Chapter 4 Experimental Results
4.3 Discussions
The verifications of colorimetric reproduction were based on an LCD with locally controlled backlight module of 8 by 8 divisions. As the experimental results showed, the color differences were increased along with complex image contents. The CIEDE2000 values in images with high spatial frequency were larger than three, which were unacceptable values of colorimetric reproduction accuracy since the limitation of presented backlight divisions. Therefore, the essential backlight parameters, number of divisions and light spread function (LSF) size, must be optimized to improve accuracy of colorimetric reproduction on images with complex contents.
Color arrangements in two-color-field method play an important role. The CBU examination results demonstrated that the minimum RCS value appeared when the main color components of test images separated into two field images. However, the accuracy of colorimetric reproduction was based on dividing the least component into two field images because of less reproduction errors. Therefore, the color arrangement of CBU suppression and colorimetric reproduction was tradeoff.
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Chapter 5
Optimizations of Two-color-field Method
To improve accuracy of colorimetric reproduction in images with complex content, the backlight parameters, number of segments and light spread function (LSF) size, must be optimized. Moreover, color difference maps were used to describe the accuracy of colorimetric reproductions. Finally, results and discussions will be presented.
5.1 Backlight parameters
The two main backlight parameter factors affected color reproduction accuracy were the number of backlight divisions and light spread function size. Considering implementation complexity and thermal effect, the backlight parameters optimizations were essential. The two-dimensional Gaussian profile was simulated as the LSF in optimal process, where σ size was used to adjust the LSF width, as shown in Fig.
5-1. The optimal process and results are detailed below.
σ
Fig. 5-1 Gaussian profile
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5.1.1 Backlight Divisions
There were five test color patch images with different image content were chosen as test images as shown in Fig. 5-2. An LSF, formulated by a two-dimensional Gaussian profile with horizontal and vertical standard deviations σx = 60 pixels and σy
= 60 pixels, was applied to initiate the optimization. The Gaussian profile was adopted for simplicity; σx and σy were selected because of the largest backlight segment size.
The results, as shown in Fig. 5-3, show that color differences of the five test images are decreased along with increasing amount of backlight divisions. The reason is that more independent backlight segments provide higher resolution of output backlight distribution, which is more adequate to be compensated by the LC module. Under current LSF setup, backlight division 80*45 is the optimized value since color difference only varies slightly exceeding this value.
1-patch 4-patches 12-patches 48-patches 144-patches
Fig. 5-2 Five test images with different image contents
5.1.2 Light Spread Function Size
Color reproduction accuracy dependence on LSF size was performed under 80*45 backlight segments. Similarly, color difference reduces when the LSF size shrinks, as shown in Fig. 5-4. LSF must be concentrated to adapt to increased spatial frequency of images. With σx*σy = 31*31 pixels, the color difference is lowered to an average of ΔE00ave< 3, which is generally regarded as an acceptable color difference.
45
0 2 4 6 8 10 12 14 16
16*9 32*18 48*27 64*36 80*45 96*54
Δ E
00(ave.)
B/L divisions
16*9 8*6 4*3
2*2 1
Fig. 5-3 The correlation between number of backlight divisions and color differences.
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
34 31 27 23 20 17
Δ E
00(ave.)
LSF size (σ pixels)
16*9 8*6 4*3
2*2 1
Fig. 5-4 The optimal results with the σ size of Gaussian profile against color difference.
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5.2 Results
The backlight parameter optimizations were accomplished in prior sections. The reproduction images with optimal results are presented below. Moreover, color difference maps evaluated colorimetric reproduction accuracy. Finally, demonstration results will be given.
5.2.1 Color Difference Maps
Color difference maps were used to evaluate the accuracy of colorimetric reproductions, where S-CIEDE2000 was the evaluation index. The four test images, (a) Lily, (b) Butterfly, (c) Parrot, and (d) Color-ball with different detail and color complexities are shown in Fig. 5-5. The optimal results, which were simulated by using Matlab, are illustrated in Fig. 5-6. Comparing the target image with the optimal Lily test reproduction image (Fig. 5-6 (a)), the human eye can hardly differentiate between the two images. Moreover, the average S-CIEDE2000 value in the Lily image is 0.07, which is an acceptable color difference value. The reproduction result in the Butterfly image is shown in Fig. 5-6 (b), the color difference map shows the maximum S-CIEDE2000 value is lower than 4, and the standard deviation value is 0.14, that indicate the acceptable colorimetric reproduction. Similarly, the results of Parrot and Color-ball images are illustrated in Figs. 5-6 (c) and (d). The average S-CIEDE2000 values were all of less than 1, which means the human eye could not distinguish difference between the target image and the reproduction image.
(a) (b) (c) (d)
Fig. 5-5 Four test images: (a) Lily, (b) Butterfly, (c) Parrot, and (d) Color-ball images.
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2-field image Target image
Difference image
S-ΔE00
min max ave std 0 2.71 0.07 0.10
(a) Lily image
2-field image Target image
Difference image
S-ΔE00
min max ave std 0 3.19 0.10 0.14
(b) Butterfly image
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2-field image Target image
Difference image
S-ΔE00
min max ave std 0 3.93 0.23 0.28
(c) Parrot image
2-field image Target image
Difference image
S-ΔE00
min max ave std 0 4.91 0.16 0.15
(d) Color-ball image
Fig. 5-6 The reproduction results of (a) Lily, (b) Butterfly, (c) Parrot, and (d) Color-ball images.
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5.2.2 Demonstration Results
A digital light processing (DLP) LCD was used to simulate a FSC-LCD using the two-color-field method. The two-color-field method could be verified using the experimental demonstration. The simulated field images with optimal parameters, 80*45 backlight divisions, and σx*σy = 31*31 pixels of LSF, were displayed sequentially at 120Hz field rate on the DLP LCD. The resulting images are illustrated in Fig. 5-7. The simulated backlight images of the first field (Fig. 5-7 (a)) and the second field (Fig. 5-7 (b)), and LC images in the first field (Fig. 5-7 (c)) and the second field (Fig. 5-7 (d)) were captured by using a Canon D60 digital camera. Then, displayed two field images ( Figs.5-7 (e) and (f)) with 120Hz field rate, and the vivid color image was generated by using temporal color mixing, as shown in Fig. 5-8 (b).
Comparing the target image (Fig. 5-8 (a)) with reproduction image (Fig. 5-8 (b)) using the two-field-color method, the results demonstrated accurate colorimetric reproduction. Therefore, the two-color-field method was successfully verified by the experiment.
Furthermore, CBU demonstrated results are detailed. CBU visibility was compared between two images formed by the conventional three-field (RGB) and the proposed two-color-field sequential methods. A high-speed camera moved horizontally to simulate eye movement (Fig. 5-9 (a)) in capturing CBU images, shown in Fig. 5-9 (b) and (c). For example, the color band edges of the white ball induced by the primary colors (red, green and blue), are shown in Fig. 5-9 (b), incurring higher sensitivity than the mixed colors (red with partial blue and green with remaining partial blue), as shown in Fig. 5-9 (c). The result displayed an innate advantage of the two-field driving scheme in reducing CBU visibility.
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(a) (b)
(c) (d)
(e) (f)
Fig. 5-7 The demonstrated results of (a) 1st B/L image, (b) 2nd B/L image, (c) 1st LC image, (d) 2nd LC image, (e) 1st field image, and (f) 2nd field image.
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Fig. 5-8 Comparison of (a) target and (b) reproduced image
46” 120Hz MVA LCD
X-Y move table Camera
(a)
(b) (c)
Fig. 5-9 Target image was input to a 46” 120Hz MVA LCD (a), the corresponding CBU images, synthesized by three-field (b) and two-field (c), were captured by a high-speed camera moving horizontally.
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5.3 Discussions
By optimization works presented in this chapter, optimal hardware parameters using the two-color-field method were collected. The number of back divisions 80*45, and light spread function size with σ= 31*31 pixels were used to obtain an accurate colorimetric reproduction using the two-color-field method. Comparing the optimal results with the experimental results of the four test images, color differences were reduced to an average of 30% in the optimal process, as shown in Fig. 5-10. Therefore, the optimal two-color-field method successfully reduced color difference in complex images.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
L B P CB
8x8 80x45
29%
35%
29%
24%
S-ΔE00( ave.)
Lily Butterfly Parrot ColorBall
Fig. 5-10 Comparisons of optimal results and experimental results.
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As the experimental results show, the two-color-field method reduced CBU visibility. The reason was that our method’s color arrangement reduced opponent colors in each field. When the image and human eye had relative motion, the color band edges at the image fringes can get slight color difference sensitivity for human eye, as shown in Fig. 5-11. Thus, based on the concept, two-color-field method can suppress both static and dynamic CBU phenomenon.
1
st2
ndR G
B
Y
Fig. 5-11 The slight CBU sensitivity yielded by reducing opponent colors in each field.
The color-mixing band edge of two-color-field image incurred less color different sensitivity.
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However, the colorimetric reproductions of some specific test images do not have good performance. For example, the Blue Hill test image shown in Fig. 5-12.
The average color difference value is 2.08, but the maximum value is larger than 4.
The percentage of unacceptable values which means the values larger than 3 is 25%.
Comparing the target image with reproduced image as shown in Fig. 5-12. (a) and (b), the difference between these two images can distinguish by observer’s eye. Therefore, the third primary option may have another choice since the less colorimetric reproduction error is generated.
S-CIEDE2000
min max std ave >3
0 4.9483 0.1247 2.0844 25.8%
(a) (b) (c)
Fig. 5-12 (a)Target image (b)reproduced image (c) reproduced image S-CIEDE2000 values
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5.4 Comparisons
A comparison between the proposed method and other methods are shown in Table. 4. The two-color-field sequential method has some advantages such as color filter free (0), higher luminance and resolution (both 300%), lower field rate (120Hz), and less field number (2). Moreover, the experiment demonstrated the two-color-field sequential method which could also suppressed CBU effectively. However, the NCTU two-field method needs combined the locally controlled backlight system to display the color-mixing field images, which may increase the system complexity.
Table. 4 Comparison between NCTU two-color-field method and other FSC methods
Conventional RGB-field Philips two-field NCTU two-field
Luminance 100% 300% 150% 300%
Resolution 100% 300% 150% 300%
Color
breakup None High Medium Medium
Color filters 3 0 2 0
Color fields 1 3 2 2
Refresh rate 60Hz 180Hz 120Hz 120Hz
Light sources 1x CCFL 3x LED 3x LED 3x LED BL system Global Global Global Local control
5.5 Summary
Optimizations of the two-color-field method were done in this chapter. The colorimetric reproduction with optimal backlight parameters was acceptable with an average CIEDE2000 lower than 3 and average S-CIEDE2000 lower than 1. Moreover, the demonstrated result presented the two-color-field method could effectively reduce the CBU visibility. The third primary options can further to have another choice in the future work.
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Chapter 6
Conclusions and Future Works
6.1 Conclusions
FSC-LCDs do not need color filters and flash red, green, and blue images time sequentially to generate full color image by temporal color mixing. Therefore, FSC-LCDs have some advantages, such as high optical throughput and low material cost. However, the FSC methods are only with limited success because of the slow LC response time.
In order to overcome this issue, we proposed the two-color-field sequential method. The two-color-field sequential method for LCDs without color filter was proposed to further reduce field rate, so many commercial LC modes, such as MVA, TN, or IPS modes could be utilized. The results demonstrated that the average color difference, ΔE00ave, of the reproduced image was lower than 3 and average S-CIEDE2000 value, S-ΔE00ave was lower than 1. Moreover, the experimental results illustrated the proposed method also can suppress CBU visibility. Therefore, two-color-field sequential method is very promising for low power consumption large size LCD applications.
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6.2 Future works
The two-color-field sequential method was proposed to reduce the field number thus allowing sufficient time for LC response. The results demonstrated that the colorimetric reproductions were acceptable for human visual system. However, some specific cases showed that the colorimetric reproductions accuracy should be improved, as mentioned in section 5.3.
The algorithm of the proposed sequential method remains to be improved. For example, the third primary can be chosen based on the least significant image content, since less reproduction error is generated. Fig. 6-1 shows the simulation results of two-color-field method and improved algorithm. The third primary of reproduced image (Fig. 6-1(b)) was chosen based on the least image content, red. Compared the reproduction images with blue based (Fig. 6-1 (a)) and less component based (Fig. 6-1 (b)), the color difference percentage larger than 3 was reduced from 26% to 0%.
Moreover, the maximum color difference value was lower than 3 which is an acceptable color difference value for human visual system.
However, if there was a test image whose main image content had least color component, the optimal algorithm will sacrifice color information accuracy. Therefore, the analyses of content significance can further be localized in the future, which may result in different third primary at different areas. Finally, the option of third primary should be an important factor which can affect the colorimetric reproduction accuracy.
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S-CIEDE2000
min max std ave >3
0 2.6097 0.0228 0.043 0%
S-CIEDE2000
min max std ave >3
0 4.9483 0.1247 2.0844 25.8 %
(a) (b)
Fig. 6-1 (a) Reproduced image of the third primary is blue, and (b) reproduced image of the third primary with the least color component.
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