-4 Control systems of the 37” HDR-LCD TV
The maximum color gamut of the HDR-LCD TV could be enlarged from 107.7% to 125.4% NTSC by using color BL control, as shown in Fig. 4-5. Besides, the power consumption of the HDR-LCD TV could be reduced by using color control. In the experimental panel, three primary LEDs (R, G, and B) consumed different power consumption, as shown in Fig. 4-6. Therefore, red LEDs could save three watts, green LEDs could save five watts, and blue LEDs could save four watts by reducing per 16 gray levels.
Fig. 4-6 The power consumption of the 37” HDR-LCD TV
4.2 Static Testing Images
(a) In order to adjust the image qualities by using various backlight algorithms, three indices,
“image details”, “power consumption”, and “contrast ratio” were been utilized. Therefore, four different static images, Lily, Robot, Sun, and Strawberry were chosen as experimental
target images, as shown in Fig. 3-4. Referring to
Fig. 4-7 (b) and Fig. 4-8(b), the target images, Lily and Robot, were the high contrast ratio images. Next, the target image, strawberry, has more red content, as shown in Fig. 4-9.
Finally, the target image, sun, which has high image details could be magnified to compare image details, as shown in Fig. 4-10.
(b) (b)
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Fig. 4-8 (a) The high CR image and (b) the histogram of the target image- Robot
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Fig. 4-9 (a) The colorful image- Strawberry, (b) the histogram of red, (c) green, and (d) blue component.
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Fig. 4-10 (a) The red rectangle of high detail image are magnified and (b) the histogram of the high detail image- Sun.
4.3 Image Details
The high detail image, Sun, was locally magnified and shown in Fig. 4-11. The image details in the high brightness region were almost preserved by using Max, IMF, IMF+DCA (M=16, N=6), and SCC (A=1, R=2, M=5). Therefore, the two color backlight control methods, the Delta-Color Adjustment method and the Segment Color Control method, could keep the image details.
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(b) (c) (d)
There is no suitable index to describe image details in HDR systems. Therefore, human evaluation score was proposed to evaluate image details by phychophysical experiments of seven observers (score= 0~10, and 10 is the best) with four different images, Lily, Robot, Strawberry, and Sun, and the results are shown in Table 4-1and Fig. 4-12. The root method
had the lowest human score (score= 3) with the four test images. Besides, human score of three methods was the same (score= 10) that represents imperceptive image distortion.
Table 4-1 Human score of Lily, Robot, Strawberry, and Sun by using six different backlight algorithms.
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4.4 Power Consumption
Color backlight algorithm can also result in lower power consumption. The power consumption by different backlight algorithms is compared and results are listed in Table 4-2 and shown in Fig. 4-13. The two color backlight algorithms can save much power relative to conventional full-on backlight and gray backlight.
Table 4-2 Power consumption of Lily, Robot, Strawberry, and Sun by using six different backlight algorithms. (Unit: watt)
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4.5 Contrast Ratio
HDR system can also yield a high contrast ratio (CR) image to satisfy human vision system in the real world with high dynamic range. The positions of maximum luminance and minimum luminance were shown in Fig. 3-4. Consequently, CR of the images was measured by using a luminance analyzer, CA210 [11], as shown in Table 4-3.
Table 4-3 Contrast ratio of Lily, Robot, Strawberry, and Sun by using six different backlight algorithms.
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Fig. 4-14 Contrast ratio of (a) Lily, (b) Robot, (c) Strawberry, and (d) Sun by using six different backlight algorithms.
Compared CR values of these methods, although root method has high CR, but the human score is too low. Besides, IMF method has high CR, but the power consumption is higher. For DCA and SCC, CR of the image, Lily, could be increased to ~40,000:1, meanwhile the conventional LCD with full-on backlight can only achieve the CR of 1,352.
4.6 Summary
The indices, image details, power consumption, and contrast ratio, were used to evaluate the image quality by checking the difference between target image and the HDR image obtained by using different backlight algorithms with compensated LC signals. Four test images, Lily, Robot, Strawberry, and Sun, with different histogram distributions were chosen for the experiments.
According to those evaluation parameters, two color backlight control algorithms, DCA and SCC, for high dynamic range (HDR) displays were demonstrated for yielding higher performance. From the experimental results, IMF+DCA and SCC in the high CR images not only achieve high contrast ratio (~40,000:1) but also preserve clearer image details.
Furthermore, the power consumption could be much lower than full-on backlight. Therefore, the backlight signal can be optimized by the properties of each image by using color backlight algorithms. Consequently, the two color backlight algorithms were successfully applied on a commercial 37” HDR-LCD TV and demonstrated for achieving high image quality and lower power consumption.