IEC 61747 6 3 Edition 1 0 2011 07 INTERNATIONAL STANDARD NORME INTERNATIONALE Liquid crystal display devices – Part 6 3 Measuring methods for liquid crystal display modules – Motion artifact measureme[.]
Temperature, humidity and pressure conditions
The standard conditions for measuring motion artifacts are a temperature of (25 ± 3) °C, relative humidity between 25% and 85%, and air pressure ranging from 86 kPa to 106 kPa Additionally, all visual inspection tests must be conducted at a temperature of (25 ± 5) °C.
Illumination condition
The illuminance at the measuring spot of the DUT shall be below 1 lx (standard dark room condition as defined in IEC 61747-6)
6 Standard motion-blur measuring methods
General
Motion induced object blur occurs due to the slow response of liquid crystal cells and the stationary representation of temporal images, influenced by the display's hold time and smooth pursuit eye-tracking As an object moves across the display, the human retina integrates the object's luminance over time This spatiotemporal integration can be measured through direct methods, such as using a pursuit camera system, or through indirect techniques that analyze temporal response curves to calculate the resulting motion induced object blur on the retina Both measurement approaches will be detailed in this standard.
Direct measurement method
Test patterns
To measure motion-induced object blur, various test patterns can be utilized, including the full test pattern, box test pattern, and line bar test pattern It is essential to report the specific test pattern(s) employed When implementing a pursuit system, the test pattern's width should be at least five times the advancement (step-width) per frame to effectively capture the display's total temporal response Additionally, it is advisable to incorporate a minimum of seven gray shades, encompassing black and white, for the gray levels of each section of the test pattern The lightness function should adhere to the specifications outlined in CIE 1976 (L*u*v*).
The L*a*b* color space allows for the equal spacing of intermediate gray shades along the lightness scale This is particularly useful for gray level data, such as the range from 0 to the maximum input available at LCD modules.
255 for an 8-bit LCD module, also can be used as this gray level
(A) Full test pattern (B) Box test pattern (C) Line bar test pattern
Figure 1 – Examples of edge blur test pattern
To measure the edge blur of an LCD module, a CCD camera should be utilized in conjunction with the pursuit measurement system illustrated in Figures 2 and 3 For additional information on these systems, please refer to the relevant literature listed in references [1] to [5].
1 Figures in square brackets refer to the Bibliography
Figure 2 – Example of a pivoting pursuit camera system
Figure 3 – Example of a linear pursuit camera system
When implementing the pursuit measuring system, it is recommended to use LMD devices such as CCD or CMOS cameras that incorporate the CIE 1931 photopic luminous sensitivity function for accurate luminance measurement Additionally, it is crucial to synchronize the scroll speed of the test pattern with the pursuing speed of the LMD to prevent integration errors The pursuing system can be either a pivoting or linear design, as illustrated in Figures 2 and 3, with angular rotation limited to less than ±5˚ to minimize viewing-angle dependencies.
6.2.2.2 Specified conditions a) Any deviations from the standard measurement conditions shall be reported: “Full test pattern” shown in Figure 1(A) shall be used as the test pattern for this test method Other test patterns, such as “Box test pattern” shown in Figure 1(B) or “Line bar test pattern” shown in Figure 1(C), can be used additionally depending on the requirements The used patterns shall be reported
When using test patterns other than the standard "Full test pattern," it is crucial to exercise caution, as the pattern size may affect the luminance levels of LCD modules with automatic luminance control Additionally, blurred edges may extend onto adjacent edges, leading to ambiguity in data analysis The signal levels, including the start and end levels for the test pattern, are summarized in the table.
Table 1 – Step response data for different luminance transitions
2) Shutter speed of camera : 1/20 sec.
Analysis method
The time between the transition from 10 % to 90 % in the luminance transition curve (see
Figure 4) is used to represent blurred edge time Other ranges, such as 40 % to 60 %, can be used, but they shall be reported
R el at iv e l um inan ce i nt ens ity
Figure 4 – Example of luminance cross section profile of blurred edge
The extended blurred edge time is defined as EBET = BET/0.8, which linearly extends the
BET to the 0 % to 100 % levels (see Figure 5)
R el at iv e l um inan ce i nt ens ity
Figure 5 – Example of luminance cross-section profile of blurred edge
The process of obtaining a PBET curve involves converting a luminance blurred edge into a spectrum using fast Fourier transformation (FFT) This spectrum is then multiplied by values provided by the contrast sensitivity function (CSF) Finally, an inverse FFT is applied to derive the PBET curve, with the PBET value representing the distance between the peaks of the curve, measured in milliseconds.
R el at iv e l um inan ce
Luminance profile CSF PBEW PBET
S en sit iv ity R ela tiv e s tim uli R ela tiv e s tim uli
CCD pixel Spatial frequency Spatial frequency Width Time
NOTE This standard recommends Peter Barten’s CSF (reference [7]), although other CSFs could be used
S(u) is the spatial contrast sensitivity function for binocular vision; m t (u) is the modulation threshold; u is the spatial frequency; σ is the standard deviation of the line-spread function of the eye ;
K is the signal-to-noise ratio (3,0);
T is the integration time of the eye (0,1 s);
X O is the angular size of the object;
X max is the maximum angular filed size of the object (12˚);
The maximum number of cycles that the eye can integrate is denoted as N max, which is 15 cycles The quantum efficiency of the eye is represented by η, with a value of 0.03 Additionally, the photon conversion factor, p, varies based on the light source used.
E is the retinal illumination (Td); Φ 0 is the spectral density of the neural noise (3,10 -8 sec deg 2 );
U o is the spatial frequency above which the lateral inhibition ceases (7 cycles/degree)
For the calculations, the viewing distance is set to 1.5 times the diagonal screen size of the active display area (approximately 3 x height of display active area)
Indirect measurement method
Temporal step response
The temporal step response measurement method is based on the literature, indicated in the
A schematic representation of the measurement set-up to measure the temporal step response is shown in Figure 7
Figure 7 – Set-up to measure the temporal step response
The measurement set-up, presented in Figure 7, comprises of the following components:
The DUT (1), which is the display to be measured
A pattern generator is essential for producing test patterns at the native display resolution and applicable refresh rates It should feature a control interface for easy selection of patterns and management of the measurement process The output can include multiple terminals such as LVDS or DVI, allowing connection to display input terminals Additionally, the pattern generator must provide a trigger output signal to initiate the data acquisition process.
A fast response photo-diode or opto-electrical detector is utilized to capture the temporal luminance generated by the Device Under Test (DUT) This detector features spectral sensitivity aligned with the spectral luminous efficiency function V(λ) for photopic vision.
A signal amplifier (4), which is used for signal amplification to match the input range of data acquisition device, and for low-pass filtering to attenuate the signal noise
A data acquisition device records the amplified signal v(t) from the photo-diode, requiring a minimum sampling rate of 10 kHz to ensure adequate temporal resolution for luminance data This sampling rate should align with the display's refresh rate for precise data analysis An oscilloscope or data-acquisition card can effectively acquire and digitize the time-varying luminance signal.
A luminance meter measures the display's luminance for each input code ranging from 0 to 255 in an 8-bit input signal This data allows for the conversion of the time-varying photo-diode signal, denoted as \$v(t)\$, into a corresponding time-varying luminance signal represented by the function \$L(t) = f(v(t))\$.
A control system (7), e.g a personal computer, which can be used to start the measurement procedure, and to collect and process all data
In liquid crystal displays, the transition of luminance levels is influenced by the chosen input codes, affecting perceived motion blur To accurately assess this, multiple luminance transitions must be measured, with a minimum of seven equidistant levels on the CIE1976 lightness scale Initially, it is essential to measure the luminance transfer function of the device under test (DUT) to establish the appropriate luminance levels.
The pattern generator should generate images with grey-level values ranging from 0 to 255
To accurately measure luminance levels on an 8-bit display, a luminance meter should be utilized Concurrently, the signal from a photo-diode must be measured to facilitate the conversion of time-varying voltage values into corresponding luminance values The seven identified luminance levels will serve as the starting and ending points for assessing the temporal step responses of the Device Under Test (DUT) In this process, a pattern generator will create the necessary luminance transitions, which will be captured by a data acquisition device through the photo-diode and amplifier setup.
The control system (7) allows for the acquisition of multiple traces to facilitate temporal averaging of step responses To ensure accurate and stable start and end levels, the step response must include six frames for the start level and at least six frames for the end level It is permissible to record both rising and falling luminance transitions in a single pass The measurements are organized in a table, where each cell contains an array of temporal luminance data Additionally, separate tables for each primary color and white are necessary to analyze motion-related color artifacts (see Table 1).
The motion picture response curve for each transition and primary color is derived from the temporal step response through a straightforward convolution with a moving window function that is one frame time wide An illustration of this convolution process is shown in Figure 8, highlighting the resulting output.
LC response time and window function: transition 0 -> 255 -> 0
N or m al iz ed l um inan ce
Figure 8 – Example of a LC response time measurement
N or m al iz ed l um inan ce
Figure 9 – Example of a motion picture response curve derived from the response measurement presented in Figure 8, and a convolution with a one frame wide window function
The motion picture response curves allow for the derivation of edge profiles based on object speed By converting these curves from the temporal to the spatial domain using the formula \( x_r = -\nu \cdot \tau / T_f \), where \( x_r \) represents the display pixel position on the retina, \( \tau \) is time, \( T_f \) is frame time, and \( \nu \) is motion speed in pixels per frame, we can analyze luminance transitions As motion speed increases, the edge blur becomes less pronounced, affecting visibility based on the relationship between display pixel size, viewing distance, luminance contrast, and edge profile Currently, the edge profile serves as a reliable measure of motion performance, particularly for continuous backlight type LCDs, where metrics such as BET, EBET, and/or PBET can be derived.
High speed camera
The movement of a visual target is captured through multiple individual images taken within a single frame period, a process known as oversampling This is followed by numerical processing of the images to track the target's movement and assess the resulting blur characteristics.
When utilizing a moving block target as a test pattern, it is essential that the block width (w) is several times greater than the advancement per frame (∆), such as w = 5ã ∆ This ensures that the optical response stabilizes to a steady state, which serves as the reference level for evaluations.
The step-response of the display under test (DUT) is measured at either 100% or 0% level It is essential to ensure that the optical response is sampled with an adequate number of images during each frame period.
Characteristics for the width of the blurred edges can be obtained e.g by the distance between the 10 % and 90 % luminance levels (BEW) for both rising and falling edge
Optical transitions should be categorized based on the electrical driving conditions, such as increasing or decreasing voltage, rather than the slope of the optical response This approach helps prevent confusion, as a normally-black VA-LCD becomes bright when activated, while a normally-white TN-LCD turns dark upon activation.
General
Test results shall be reported in conjunction with the test method, the measurement conditions, and the analysis method(s).
Items to be reported
Environmental conditions
• Temperature, humidity, and atmospheric pressure
• Other conditions which are different from the standard measuring conditions (Clause 5)
Display parameters
• Backlight driving (impulse, stationary, blinking, scanning, other)
• Display gamma function (sometimes referred to as electro-optical transfer function)
• Drive mode (when optional driving mode, e.g “over drive” are installed in the module, the driving mode used for the test shall be reported)
NOTE Driving mode could interfere with experimental results.
Measuring method and conditions
• Measuring device (pursuit detection system, temporal step response, high speed camera)
• Number of bits in the measuring device, used to capture the luminance signal
• For imaging devices, the number of CCD pixels per display pixel, the diaphragm, the dynamic range, and the exposure time
• For pursuit systems, the synchronization accuracy
• Light measuring device (luminance meter, color analyzer, spectroradiometer, other)
• Scroll speed(s) (ex 8 pixels/frame)
• Gray levels (start levels and end levels, see Table 1)
• Other measuring conditions, such as shutter speed of the camera, frame frequency, etc.
Analysis method
• Threshold for EBET or BET calculation, e.g 10% to 90%
• Type of CSF and the CSF parameters for PBET calculation
An example for visually reporting the PBET analysis data is shown in Figure 10
Figure 10 – Example of measurement data reporting
The process involves analyzing a pair of digital grayscale images, consisting of a test image and a reference image, where one image may represent a uniform field These images can vary in pixel size, allowing for flexible analysis.
Images with a difference of 2 degrees or less can be effectively analyzed using appropriate metric extensions These images are evaluated at a designated viewing distance, where the relationship between pixels and luminance is established The metric's output quantifies the visibility of differences between test and reference images, expressed in just-noticeable difference (JND) units.
Line spreading is an effective technique for assessing motion blur and contrast degradation as a function of speed, all within a single measurement This method is more efficient and straightforward compared to dual edge techniques like Moving-Edge or Box Edge Blur By measuring the width and amplitude of the spreading line, it offers valuable insights into the motion performance of a display.
Measurement method is the same as edge blurring method except the test pattern (see [8])
Since this method is targeted to measure moving line spreading, narrow vertical line pattern should be used The example of the test pattern is shown in Figure B.1
Figure B.1 – Example of motion contrast degradation test pattern
The motion contrast degradation (MCD) characteristics can be analyzed due to line spreading measurement An example of the result is shown in Figure B.2
Line spreading of a white 2-pixel wide line moving at various speeds across a black background derived with an motion blur measurement system
Figure B.2 – Example of motion contrast degradation due to line spreading
To assess the luminance degradation of a line, the measurement system and process outlined in section 6.3.1 should be utilized It is essential that the number of frames corresponds to the line width By analyzing the motion picture response curves, one can calculate the line spreading for any specified motion speed.
The Dynamic Modulation Transfer Function (DMTF) is a key metric for assessing display performance in motion image rendering, reflecting a display's resolving power across various spatial frequency components at specific motion speeds DMTF calculations utilize captured temporal luminance variations from designated input code sequences, which, under smooth pursuit eye tracking conditions, translate into spatial effects This spatiotemporal conversion is achieved through smooth pursuit eye tracking and temporal light integration at the human retina By modeling the perceived performance of a moving sine wave pattern on the display and analyzing the resulting contrast degradation, the DMTF properties are established.
The DMTF is defined as the ratio of the perceived amplitude of a moving pattern, \(A_p\), to the amplitude of the original input pattern, \(A_i\), expressed mathematically as DMTF(V,f) = A_p(V,f)/A_i In this equation, \(V\) represents the motion speed of the pattern in pixels per frame, and \(f\) denotes the spatial frequency of the pattern in cycles per pixel.
DMTF calculations is presented in Figure C.2
For more details on DMTF calculation, see e.g [16]
Figure C.1 – Example of motion contrast degradation
Figure C.2 – Example of DMTF properties for different motion speeds ( V )
[1] Y Igarashi, et al., “Summary of moving picture response time (MPRT) and futures”, SID
International Symposium Digest of Technical Papers 35, 1262 – 1265 (2004)
[2] J Miseli, “Motion artifacts”, SID International Symposium Digest of Technical Papers 35,
[3] M Shigeta, and H Fukuoka, “Development of high quality LCDTV”, SID International
Symposium Digest of Technical Papers 35, 754 – 757 (2004)
[4] K Oka, and Y Enami, “Development of accurate and reliable system for motion picture quality analysis”, IDW’03 Proceedings, 1483 (2003)
[5] K Oka, and Y Enami, “Moving picture response time (MPRT) measurement system”,
SID International Symposium Digest of Technical Papers 35, 1266 – 1269 (2004)
[6] K Oka, Y Enami, J.S Lee, and T Jun, “Edge blur width analysis using a contrast sensitivity function”, SID Symposium Digest Tech Papers 37, 10 – 13 (2006)
[7] P.G.J Barten, “Contrast sensitivity of the human eye and its effects on image quality”,
SPIE Optical Engineering Press, Bellingham, Washington, 1999
[8] J Miseli, J.S Lee, and J.H Suk, ”Advanced motion artifact analysis method for dynamic contrast degradation caused by line spreading”, SID Symposium Digest Tech Papers 37,
[9] X Li, X Yang, and C Teunissen, “LCD motion artifact determination using simulation methods”, SID Symposium Digest Tech Papers 37, 6–9 (2006)
[10] C Teunissen et al., “Method for predicting motion artifacts in matrix displays”, Journal of the Society for Information Display 14/10, 957–964 (2006)
[11] X Feng et al., “26.2: Comparison of Motion Blur Measurement in LCD”, SID Symposium
[12] A.B Watson, “31.1: Invited Paper: The Spatial Standard Observer: A Human Vision
Model for Display Inspection”, SID Symposium Digest Tech Papers 37, 1312–1315
[13] C Teunissen et al., “Perceived motion blur in LCD displays”, Proc IDW ‘06, 1463–1466
[14] X Li, L Chai, C Teunissen, and I Heynderickx, “Characterizing LCD motion color artifacts using simulation methods”, SID Symposium Digest Tech Papers 38, 1130–1133
[15] C Teunissen, X Li, L Chai, and I Heynderickx, “Modeling motion-induced color artifacts from the temporal step response”, Journal of the Society for Information
[16] Y Zhang, C Teunissen, W Song, and X Li, “Dynamic modulation transfer function: a method to characterize the temporal performance of liquid-crystal displays”, Optics
[17] IEC 61747-1:2003, Liquid crystal and solid-state display devices – Part 1: Generic specification
[18] IEC 61747-5:1998, Liquid crystal and solid-state display devices – Part 5:
Environmental, endurance and mechanical test methods
[19] ISO 9241, Ergonomics of human-system interaction – Ergonomic requirements and measurement techniques for electronic visual displays – Part 305: Optical laboratory test methods, Part 307: Analysis and compliance test methods
[20] ISO 11664-4:2008, Colorimetry – Part 4: CIE 1976 L*a*b* Color space
5.1 Conditions de température, d'humidité et de pression 32
6 Méthodes normalisées de mesure du flou de mouvement 32
7.2.3 Conditions et méthode de mesure 40
Annexe A (informative) Méthode d'essai subjective 42
Annexe B (informative) Dégradation du contraste de mouvement 43
Annexe C (informative) Fonction de transfert de modulation dynamique 45
Figure 1 – Exemples de mire pour flou de bords 32
Figure 2 – Exemple de système de caméra de poursuite pivotante 33
Figure 3 – Exemple de système de caméra de poursuite linéaire 33
Figure 4 – Exemple de profil de section de luminance pour un bord flou 35
Figure 5 – Exemple de profil de section de luminance pour un bord flou 35
Figure 7 – Montage de mesure de la réponse à un échelon temporel 37
Figure 8 – Exemple d'une mesure du temps de réponse des cristaux liquides 38
Figure 9 – Exemple d'une courbe de réponse d'image animée obtenue par la mesure de réponse présentée à la Figure 8, et une convolution avec une fonction fenêtre d'une trame de largeur 39
Figure 10 – Exemple de rapport de données de mesure 41
Figure B.1 – Exemple de mire d’essai de dégradation du contraste de mouvement 43
Figure B.2 – Exemple de dégradation du contraste de mouvement du fait de l'étalement de ligne 44
Figure C.1 – Exemple de dégradation du contraste de mouvement 45
Figure C.2 – Exemple de propriétés de la DMTF pour différentes vitesses de mouvement (V) 46
Tableau 1 – Données de réponses à un échelon pour différentes transitions de luminance 34
Partie 6-3: Méthodes de mesure pour les modules d'affichage à cristaux liquides – Mesure de l'artefact de mouvement dans les modules d'affichage à cristaux liquides à matrice active
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La Norme internationale CEI 61747-6-3 a été établie par le comité d’études 110 de la CEI:
Le texte de cette norme est issu des documents suivants:
Le rapport de vote indiqué dans le tableau ci-dessus donne toute information sur le vote ayant abouti à l’approbation de cette norme
Cette publication a été rédigée selon les Directives ISO/CEI, Partie 2
Une liste de toutes les parties de la série CEI 61747, sous le titre général Dispositifs d'affichage à cristaux liquides et à semiconducteurs, est disponible sur le site web de la CEI
The future standards of this series will adopt the new general title mentioned above Existing standards within this series will be updated in the next edition.
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