IEC TR 62977-5-2:2021

IEC TR 62977-5-2 ®
Edition 1.0 2021-03
TECHNICAL
REPORT
colour
inside
Electronic displays –
Part 5-2: Visual assessment – Colour discrimination according to viewing
direction
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IEC TR 62977-5-2 ®
Edition 1.0 2021-03
TECHNICAL
REPORT
colour
inside
Electronic displays –
Part 5-2: Visual assessment – Colour discrimination according to viewing

direction
INTERNATIONAL
ELECTROTECHNICAL
COMMISSION
ICS 31.120 ISBN 978-2-8322-9514-4

– 2 – IEC TR 62977-5-2:2021 © IEC 2021
CONTENTS
FOREWORD . 4
INTRODUCTION . 6
1 Scope . 7
2 Normative references . 7
3 Terms, definitions and abbreviated terms . 7
3.1 Terms and definitions . 7
3.2 Abbreviated terms . 8
4 Introduction to visual assessment . 8
5 Standard measuring equipment and coordinate system . 10
5.1 Light measuring devices . 10
5.2 Viewing direction coordinate system . 10
6 Test patterns . 11
6.1 Geometrical construction . 11
6.2 Colour assignment . 12
6.3 Dots fill factor . 14
7 Visual assessment method . 15
7.1 General description of the assessment . 15
7.2 Test room conditions . 15
7.3 DUT parameters . 16
7.4 Observers . 16
7.5 Instructions for visual assessment method . 17
7.6 Repeatability . 18
7.7 Presentation and interpretation of the experimental assessment results . 18
Annex A (informative) Fill factor dependency . 26
Annex B (informative) Display white luminance dependency . 29
Annex C (informative) Pattern generator . 32
Bibliography . 34

Figure 1 – Comparison between the proposed visual assessment and the conventional
physical measurement . 9
Figure 2 – Definition of viewing directions by the spherical angles of θ and φ . 10
Figure 3 – Layout for horizontal viewing direction . 11
Figure 4 – Pattern structures. 12
Figure 5 – Colour assignment of test pattern . 14
Figure 6 – Test environment . 15
Figure 7 – Average CMF according to ethnic origin . 17
Figure 8 – Assessment procedure . 18
Figure 9 – Visual assessment results: statistical plot (upper figure) and mean
recognition rates (lower figure) . 19
Figure 10 – Statistical plot (upper) and mean of colour differences (lower) of test
patterns . 20
Figure 11 – Process of S-CIELAB transformation . 21
Figure 12 – Contrast sensitivity function of HVS. 21
Figure 13 – S-CIELAB results: statistical plot (upper) and mean colour difference
(lower) . 22

Figure 14 – Correlation between physical measures and S-CIELAB results . 23
Figure 15 – Correlation between visual assessment and S-CIELAB method . 23
Figure 16 – Pattern dependency . 24
Figure 17 – Observer dependency . 25
Figure A.1 – Fill factor variation . 26
Figure A.2 – FF dependency . 27
Figure A.3 – Colour difference relationship between pictorial image and test patterns
with various FF . 28
Figure B.1 – Colour reproduction performance of the DUT . 30
Figure B.2 – White luminance dependency . 31
Figure C.1 – Pattern generator user interface . 33

Table 1 – Measurement directions for DUTs in living rooms . 11
Table 2 – Reference colours of test pattern . 13
Table 3 – Test room condition . 15
Table 4 – Experimental setup of the DUT . 16
Table 5 – Correlation coefficients . 24
Table B.1 – Experimental setup and parameters . 29

– 4 – IEC TR 62977-5-2:2021 © IEC 2021
INTERNATIONAL ELECTROTECHNICAL COMMISSION
____________
ELECTRONIC DISPLAYS –
Part 5-2: Visual assessment –
Colour discrimination according to viewing direction

FOREWORD
1) The International Electrotechnical Commission (IEC) is a worldwide organization for standardization comprising
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IEC TR 62977-5-2 has been prepared by IEC technical committee 110: Electronic displays. It
is a Technical Report.
The text of this Technical Report is based on the following documents:
Draft Report on voting
110/1227/DTR 110/1251A/RVDTR
Full information on the voting for its approval can be found in the report on voting indicated in
the above table.
The language used for the development of this Technical Report is English.
This document was drafted in accordance with ISO/IEC Directives, Part 2, and developed in
accordance with ISO/IEC Directives, Part 1 and ISO/IEC Directives, IEC Supplement, available
at www.iec.ch/members_experts/refdocs. The main document types developed by IEC are
described in greater detail at www.iec.ch/standardsdev/publications.

A list of all parts in the IEC 62977 series, published under the general title Electronic displays,
can be found on the IEC website.
The committee has decided that the contents of this document will remain unchanged until the
stability date indicated on the IEC website under "http://webstore.iec.ch" in the data related to
the specific document. At this date, the document will be
• reconfirmed,
• withdrawn,
• replaced by a revised edition, or
• amended.
This publication contains attached files in the form of compressed Zip files (“Pattern generator”
program in Annex C). These files are intended to be used as a complement and do not form an
integral part of the publication.
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IMPORTANT – The 'colour inside' logo on the cover page of this publication indicates
that it contains colours which are considered to be useful for the correct understanding
of its contents. Users should therefore print this document using a colour printer.

– 6 – IEC TR 62977-5-2:2021 © IEC 2021
INTRODUCTION
Current display measurement standards use mainly simple patterns for physical measurement
methods to characterize display performance. Recent studies have introduced multiple colour
test patterns to simulate real images based on physical measurements. Such types of physical
measurements are commonly used and are an essential method of the industry. Often, humans
can perceive a structural similarity [1] as much as physical factors (colour, luminance, etc.).
This document describes a method of structural sensitivity assessment dependent on the
viewing direction, interpretation of assessment results, and correlation between assessment
results and physical measurements. This correlation value can be used as the basis for
determining one aspect of the viewing direction range of a display, which has relevance from a
visual quality point of view. However, it should be noted that several characteristics (e.g.
contrast ratio, resolution, and colour shift) are simultaneously changing in the assessment of
the viewing direction.
This visual assessment approach has the benefit of obtaining direct human response to
variations for any given task. However, it can be challenging with this approach to get
reproducible experimental results due to different colour matching functions (CMFs),
differences in observer experience, observer fatigue, attitudes toward experiments, human
adaptation to different experimental environments (including illumination conditions, surround,
or other environmental factors), content-dependent differences, and other variables. Therefore,
the uncertainty for these visual assessment methods can be higher compared to
instrumentation-based evaluation methods. Accordingly, this document should be seen as a
limited constrained model to help understand some of the various human responses to the
experiment. It can be used as an indicator of such response and to provide a framework to
guide the acquisition of performance data by way of reliable instrumentation-based
measurement methods.
_____________
Numbers in square brackets refer to the Bibliography.

ELECTRONIC DISPLAYS –
Part 5-2: Visual assessment –
Colour discrimination according to viewing direction

1 Scope
This part of IEC 62977, which is a Technical Report, describes the visual assessment method
of the viewing direction characteristics of display devices. This document reviews the visual
assessment of viewing direction by using special test patterns to estimate colour changes,
image structure, and image luminance.
Experimental results are shown to reveal the effectiveness of this kind of visual assessment.
This method is a valuable tool for identifying image quality issues, but physical measurements
will be used to confirm display performance specifications.
NOTE The visual assessment results will depend on the test pattern parameters and display setup conditions. As
the viewing direction changes, characteristics such as contrast ratio, resolution, and device colour-shift
simultaneously change in the perceived image.
2 Normative references
There are no normative references in this document.
3 Terms, definitions and abbreviated terms
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminological databases for use in standardization at the following
addresses:
• IEC Electropedia: available at http://www.electropedia.org/
• ISO Online browsing platform: available at http://www.iso.org/obp
3.1 Terms and definitions
3.1.1
pixel
smallest encoded picture element in the input image
Note 1 to entry: Pixel is used as the unit of resolution of image sensor, image signal and display, respectively.
3.1.2
structural similarity
SS
measurement of the similarity between two images by comparison of the luminance, contrast
and structure
Note 1 to entry: Refer to [1].

– 8 – IEC TR 62977-5-2:2021 © IEC 2021
3.1.3
viewing direction
direction from which the display is viewed as measured from the normal using spherical-polar
coordinates
3.2 Abbreviated terms
APL Average picture level
CCT Correlated colour temperature
CIE Commission Internationale de L’Eclairage
(International Commission on llumination)
CIE 1976 (L*a*b*) colour space [2]
CIELAB
CMF Colour matching function
CSF Contrast sensitivity function
DFT Discrete Fourier transform
DUT Device under test
FF Fill factor (of a dot)
HVS Human visual system
JND Just noticeable difference
LMD Light measuring device
MSE Mean squared error
PSNR Peak-signal-to-noise ratio
SS Structural similarity
TV Television set
ZF Zooming factor
CIE 1976 (L*a*b*) colour difference
ΔE*
ab,76
ΔE* CIE 2000 colour difference [3]
4 Introduction to visual assessment
Traditional physical measurements to describe the properties of displays have been used on a
regular basis. Sometimes, visual assessment methods have been introduced due to cost
concerns, limitations of physical measurements, or to verify the effectiveness of physical
methods with regard to HVS.
As typical examples, IEC has published a number of visual assessment methods
(IEC 62629‑13-1 [32], IEC 61747-20-3 [33], IEC 62341-6-2 [34] and IEC 61988-2-4 [35]). These
documents focus on the qualities of images (perceptual screen resolution, cross-talk, colour
gradation, half-luminance viewing angle, 2D-artefacts, and 3D-ghosts), and defects (subpixel-,
mura- and line-defects) of displays. Such methods and the colour- and greyscale inversions
under varying viewing directions were also the focus of IDMS:2012 [4], Chapter 4.
In broadcasting technology, for example, visual image quality assessments for video clips are
popularly used. Many technical parameters, test environments, test methods and datasets used
in image quality assessments are described in standards and recommendations issued by the
International Telecommunication Union (ITU) [5] and the European Broadcasting Union (EBU)
[6].
Usually the image quality of a display depends on the viewing direction. To describe the
dependence in the viewing direction, the conventional physical measuring method [7] is well-
established in industry. It is stable, robust and can uniquely determine the viewing direction
range using the colour difference metric. But the viewing direction range is a complex feature
and determined by multiple factors that vary simultaneously, for example luminance, tone
rendering, and colour shift. It is a challenge to weigh these factors into a single viewing direction
range metric. Another challenge is that measurements use aperture colours (colours in a small
portion of the viewing field) which do not take into account spatial filtering in the HVS. To include
the CSF of the HVS, the S-CIELAB method has been used [8].
The advantage of physical measurements is that CIELAB with ∆E* takes chromatic,
luminance adaptation and the uniform JND metric into account for the representative CIE-CMF.
However, human colour perception is a very complex process. It depends on many factors, such
as chromatic and luminance adaptation, lateral inhibition of ganglion cells, contrast sensitivity,
simultaneous contrast, adaptation on local image features and subjectivity of colour perception
(human colour experiences) [9].
An imaging LMD with ∆E* metric can provide a stable and objective measurement result for
the representative CIE-CMF. However, it cannot represent the entire colour perception of
observers and observer variabilities. To achieve more precise perception an imaging LMD can
be combined with a vision model, but it is not easy to describe complex processes of human
colour perception with a few mathematical functions. As a concern, the physical measurement
does not fully reflect the HVS sensations and abilities. A colour difference between two colours
with physically constant colour differences can be perceived differently by humans, affected
according to changes in various conditions (e.g. object size, shape, ambient brightness, etc.)
[9]. In particular, colour discrimination between two coloured objects within the same viewing
direction is not included in the physical measurement. Colour discrimination is the ability of
human perception to distinguish two different coloured objects. It can also be expressed in
terms of a colour difference between two coloured objects within the same viewing direction
such as ∆E* . In conventional physical measurement, there are only the measurement
methods of colour and luminance differences between the normal-axis (as reference) and the
other viewing direction (see Figure 1).
Recently, it was verified that the SS [1] is a meaningful criterion of image quality. SS was
developed to improve on conventional methods such as peak signal-to-noise ratio (PSNR) and
mean squared error (MSE). SS is a perception-based model that considers image degradation
as perceived change in structural information. It is the reproduction ability of the image detail
and shape. Thus, SS can be an additional important feature beyond the conventional
measurement of the colour and luminance characteristic. Changing the viewing direction can
diminish the shape of the object and the image details. One of the functional components of the
SS is that two neighbouring colours could be discernible to each other.

Figure 1 – Comparison between the proposed visual assessment
and the conventional physical measurement

– 10 – IEC TR 62977-5-2:2021 © IEC 2021
The conceptual Figure 1 shows the differences between the conventional physical
measurement and the new visual assessment for the colour discrimination under varying
viewing directions. The conventional method describes well the viewing direction-dependent
characteristic in relation to the normal axis (IEC TS 62977-3-1 [7]). It checks the colour
constancy between two viewing directions. With respect to the viewer, it is also important to get
visual information within a same viewing direction.
Another meaning of the visual assessment method in comparison to the physical measurement
is with respect to observers. The colourimetric value of the measuring instrument is evaluated
by the 1931 CIE-CMF, which is approximately derived from the average sensitivities of a number
of observers. The effectiveness of this CMF has been extensively studied and there has been
a lot of demand for improvements to this CMF. Although 1931 CIE-CMF had to be supplemented,
continuous use of this CMF was considered more efficient than revision [10], [11]. Recently,
CIE published the observer's LMS-cone sensitivities by age and angle of view [11]. At a constant
viewing angle, the cone sensitivities slowly shift towards the long wavelength. The shift is about
5 nm between 10 years and 60 years of age. This shift is accelerated from the age of 70 with
10 nm and more. Thus, it is preferred to supplement the physical measurement method with the
visual assessment method because there is a limit to represent the change of the spectral
sensitivity of different observers by the mean value derived CMF. Such observer variation would
be roughly treated as a statistical plot of observer ratings by the visual assessment method.
Usually the colour perception of humans is also influenced by geometric changes of object
shapes and spatial frequency content which happen with a change of the viewing direction [9].
It would be helpful for visual assessment, if the proposed method would be added.
Therefore, the visual assessment method of this document is a supplemental method for the
conventional method.
5 Standard measuring equipment and coordinate system
5.1 Light measuring devices
Light measuring devices (LMDs) for the initial setup of the visual assessment considered in
IEC 62977-2-1:2021, 5.3, are used [13]. An LMD or imaging LMD can be used in order to
measure the colour differences of the test pattern, the correlated colour temperature and peak
luminance of a display white.
NOTE A vision model of an imaging LMD depends on products. Here, imaging LMDs are calibrated by XYZ values.
5.2 Viewing direction coordinate system
The viewing direction coordinate system for LMDs specified in IEC 62977-2-1:2021, 5.6 is used,
and is represented in Figure 2.

Figure 2 – Definition of viewing directions by the spherical angles of θ and φ

For visual assessment in the horizontal direction, the observer can be positioned as shown in
Figure 3. The observing layout for the vertical viewing direction can also be used for the
horizontal layout with a rotating the screen at 90° to construct a simple test equipment with only
horizontal tilt, or by tilting the screen vertically at the normal viewing direction.

Figure 3 – Layout for horizontal viewing direction
The suggested ranges of the direction (θ and φ) are shown in Table 1 for DUTs in living rooms
[7].
Table 1 – Measurement directions for DUTs in living rooms
θ (degree) φ (degree)
Horizontal 0, ±15, ±30, ±45, ±60 0
Vertical 0, ±15, ±30 90
Diagonal 45 45, 90, 135, 225, 270 and 315

NOTE Table 1 is consistent with IEC TS 62977-3-1:2019, Table 1 [7]. If needed, it can be adjusted by test
organizations for their purposes.
6 Test patterns
6.1 Geometrical construction
The geometrical structures and dimensions of the test patterns are shown in Figure 4. The first
rectangular colour patch type (Figure 4a)) is designed for the optical measurement by the LMD.
The second inside font (number or alphabet) type (Figure 4b)) is used for the visual assessment.
All sizes are specified by factors of the display screen height (H), and the size of the inside
stimuli is 1/18 × H (font height). Therefore, the font width is defined by the notation of the used
font format. The inside font has a 2° viewing angle as the default for the observer. The viewing
angle is kept at 2°.
– 12 – IEC TR 62977-5-2:2021 © IEC 2021

a) Type 1 b) Type 2 c) viewing angle

Figure 4 – Pattern structures
The viewing angles of the number, intermediate circle and outer grey rectangle are designed
for the stimulus (2°), proximal field (5°) and background (10°) according to the recommendation
of Hunt [9], [14].
NOTE 1 The viewing angles of the test pattern in the visual assessment results in this document were as follows:
2°, 4°, and 8° for stimulus, proximal and background regions, which are slightly different from Figure 4.
NOTE 2 The test pattern used for this document can be modified, produced and used according to the purpose of
each party.
6.2 Colour assignment
For the assigning of colours in the test pattern, a Macbeth colour chart was used (Table 2) [15],
[16], [17]. It consists of six achromatic- and eighteen chromatic colours. These twenty-four
colours were named as reference colours, and the proximal fields (outer rectangle of Type 1
and circle of Type 2 in Figure 4) were filled with these reference colours.
The inside stimuli (small rectangle of Type 1 and numbers of Type 2 in Figure 4) were filled with
one of the variated colours in the lightness, hue and chroma direction in the CIE-L*C*H* colour
space (Figure 5a)). For example, the hue (H*) of the first row numbers in Figure 5b) was
increased (+ marked number "1") or decreased (- marked number "2") from the hue values of
the reference colours. The second row numbers “3” and “4” in Figure 5b) were changed by the
chroma values (C*) in the same way. Figure 5d) is the example for the chromatic and achromatic
∗
patterns for 5 𝛥𝛥𝐸𝐸 difference.
Table 2 – Reference colours of test pattern
CIE/ SMPTE-303M(D65) ITU-R. BT.709 ITU-R.BT.2020
No.
X Y Z L* a* b* C* H* R' G' B' R' G' B'
1 0,109 7 0,097 0,060 6 37,3 13,71 15,54 20,72 0,85 0,404 1 0,25 0,187 4 0,352 4 0,262 7 0,198 7
2 0,381 2 0,355 8 0,259 2 66,2 14,43 17,78 22,9 0,89 0,747 1 0,548 6 0,46 0,677 5 0,563 8 0,474 5
3 0,178 6 0,190 8 0,345 2 50,78 -1,46 -21,23 21,28 4,64 0,313 6 0,432 7 0,573 6 0,370 8 0,427 4 0,559 3
4 0,101 0,129 8 0,066 9 42,73 -16,33 22,35 27,68 2,2 0,281 0,366 7 0,186 1 0,308 5 0,359 8 0,209 1
5 0,258 3 0,243 8 0,453 2 56,47 11,51 -24,38 26,96 5,15 0,475 3 0,463 6 0,663 4 0,481 2 0,467 2 0,645 7
6 0,312 7 0,427 3 0,446 9 71,37 -31,43 2,02 31,49 3,08 0,345 4 0,717 8 0,630 8 0,512 3 0,697 7 0,635 4
7 0,364 6 0,293 2 0,058 9 61,06 31,13 57,23 65,15 1,07 0,838 0,432 6 0,101 2 0,710 3 0,470 3 0,184 9
8 0,134 2 0,117 6 0,372 3 40,83 15,4 -41,86 44,6 5,06 0,229 9 0,301 3 0,609 5 0,280 6 0,302 1 0,584 5
9 0,284 5 0,192 2 0,137 5 50,94 45,92 15,09 48,33 0,32 0,746 3 0,273 9 0,327 4 0,616 4 0,329 3 0,334 2
10 0,086 8 0,065 2 0,146 9 30,69 23,92 -22,07 32,55 5,54 0,304 4 0,171 3 0,364 5 0,270 3 0,186 0,350 5
11 0,332 0,436 6 0,111 9 72,00 -27,18 58,05 64,1 2,01 0,585 3 0,706 9 0,180 4 0,617 3 0,695 4 0,277 7
0,461 7 0,431 2 0,084 71,64 15,31 65,96 67,71 1,34 0,890 3 0,599 2 0,115 6 0,786 0,620 9 0,230 6
0,084 0,062 2 0,3 29,96 24,61 -50,89 56,53 5,16 0,117 4 0,180 6 0,548 9 0,176 1 0,184 6 0,522 2
0,145 0,235 8 0,095 1 55,66 -41,73 34,83 54,36 2,45 0,210 9 0,545 8 0,212 0,356 1 0,526 7 0,257 8
0,201 7 0,118 2 0,052 40,93 52,85 25,6 58,73 0,45 0,665 2 0,122 3 0,165 1 0,531 6 0,204 8 0,179 9
0,560 5 0,596 4 0,095 6 81,64 -1,58 79,46 79,48 1,59 0,923 6 0,760 8 0,047 6 0,852 4 0,769 0,242 4
17 0,294 2 0,192 7 0,302 9 51.00 49,43 -15,03 51,66 5,99 0,71 0,270 9 0,537 6 0,594 7 0,324 5 0,523
18 0,144 7 0,198 7 0,395 2 51,69 -24,78 -25,95 35,88 3,95 0,139 6 0,488 8 0,616 4 0,248 9 0,469 3 0,600 5
19 0,839 8 0,887 6 0,923 5 95,48 -0,73 2,9 2,99 1,82 0,947 4 0,943 6 0,918 0,944 9 0,943 6 0,920 8
20 0,558 8 0,588 7 0,628 7 81,22 -0,18 1,09 1,11 1,74 0,769 4 0,767 0,758 1 0,768 1 0,767 1 0,759 1
21 0,336 7 0,355 1 0,381 1 66,14 -0,28 0,69 0,75 1,96 0,590 9 0,591 2 0,585 4 0,590 7 0,591 1 0,586
22 0,183 0,193 0,208 3 51,04 -0,23 0,35 0,42 2,16 0,424 6 0,425 6 0,422 7 0,424 9 0,425 5 0,423
23 0,079 6 0,084 0,090 6 34,8 -0,22 0,28 0,36 2,23 0,260 9 0,261 9 0,259 7 0,261 2 0,261 8 0,259 9
24 0,028 3 0,029 5 0,032 2 19,84 0,48 -0,05 0,48 6,19 0,128 9 0,125 3 0,126 4 0,127 6 0,125 5 0,126 4
NOTE The values of R’G’B’ are the normalized nonlinear values. The hue values (H*) are presented here in radian.

Luminance and size of the background grey can be freely assigned by test organizations.
However, it is preferable to assign the 18 % (L* = 56 for dim-surround) luminance of the display
white and full screen size. Therefore, 18 % grey luminance represents the average luminance
of scenes when watching natural scene videos according to the grey-world theory [18]. Hence,
the human visual system might be adapted to a white with five times the average luminance of
this scene approximately [19], [20]. This grey background might contribute to the stabilization
of the light adaptation of the HVS.
Figure 5d) shows an example of the achromatic and chromatic test patterns. Twenty-four test
patterns, each with four fonts, can be shown to observers for the visual assessment.

– 14 – IEC TR 62977-5-2:2021 © IEC 2021

a) Colour variation b) Chromatic pattern c) Achromatic pattern

*
d) Example for
∆=E 5
Figure 5 – Colour assignment of test pattern
6.3 Dots fill factor
Most image contents are usually structured. This image complexity can be represented as a fill
factor (FF) in the test pattern as shown in Figure 5d). Formula (1) defines the fill factor FF as a
ratio of the area of dots (A ) to the area of circles (A ). This type of construction is similar to
D C
the Ishihara pattern for colour deficiency check [21].
A
D
FF[]% 100×
(1)
A
C
For the visual assessment, an FF of 70 % was utilized by default. The dots with multiple dot
sizes and locations in the circle of the test pattern were randomly generated by a program. The
diameters of the dots have a viewing angle between 0,178° and 0,028°. For all observers the
same dot patterns shown in the same order would be viewed in order to get the same sensation
within a same visual assessment session.
More details related to this topic are described in Annex A.
=
7 Visual assessment method
7.1 General description of the assessment
This visual assessment method was constructed based on the single stimulus method (SSM) of
ITU-R BT.500-13 [5]. A sequence of a single test pattern was presented and the observers
provided their responses for the entire presentation. All responses were gathered by an
operator and the statistical results of all responses were evaluated.
Figure 6 shows the test room environment. The DUT was connected via an HDMI interface with
an operating PC, in which the test pattern sequence was generated by an operator manually or
semi-automatically. These test patterns on the DUT were sequentially exposed to the observer,
who was asked about the visible fonts in each test pattern. The operator recorded the observer’s
responses as 'True' or 'False' on a form or in a "pattern generator" program for example. The
program could also generate all observer responses as a spreadsheet file after the test session.
The pattern generator will be provided and more details about this program can be found in
Annex C.
Figure 6 – Test environment
7.2 Test room conditions
The observers’ viewing conditions were arranged as follows (Table 3). The room was set to
dark to prevent any reflection on the screen. The surrounding area of the DUT screen was
equipped with a grey curtain with a neutral reflectance of about 20 %, allowing for a neutral
visual adaptation. Before starting the visual assessment, the observers had at least a 15 min
adaptation time to the test room environment including the screen with the 18 % grey pattern.
The viewing distance for a given pattern size satisfied the described viewing angle condition in
Figure 4c). Here, the zooming factor (Z ) is an integer scale factor (for example, from 1 to 4) of
F
the dotted test pattern to obtain a sufficient visual resolution during the visual judgment with a
low resolution and a small screen size DUT. For example, applying Z = 2 doubles the horizontal
F
and vertical size of the test pattern. When using Z , the aspect ratio of the test pattern remains
F
unchanged.
Table 3 – Test room condition
Surround Dark
< 1 lux on the screen
(measured perpendicularly to the screen)
Viewing distance 1,6 × H × Z
F
Z : zoom factor of pattern
F
– 16 – IEC TR 62977-5-2:2021 © IEC 2021
7.3 DUT parameters
Table 4 shows the experimental setup parameters of the DUT. The correlated colour
temperature (CCT) of the DUT was set at D65 white. However, another CCT is also possible.
In this case, the CCT with chromaticity coordinates can be reported in the results document.
The luminance of the display white varies from display to display, so the luminance of white can
be freely adjusted by the test organization, otherwise it is possible to use the factory setup. To
check the quality between two different DUTs, it was necessary to keep the setup parameters
because the visual
of the display the same. However, it was preferred to set over 100 cd/m
assessment result was slightly affected by the luminance of the pattern images. This luminance
dependency is discussed in Annex B. All physical values were measured from the normal
direction of the DUT screen.
NOTE 1 The minimum white luminance of some displays does not guarantee sufficient colour luminance. In this
case, the display would be additive or the total luminance of all primary colours would be greater than 100 cd/m .
Table 4 – Experimental setup of the DUT
Correlated colour temperature Test organization specific
Recommended: D65
CIE – (x, y) = (0,312 7, 0,329 0)
White luminance  Factory default or test organization specific
Dark room contrast ratio
(ratio of the luminance of the peak luminance to the Factory default, test organization specific or DUT
inactive screen) specific maximum value
Display brightness and contrast Factory default or test organization specific
Display resolution
≥ 30 pixels per degree
NOTE 2 Current TVs can reach over 500 cd/m , where the R colour can be saturated. In such a case, such a high
level of brightness would be avoided for the test.
To display the test pattern, the required resolution of the DUT would be greater than 30 pixels
per degree (240 pixels × 240 pixels for the test pattern). Any type of DUT with a resolution over
this minimum resolution can be tested.
All setting parameters and all other measurements are retained throughout the whole visual
assessment.
7.4 Observers
The following criteria on observers are reproduced from ITU-R BT.500-13 [5].
Usually, observers can be experts or non-experts depending on the objectives of the
assessment. An expert observer is an observer that has expertise in image artefacts. A non-
expert observer is an observer that has no expertise in image artefacts. In any case, observers
would not be, or have been, directly involved in related research and development. Prior to a
session, the observers could be screened for normal visual acuity on the Snellen or Landolt
chart, and for normal colour vision using specially selected charts (Ishihara, for instance). At
least 15 observers would participate [5], [22]. For studies with limited scope, for example of an
exploratory nature, fewer than 15 observers may be used. In this case, the study would be
identified as "informal". Fifteen observers with a limited age range (e.g., 20 years old to 60
years old) and a regular sample can be sufficient to reproduce average results. However, 15
observers would be insufficient to reproduce observer variability in perceived colour differences
(or colour discrimination) for the test pattern [23]. In this case, the test organization can manage
to increase the number of observers.

A study of consistency between results at different testing laboratories has been carried out. A
possible explanation for the differences between laboratories is that there can be different skill
levels amongst different groups of observers. However, in the interim, experimenters would
include as many details as possible on the characteristics of their assessment panels to
facilitate further investigation of this factor. Suggested data to be provided could include:
occupation (e.g., broadcast organization employee, university student, or office worker), gender,
and age.
The 1931 CIE-CMF is derived from average values of the spectral responses of a number of
colour-normal observers [10]. The CMF is usually dependent on age, viewing field size, density
of eye-lens and macula, and optical densities of LMS-cones rather than on ethnic origin and
gender, according to Asano [23]. These characteristic values depend on individual observers.
The average CMF of 151 observers of Asano’s database (122 Europeans, 9 North Americans,
17 Asians and 3 Africans) according to the ethnic origin are reproduced in Figure 7.
NOTE More relevant factors on CMF are the above-mentioned characteristics of individual observers rather than
ethnic origin.
Figure 7 – Average CMF according to ethnic origin
7.5 Instructions for visual assessment method
A session would not be exceeding 30 min to prevent any response affected by tiredness or
adaptation.
The method of assessment would be carefully introduced to the observers and sufficient training
sequences would demonstrate the range and the type of the test
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