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Abstract. In the present a study we relate the conventional temporal behavior of LCD displays generally expressed in terms of response time versus gray levels ...
26.4 / P. Boher

26.4: Relationship between LCD Response Time and MPRT Pierre Boher, David Glinel, Thierry Leroux, Thibault Bignon, and Jean Noël Curt ELDIM, 1185 rue d’Epron, 14200 Herouville St Clair, France

Abstract In the present a study we relate the conventional temporal behavior of LCD displays generally expressed in terms of response time versus gray levels to the motion artifact called moving picture response time (MPRT). The idea is to use the luminance temporal behavior of the display measured between gray levels using OptiscopeSA instrument to predict the blurred edge profile of moving bars at given scrolling velocity and frame frequency. We show first that this approach is valid since the temporal behavior of one pixel is independent of the others. Then we apply this approach on two different LCDs: one with a conventional temporal behavior and another with overdrive and underdrive.

1.

Introduction

Extension of the digital TV market put recently a lot of pressure on the temporal behavior of flat panel displays. Indeed, HDTV requires almost 60 Hz working frequency and Liquid Crystal Displays are not intrinsically very rapid devices. There are two problems that affect the response time of LCDs. One is the nematic liquid crystal’s slow response to an external field; the other is the driving method. Numerous efforts have been made recently to improve the time response performances of LCDs. Nevertheless, the response time measurement itself is not straight forward especially when inter-gray levels with low differences are explored. In addition new driving strategies like overdriving leads to complex temporal behavior for the display emission and great care must be taken not only on the measurement itself but also on the measurement analysis [1-3]. When addressing motion artifacts on flat panel displays, the first thing typically considered is motion blur. Full understanding of the human visual system with regard to motion performance evaluation is complex. The new VESA FPDM section addressing this problem introduces moving edge-blur that can be measured by various instruments like pursuit cameras [4]. This evaluation is generally tedious and expensive due to the cost of the instruments and their complexity. It results in moving picture response time behaviors versus gray levels generally measured in very strict moving configurations. Even if this type of measurement is necessary, a more simple way is to use fixed detectors and simulate moving edge blur assuming known the driving properties for the display. This approach has already been introduced by different authors [5-6]. In the present paper, our purpose is to relate standard gray to gray response time to motion artifacts using new Eldim Optiscope SA instrument. This system manages standard gray to gray response time measurements with a maximum of accuracy and is flexible in terms of optical configuration. One additional interest is that the experimental temporal behavior can be simulated using a regression approach and theoretical temporal behaviors. This approach is useful to extract accurately all the required parameters even for complex temporal behavior and offers the possibility to model the temporal behavior from any level to any level very rapidly. It is now also possible to calculated moving edge-blur to deduce moving picture response

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time or even moving of complex patterns in more realistic configurations.

2.

OPTISCOPE SA instrument

2.1

Description

A photograph of the Optiscope SA instrument is reported in figure 1. The light coming from the screen is collected by an aperture limited objective. It is separated in two parts using a beam splitter. One part of the light is focused on a color CMOS sensor to get the video image of the object. The other part is directed to a photo-multiplier tube and the signal is sampled by a fully programmable acquisition card. A photo peak filter before the PM tube allows luminance measurements after a proper calibration. The dark noise is automatically corrected using a shutter. The angular aperture measured by the PM tube is fixed at ±1° following the recommendations of the FPDM VESA standards. The imaging zone is about 3 times larger than the measurement zone on the surface of the display. All the optics, detection and electronics are integrated in the measurement head. A 4Mb buffer memory ensures fast and reliable acquisition with 14 bits sampling. Sensor setting and data transfer are realized via USB bus. The response time is then automatically computed by Windows friendly software. Low pass filter can be applied. The numerical procedure follows the FPDM VESA standards for this kind of measurement. Objective

USB connector Power connection

Figure 1: Photograph of the Optiscope SA system

2.2

Response times measurement

For LCDs, the liquid crystal is always sandwiched between two polarizers and the optical response of each cell is due to the optical transmittance variation versus time. In simplified cases, it is possible to express the liquid crystal director reorientation with time. If φ is the phase shift due to the LC cell, a reduction of electric field leads to [7] :

ϕ ( z ) = φ m exp( −

2t

τd

)

Φm is the maximum phase shift and τd is the decay time characteristic of the cell which depends on the rotational

ISSN/007-0966X/07/3802-1134-$1.00 © 2007 SID

26.4 / P. Boher

1+ (

φ 2t − 1) exp( − ) τr φ 2 ∞ 2 0

Φ0 and Φ∞ are the phase shifts before the electric field increase and after the reorientation. τr is the rising time characteristic of the cell. The time dependent normalized intensity can be calculated in each case by the following relationship:

I (t ) = sin ( 2

ϕ (t ) 2

14 12 10 8 6 4 2 0 4.74

4.75

4.76

)

One example of rising and falling shape is illustrated in the figure 2. In practice, the experimental rising or falling shapes are normalized and fitted adjusting τr or τd parameters and the time origin of the reorientation. In the case of overdriving, the same theoretical model is applied using a first rising shape characterized by τ1 with a multiplicative parameter characteristic of the overdrive value followed, after a time interval ΔT, by a decay characterized by a τ2 parameter. The same type of model is also applied to falling edges with under-driving.

4.77

4.78

Time (ms)

Falling Time

14 Number of measurements

φ

ϕ (t ) =

2 ∞

Rising Time

16 Number of measurements

viscosity of the LC and its dielectric anisotropy. In the same way, the φ dependence for an increase of electric field can be expressed as:

12 10 8 6 4 2 0 4.69

4.69

4.70

4.70

4.71

Time (ms)

Figure 3: Dispersion of response times on 60 different measurements on a computer controlled LED source. The standard deviation is ±0.009ms for the rising time and ±0.006ms for the falling time

Figure 2: Response time measurement using computer controlled LED source

3.

Global & pixel temporal behavior

3.1

Standard gray to gray measurement

For testing purpose, we have realized a standard gray to gray response time measurement on a LCD display using the OPTISCOPE SA instrument and its ±1° angular aperture optics. The working distance was about 30cm and the mean measurement spot size of about Ø 10mm. We have chosen to change the luminance level with 21 iso-luminance steps between black to white state. The advantage is that we really measured the temporal behavior versus the luminance levels which are directly related to the human eye sensation. The LCD shows a simple temporal behavior without overdriving and the response time can be measured very accurately. All the results are summarized in figure 4.

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Figure 4: Standard gray to gray response time measurement on LCD display I: the measurement is made between 21 levels with iso-luminance variations.

Figure 6: Local gray to gray response time measurement on LCD display I using 120 pixel width moving bars (8 pixels/frame). Measurement is made between the same 21 levels.

3.2

4.

MPRT simulation

4.1

Theory

Local gray to gray measurement

Then we have decided to measure the temporal behavior of the same display using gray level bars moving horizontally at a given speed. If the Optiscope SA is used with its standard optics, the measurement spot size is always quite large compared to the pixel size and the recorded temporal behavior is always and average than cannot be used easily to reconstruct the edge blur. On the contrary, if we adapt a microscope objective on the Optiscope SA with a medium magnification, the recorded temporal behavior address only about 1 pixel as shown in figure 5 and then the edge blur can be deduced easily.

If Y(x,t) is the luminance temporal dependence of pixel x from gray level 1 to gray level 2, and if we assume that the response time is lower than the time frame Tf, the light intensity profile V(x) as perceived by the eyes of a block of pixels ν pixels moving at a scroll velocity of ν pixels/frame can be calculated by [6]:

V0 ( x) =

1 Tf

ν −1

∑∫ x '=0

( x ' − x+1)T f /ν

( x ' − x )T f /ν

Y ( x' , t )dt

Figure 5: Measurement zone of the Optiscope SA using x20 microscope objective (enclosed circle). For comparison, we have made the experiment exactly with the same luminance levels as for the standard gray to gray response time but using now horizontal moving bars of on luminance level on a background of the other level. Temporal behaviors are analyzed exactly in the same way as for the standard measurement and the results are shown in figure 6 and 7. We see immediately that the results, even if there are noisier due to the lower efficiency of the optical collection, are exactly comparable to the previous ones. It shows that the temporal behavior of one pixel of the display is not dependant on its neighbors and that it is perfectly understandable to use standard temporal behavior measurements for MPRT simulations.

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Figure 7: Luminance profile and BEW of display with ideal response time If the LCD has an ideal response time the result is schematically represented in figure 7. In general it is not the case and the Blurred edge width (BEW) is bigger than 0.8 ν. If the response time is higher than the time frame Tf, we need to apply the same formula for a number of frames comparable to the response time [5]. No assumption is made on the luminance temporal dependence. In the simulation we take directly the mean profile

26.4 / P. Boher measured by OPTISCOPE SA. These values can be obtained directly in Cd/m2 and so the intensity profile can be simulated in an absolute way. Calculation are made automatically between each gray levels used during the measurement. The scroll velocity is a parameter. The time frame is supposed known. Blurred edge widths are then evaluated (generally between 10 and 90% of the luminance) both for rising and falling edges. Normalized blurred edge time (NBET=BEW/ν) can be also deduced which are quasi independent of the scrolling velocity.

4.2

Simulation for standard LCD

Normalized Luminance

On figure 8 we have two examples of luminance profiles calculated using the temporal behavior of LCD I (cf. figure 4) between level 0 to 255 and level 59 to 171. As generally observed, BEW increases when the gray levels are closer. Figure 9 shows the simulation results for all the gray levels.

Figure 10: Measured temporal behavior of overdriven LCD display II between 79 and 175 gray levels.

Scroll velocity (4 pixels/frame)

100 75

From gray level to gray level 0-255 59-171

50 25 0 0

25

50 Pixels

75

100

Figure 8: Normalized Luminance profile calculated for the LCD display I using experimental temporal behaviors of figure 4. BEW is 7.4 and 8.2 pixels for 0-255 variation and 8.9 and 10.3 pixels for 59-171 variation.

Figure 11: Simulated blurred edge profile of LCD display II between 79 and 175 gray levels using measurement of figure 10. Scroll velocity is fixed at 4 pixels/frames.

5.

Conclusions

The system comes with complete integrated software that allows to calculate easily and rapidly a complete picture of the BEW and NBET parameters for any gray level.

6.

References

[1] D. Glinel, V. Gibour, P. Boher, T. Leroux, , IDW Symposium Digest, Vol. 33. pp. 538-541, 2005.

[2] D. Glinel, P. Boher, T. Leroux, , SID-ME Mid Europe Spring Meeting, Eindhoven, 2006.

[3] D. Glinel, P. Boher, T. Leroux, , IMID Symposium digest, Daegu, Korea, August 22-25, 2006.

[4] J. Miseli, , Journal of the SID 14/11, 987, 2006. [5] K. Teunissen, Y. Zhang, X. Li, I. Heynderickx,“Mehtod for Figure 9: rising and falling BEW for LCD display I using temporal behaviors of figure 4. Scroll velocity is fixed at 4pixels/frame.

4.2

Example for overdriven LCD

We have also reported in figure 10 and 11 one example of measurement and simulation on an overdriven LCD display. The simulation shows easily the impact of the overdrive.

predicting motion artifacts in matrix displays”, Journal of the SID 14/11, 957, 2006.

[6] T. Kamamoto, S. Sasaki, Y. Igarashi, Y. Tanaka, “Guiding principles for high quality moving picture in LCD TVs”, Journal of the SID 14/11, 933, 2006.

[7] H. Wang, T. Wu, J. of Appl. Physics, vol 95, N°10, 5502, 2004

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