SIST ISO 12233:2017

INTERNATIONAL ISO
STANDARD 12233
Third edition
2017-01
Photography — Electronic still picture
imaging — Resolution and spatial
frequency responses
Photographie — Imagerie des prises de vues électroniques —
Résolution et réponses en fréquence spatiale
Reference number
ISO 12233:2017(E)
©
ISO 2017

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ISO 12233:2017(E)

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© ISO 2017, Published in Switzerland
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ISO 12233:2017(E)

Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Test conditions . 5
4.1 Test chart illumination . 5
4.2 Camera framing and lens focal length setting . 5
4.3 Camera focusing . 6
4.4 Camera settings . 6
4.5 White balance. 6
4.6 Luminance and colour measurements . 6
4.7 Gamma correction . 6
5 Visual resolution measurement . 7
5.1 General . 7
5.2 Test chart. 7
5.2.1 General. 7
5.2.2 Material . 7
5.2.3 Size . 7
5.2.4 Test patterns . 7
5.2.5 Test pattern modulation . 8
5.2.6 Positional tolerance . 8
5.3 Rules of judgement for visual observation . 8
5.3.1 Rules of judgement . 8
5.3.2 An example of a correct visual judgement . 9
6 Edge-based spatial frequency response (e-SFR) . 9
6.1 General . 9
6.2 Methodology .10
6.2.1 Selection of the edge region of interest (ROI) . .10
6.2.2 Transformation into effective exposure .10
6.2.3 Estimation of the location of the edge .10
6.2.4 Formation of a super-sampled line spread function array .12
6.2.5 Computation of the e-SFR .13
7 Sine-based spatial frequency response (s-SFR) measurement .13
8 Presentation of results .14
8.1 General .14
8.2 Resolution .14
8.2.1 General.14
8.2.2 Basic presentation .14
8.2.3 Representative presentation .14
8.3 Spatial frequency response (SFR) .15
8.3.1 General.15
8.3.2 Spatial frequency response . .15
8.3.3 Report of resolution value derived from the s-SFR .16
Annex A (informative) CIPA resolution test chart .17
Annex B (informative) Visual resolution measurement software .23
Annex C (informative) Low contrast edge SFR test chart with OECF patches .28
Annex D (normative) Edge spatial frequency response (e-SFR) algorithm .30
Annex E (normative) Sine wave star test chart .33
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ISO 12233:2017(E)

Annex F (normative) Sine wave spatial frequency response (s-SFR) analysis algorithm .35
Annex G (informative) Colour-filtered resolution measurements .39
Annex H (informative) Units and summary metrics .41
Annex I (informative) Original test chart defined in ISO 12233:2000 .44
Bibliography .48
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ISO 12233:2017(E)

Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www .iso .org/ patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the meaning of ISO specific terms and expressions related to conformity assessment,
as well as information about ISO’s adherence to the World Trade Organization (WTO) principles in the
Technical Barriers to Trade (TBT) see the following URL: www . i so .org/ iso/ foreword .html.
The committee responsible for this document is ISO/TC 42, Photography.
This third edition cancels and replaces the second edition (ISO 12233:2014), of which it constitutes a
minor revision with changes in Annex D.
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ISO 12233:2017(E)

Introduction
Purpose
The spatial resolution capability is an important attribute of an electronic still-picture camera.
Resolution measurement standards allow users to compare and verify spatial resolution measurements.
This document defines terminology, test charts, and test methods for performing resolution
measurements for analogue and digital electronic still-picture cameras.
Technical background
For consumer digital cameras, the term resolution is often incorrectly interpreted as the number of
addressable photoelements. While there are existing protocols for determining camera pixel counts,
these are not to be confused with the interpretation of resolution as addressed in this document.
Qualitatively, resolution is the ability of a camera to optically capture finely spaced detail, and is usually
reported as a single valued metric. Spatial frequency response (SFR) is a multi-valued metric that
measures contrast loss as a function of spatial frequency. Generally, contrast decreases as a function of
spatial frequency to a level where detail is no longer visually resolved. This limiting frequency value is
the resolution of the camera. A camera’s resolution and its SFR are determined by a number of factors.
These include, but are not limited to, the performance of the camera lens, the number of addressable
photoelements in the optical imaging device, and the electrical circuits in the camera, which can include
image compression and gamma correction functions.
While resolution and SFR are related metrics, their difference lies in their comprehensiveness and utility.
As articulated in this document, resolution is a single frequency parameter that indicates whether the
output signal contains a minimum threshold of detail information for visual detection. In other words,
resolution is the highest spatial frequency that a candidate camera can usefully capture under cited
conditions. It can be very valuable for rapid manufacturing testing, quality control monitoring, or for
providing a simple metric that can be easily understood by end users. The algorithm used to determine
resolution has been tested with visual experiments using human observers and correlates well with
their estimation of high frequency detail loss.
SFR is a numerical description of how contrast is changed by a camera as a function of the spatial
frequencies that describe the contrast. It is very beneficial for engineering, diagnostic, and image
evaluation purposes and serves as an umbrella function from which such metrics as sharpness and
acutance are derived. Often, practitioners will select the spatial frequency associated with a specified
SFR level as a modified non-visual resolution value.
In a departure from the first edition of this document, two SFR measurements are described.
Additionally, the first SFR metrology method, edge-based spatial frequency response, is identical to
that described in the first edition, except that a lower contrast edge is used for the test chart. Regions
of interest (ROI) near slanted vertical and horizontal edges are digitized and used to compute the SFR
levels. The use of a slanted edge allows the edge gradient to be measured at many phases relative to the
image sensor photoelements and to yield a phase-averaged SFR response.
A second sine wave-based SFR metrology technique is introduced in the second edition. Using a sine
wave modulated target in a polar format (e.g. Siemens star), it is intended to provide an SFR response
that is more resilient to ill-behaved spatial frequency signatures introduced by the image content driven
processing of consumer digital cameras. In this sense, it is intended to enable easier interpretation of
SFR levels from such camera sources. Comparing the results of the edge-based SFR and the sine-based
SFR might indicate the extent to which nonlinear processing is used.
The first step in determining visual resolution or SFR is to capture an image of a suitable test chart with
the camera under test. The test chart should include features of sufficiently fine detail and frequency
content such as edges, lines, square waves, or sine wave patterns. The test chart defined in this document
has been designed specifically to evaluate electronic still-picture cameras. It has not necessarily been
designed to evaluate other electronic imaging equipment such as input scanners, CRT displays, hard-
copy printers, or electro-photographic copiers, nor individual components of an electronic still-picture
camera, such as the lens.
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Some of the measurements described in this document are performed using digital analysis techniques.
They are also applicable with the analogue outputs of the camera by digitizing the analogue signals if
there is adequate digitizing equipment.
Methods for measuring SFR and resolution — Selection rationale and guidance
This section is intended to provide more detailed rationale and guidance for the selection of the
different resolution metrology methods presented in this document. While resolution metrology
of analogue optical systems, by way of spatial frequency response, is well established and largely
consistent between methodologies (e.g. sine waves, lines, edges), metrology data for such systems are
normally captured under well-controlled conditions where the required data linearity and spatial
isotropy assumptions hold. Generally, it is not safe to assume these conditions for files from many
digital cameras, even under laboratory capture environments. Exposure and image content dependent
image processing of the digital image file before it is provided as a finished file to the user prevents
this. This processing yields different SFR responses depending on the features in the scene or in the
case of this document, the target. For instance, in-camera edge detection algorithms might specifically
operate on edge features and selectively enhance or blur them based on complex nonlinear decision
rules. Depending on the intent, these algorithms might also be tuned differently for repetitive scene
features such as those found in sine waves or bar pattern targets. Even for constrained camera settings
recommended in this document, these nonlinear operators can yield differing SFR results depending
on the target feature set. Naturally, this causes confusion on which targets to use, either alone or in
combination. Guidelines for selection are offered below.
Edges are common features in naturally occurring scenes. They also tend to act as visual acuity cues by
which image quality is judged and imaging artefacts are manifested. This logic prescribed their use for
SFR metrology in the past and current editions of this document. It is also why edge features are prone
to image processing in many consumer digital cameras: they are visually important. All other imaging
conditions being equal, camera SFRs using different target contrast edge features can be significantly
different, especially with respect to their morphology. This is largely due to nonlinear image processing
operators and would not occur for strictly linear imaging systems. To moderate this behaviour, a lower
contrast slanted edge feature (Figure C.1) was chosen to replace the higher contrast version of the
first edition. This feature choice still allows for acuity-amenable SFR results beyond the half-sampling
frequency and helps prevent nonlinear data clipping that can occur with high contrast target features.
It is also a more reliable rendering of visually important contrast levels in naturally occurring scenes.
Sine wave features have long been the choice for directly calculating SFR of analogue imaging systems
and they are intuitively satisfying. They have been introduced into the second edition based on
experiences from the edge-based approach. Because sine waves transition more slowly than edges,
they are not prone to being identified as edges in embedded camera processors. As such, the ambiguity
that image processing imposes on the SFR can be largely avoided by their use. Alternatively, if the image
processing is influenced by the absence of sharp features, more aggressive processing might be used
by the camera. A sine wave starburst test pattern (Figure 6) is adopted in the second edition. With
the appropriate analysis software, a sine wave-based SFR can be calculated up to the half-sampling
frequency. For the same reasons stated above, the sine wave-based target is also of low contrast and
consistent with that of the edge-based version. An added benefit of the target’s design over other sine
targets is its compactness and bi-directional features.
All experience suggests that there is no single SFR for today’s digital cameras. Even under the strict
capture constraints suggested in this document, the allowable feature sets that most digital cameras
offer prevent such unique characterization. Confusion can be reduced through complete documentation
of the capture conditions and camera setting for which the SFR was calculated. It has been suggested
that comparing edge-based and sine wave-based SFR results under the same capture conditions could
be a good tool in assessing the contribution of spatial image processing in digital cameras.
Finally, at times, a full SFR characterization is simply not required, such as in end of line camera
assembly testing. Alternately, SFR might be an intimidating obstacle to those not trained in its utility.
For those in need of a simple and intuitive space domain approach to resolution using repeating line
patterns, a visual resolution metric is also provided in this third edition of this document.
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With such a variety of methods available for measuring resolution, there are bound to be differences
in measured resolution results. To benchmark the likely variations, the committee has published the
results of a pilot study using all of the proposed techniques and how they relate to each other. These
results are provided in Reference [20].
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INTERNATIONAL STANDARD ISO 12233:2017(E)
Photography — Electronic still picture imaging —
Resolution and spatial frequency responses
1 Scope
This document specifies methods for measuring the resolution and the SFR of electronic still-picture
cameras. It is applicable to the measurement of both monochrome and colour cameras which output
digital data or analogue video signals.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO 14524, Photography — Electronic still-picture cameras — Methods for measuring opto-electronic
conversion functions (OECFs)
3 Terms and definitions
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
addressable photoelements
number of active photoelements in an image sensor (3.11)
Note 1 to entry: This equals the product of the number of active photoelement lines and the number of active
photoelements per line.
3.2
aliasing
output image artefacts that occur in a sampled imaging system (3.23) due to insufficient sampling
Note 1 to entry: These artefacts usually manifest themselves as moiré patterns in repetitive image features or as
jagged stair-stepping at edge transitions.
3.3
cycles per millimetre
cy/mm
spatial frequency unit defined as the number of spatial periods per millimetre
3.4
edge spread function
ESF
normalized spatial signal distribution in the linearized (3.15) output of an imaging system resulting
from imaging a theoretical infinitely sharp edge
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3.5
effectively spectrally neutral
having spectral characteristics which result in a specific imaging system producing the same output as
for a spectrally neutral (3.25) object
3.6
electronic still-picture camera
camera incorporating an image sensor (3.11) that outputs an analogue or digital signal representing a
still picture
Note 1 to entry: This camera may also record or store an analogue or digital signal representing a still picture on
a removable media, such as a memory card or magnetic disc.
3.7
gamma correction
signal processing operation that changes the relative signal levels
Note 1 to entry: Gamma correction is performed, in part, to correct for the nonlinear light output versus signal
input characteristics of the display. The relationship between the light input level and the output signal level,
called the camera opto-electronic conversion function (OECF), provides the gamma correction curve shape for
an image capture device.
Note 2 to entry: The gamma correction is usually an algorithm, lookup table, or circuit which operates separately
on each colour component of an image.
3.8
horizontal resolution
resolution (3.22) value measured in the longer image dimension, corresponding to the horizontal
direction for a “landscape” image orientation, typically using a vertical or near vertical oriented test-
chart feature
3.9
image aspect ratio
ratio of the image width to the image height
3.10
image compression
process that alters the way digital image data are encoded to reduce the size of an image file
3.11
image sensor
electronic device that converts incident electromagnetic radiation into an electronic signal
EXAMPLE Charge coupled device (CCD) array, complementary metal-oxide semiconductor (CMOS) array.
3.12
line pairs per millimetre
lp/mm
spatial frequency unit defined as the number of equal width black and white line pairs per millimetre
3.13
line spread function
LSF
normalized spatial signal distribution in the linearized (3.15) output of an imaging system resulting
from imaging a theoretical infinitely thin line
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3.14
line widths per picture height
LW/PH
spatial frequency unit for specifying the width of a feature on a test chart (3.26) relative to the height of
the active area of the chart
Note 1 to entry: The value in LW/PH indicates the total number of lines of the same width which can be placed
edge to edge within the height of a test target or within the vertical field of view of a camera.
Note 2 to entry: This unit is used whatever the orientation of the “feature” (e.g. line). Specifically, it applies to
horizontal, vertical, and diagonal lines.
EXAMPLE If the height of the active area of the chart equals 20 cm, a black line of 1 000 LW/PH has a width
equal to 20/1 000 cm.
3.15
linearized
digital signal conversion performed to invert the camera opto-electronic conversion function (OECF) to
focal plane exposure or scene luminance
3.16
lines per millimetre
lines/mm
spatial frequency unit defined as the number of equal width black and white lines per millimetre
Note 1 to entry: One line pair per millimetre (lp/mm) is equal to 2 lines/mm.
3.17
modulation
normalized amplitude of signal levels
Note 1 to entry: This is the difference between the minimum and maximum signal levels divided by the average
signal level.
3.18
modulation transfer function
MTF
modulus of the optical transfer function (3.20)
Note 1 to entry: For the MTF to have significance, it is necessary that the imaging system be operating in an
isoplanatic region and in its linear range. Because most electronic still-picture cameras (3.6) provide spatial
colour sampling and nonlinear processing, a meaningful MTF of the camera can only be approximated through
the SFR. See ISO 15529:2010.
3.19
normalized spatial frequency
spatial frequency unit for specifying resolution characteristics of an imaging system in terms of cycles
per pixel rather than in cycles/millimetre or any other unit of length
3.20
optical transfer function
OTF
two-dimensional Fourier transform of the imaging syste
...