SIST ISO 12233:2025

International
Standard
ISO 12233
Fifth edition
Digital cameras — Resolution and
2024-09
spatial frequency responses
Caméras numériques — Résolution et réponses en fréquence
spatiale
Reference number
© ISO 2024
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ii
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 .6
4.3 Camera focusing .6
4.4 Camera settings .6
4.5 White balance .7
4.6 Luminance and colour measurements .7
4.7 Gamma correction .7
5 Visual resolution measurement . 7
5.1 General .7
5.2 Test chart .8
5.2.1 General .8
5.2.2 Material.8
5.2.3 Size .8
5.2.4 Test patterns .8
5.2.5 Test pattern modulation .8
5.2.6 Positional tolerance .8
5.3 Rules of judgement for visual observation .9
5.3.1 Rules of judgement .9
5.3.2 Example of a correct visual judgement .9
6 Edge-based spatial frequency response (e-SFR) . 10
6.1 General .10
6.2 Methodology . 13
7 Sinewave-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 . 15
8.2.3 Representative presentation . 15
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 chart .18
Annex B (informative) Visual resolution measurement software .24
Annex C (informative) Edge SFR test chart .30
Annex D (normative) Edge spatial frequency response (e-SFR) algorithm .32
Annex E (normative) Sine wave star test chart .38
Annex F (normative) Sine wave spatial frequency response (s-SFR) analysis algorithm . 41
Annex G (informative) Colour-filtered resolution measurements .46
Annex H (informative) Units and summary metrics .48

iii
Annex I (informative) Original test chart defined in ISO 12233:2000 .51
Annex J (informative) Non-uniform illumination compensation for some applications .55
Annex K (informative) Derivation of correction functions . 61
Annex L (informative) Acutance calculation .65
Annex M (informative) Matlab function for computing e-SFR .68
Bibliography .73

iv
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
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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 document 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).
ISO draws attention to the possibility that the implementation of this document may involve the use of (a)
patent(s). ISO takes no position concerning the evidence, validity or applicability of any claimed patent
rights in respect thereof. As of the date of publication of this document, ISO had not received notice of (a)
patent(s) which may be required to implement this document. However, implementers are cautioned that
this may not represent the latest information, which may be obtained from the patent database available at
www.iso.org/patents. ISO shall not be held responsible for identifying any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, 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 www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 42, Photography.
This fifth edition cancels and replaces the fourth edition (ISO 12233:2023), which was revised.
The main changes are as follows:
— The subtitle of Annex D has been corrected to state that Annex D is normative (since it was erroneously
th
listed as informative in the 4 edition), and the reference to Annex D in 6.1 has been clarified to state
that Annex D shall be used to implement the e-SFR algorithm.
— In Annex D, the name of the function “OECF” in Formula (D.1) has been changed to “inverse OECF”, and
the description of the equation has been clarified.
— The term “electronic still picture imaging” in the title and the term “electronic still-picture cameras” in
the scope have been changed to “digital cameras”, to match current industry terminology.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.

v
Introduction
0.1  Purpose
The spatial resolution capability is an important attribute of a digital camera. Resolution measurement
standards allow users to compare and verify spatial resolution measurements, as described in Reference [15].
This document defines terminology, test charts, and test methods for performing resolution measurements
for digital cameras.
0.2  Technical background
Because digital cameras are sampled imaging systems, 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. SFR is similar to the optical transfer function (OTF) and
the modulation transfer function (MTF) which are defined for linear systems (see References [2] and [4]).
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 several 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 camera image processing,
which can include image sharpening, 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 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 spatial frequencies.
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 were described in the second
edition. The first SFR metrology method, an edge-based spatial frequency response (e-SFR), was identical to
that described in the first edition, except that a lower contrast edge was used for the test chart. In the fourth
edition, the test chart used for the e-SFR measurement was updated, to enable measurements in diagonal
directions. Regions of interest (ROIs) near slanted vertical, diagonal, and horizontal edges are digitized and
used to compute the e-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 e-SFR response.
A second sine wave based SFR (s-SFR) metrology method was 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 some consumer digital cameras. In this sense, it is intended to enable easier interpretation of
SFR levels from such cameras. 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 charts defined in this document have
been designed specifically to evaluate digital cameras. They have 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 a digital camera, such as the lens.

vi
The measurements described in this document are performed using digital analysis techniques.
0.3  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 test chart. 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 using the constrained camera settings recommended in this document, these nonlinear operations can
yield differing SFR results depending on the test chart. Naturally, this causes confusion on which test charts
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 test chart contrast edge features can be significantly different,
especially with respect to their morphology. This is largely due to nonlinear image processing operations
and would not occur for strictly linear imaging systems. To moderate this behaviour, in the second edition
of ISO 12233, a lower contrast slanted edge feature was chosen to replace the higher contrast version of
the first edition. In the fourth edition, the edge feature was further modified to enable measurements in
diagonal directions. This “slanted star” 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. However, data clipping is still possible when using a test chart having a large edge reflectance ratio
and/or when the captured image of the test chart is significantly overexposed. This data clipping can cause
the measured e-SFR values to be overstated.
Sine wave features have long been the choice for directly calculating the MTF of analogue imaging systems
and they are intuitively satisfying. They were introduced in 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. Using the sine
wave starburst test pattern (see Figure 6) adopted in the second edition along 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.
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 settings 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 can be a good tool in
assessing the contribution of spatial image processing in digital cameras. See Reference [15].
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 measurement is also provided in this document.

vii
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 several measurement methods and how they relate to each other. These results are
provided in Reference [19].
viii
International Standard ISO 12233:2024(en)
Digital cameras — Resolution and spatial frequency
responses
1 Scope
This document specifies methods for measuring the resolution and the spatial frequency response (SFR) of
digital cameras. It is applicable to the measurement of both monochrome and colour cameras which output
digital data.
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:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
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 (3.31) 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
digital camera
device which incorporates an image sensor (3.11) and produces a digital signal representing a picture
Note 1 to entry: A digital camera is typically a portable, hand-held device. The digital signal is usually recorded on a
removable or an internal memory.

3.5
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
3.6
effectively spectrally neutral
having spectral characteristics which result in a specific imaging system producing the same output as for a
spectrally neutral (3.26) object
Note 1 to entry: Effectively spectrally neutral objects may have spectral reflectances or transmittances that vary with
wavelength (are not constant) so long as they produce a neutral response using the specified imaging system. Objects
that are effectively spectrally neutral with respect to one imaging system will not necessarily be so with respect to
another imaging system.
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 logarithm (base 10) of 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 (3.23) value(s) 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

3.14
line widths per picture height
LW/PH
spatial frequency unit for specifying the width of a feature on a test chart (3.27) 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
L/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 L/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 digital cameras (3.4) are sampled imaging systems (3.31) which use spatial colour
sampling and typically include nonlinear processing, a meaningful MTF of the camera can only be approximated
[4]
through the SFR. See ISO 15529 .
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 system's point spread function (3.21)
Note 1 to entry: For the OTF to have significance, it is necessary that the imaging system be operating in an isoplanatic
region and in its linear range. The OTF is a complex function whose modulus has unity value at zero spatial frequency
[2]
See ISO 9334 . Because digital cameras (3.4) are sampled imaging systems (3.31) which use spatial colour sampling and
typically include nonlinear processing, a meaningful OTF of the camera can only be approximated through the SFR.
3.21
point spread function
normalized spatial signal distribution in the linearized (3.15) output of an imaging system resulting from
imaging a theoretical infinitely small point source

3.22
reflectance
ratio of the luminous flux reflected from the surface of the chart to the luminous flux incident on the surface
of the chart. The reflectance should be integrated over the range of wavelengths from at least 400 to 700 nm.
Note 1 to entry: If the camera under test is sensitive to an extended spectral range (e.g. near Infrared wavelengths),
the spectral range over which the reflectance is integrated needs to include this extended spectral range.
3.23
resolution
measure of the ability of a camera system, or a component of a camera system, to depict picture detail
Note 1 to entry: The limiting resolution, visual resolution, e-SFR and s-SFR are examples of resolution measurements.
3.24
SFR10 frequency
Spatial frequency where the SFR value drops to 10 %
3.25
spatial frequency response
SFR
relative amplitude response of an imaging system as a function of input spatial frequency
Note 1 to entry: The SFR is normally represented by a curve of the output response to an input sinusoidal spatial
luminance distribution of unit amplitude, over a range of spatial frequencies. The SFR is divided by its value at the
spatial frequency of 0 as normalization to yield a value of 1,0 at a spatial frequency of 0.
3.25.1
edge-based spatial frequency response
e-SFR
measured amplitude response of an imaging system to a slanted-edge input
Note 1 to entry: Measurement of e-SFR is as defined in Clause 6.
3.25.2
sinewave-based spatial frequency response
s-SFR
measured amplitude response of an imaging system to a range of sine wave inputs
Note 1 to entry: Measurement of s-SFR is as defined in Clause 7.
3.26
spectrally neutral
exhibiting reflective or transmissive characteristics which are constant over the wavelength range of
interest
3.27
test chart
arrangement of test patterns (3.28) designed to test particular aspects of an imaging system
3.28
test pattern
specified arrangement of spectral reflectance or transmittance characteristics used in measuring an image
quality attribute
3.28.1
bi-tonal pattern
pattern that is spectrally neutral (3.26) or effectively spectrally neutral (3.5), and consists exclusively of two
reflectance or transmittance values in a prescribed spatial arrangement
Note 1 to entry: Bi-tonal patterns are typically used to measure resolution (3.23) by using the visual resolution method.

3.28.2
hyperbolic wedge test pattern
bi-tonal pattern (3.28.1) that varies continuously and linearly with spatial frequency
Note 1 to entry: A bi-tonal hyperbolic wedge test pattern is used to measure resolution (3.23) by using the visual
resolution method in this document.
3.29
vertical resolution
resolution (3.23) value measured in the shorter image dimension, corresponding to the vertical direction for
a "landscape" image orientation, typically using a horizontal or near horizontal oriented test-chart feature
3.30
visual resolution
spatial frequency at which all of the individual black and white lines of a test pattern (3.28) frequency can no
longer be distinguished by a human observer
Note 1 to entry: This presumes the features are reproduced on a display or print.
3.31
sampled imaging system
imaging system or device which generates an image signal by sampling an image at an array of discrete
points, or along a set of discrete lines, rather than a continuum of points
Note 1 to entry: The sampling at each point is done using a finite-size sampling aperture or area.
4 Test conditions
4.1 Test chart illumination
The luminance of the test chart shall be sufficient to provide an acceptable camera output signal level. The
test chart (key item 2) shall be uniformly illuminated as shown in Figure 1, so that the illuminance at any
position within the chart is within ±10 % of the illuminance in the centre of the chart. The illumination
sources (key item 3) should be baffled (key item 5) to prevent direct illumination of the camera lens by
the illumination sources. The area surrounding the test chart (key item 1) should be of low reflectance to
minimize flare light. The test chart should be shielded from any reflected light. The illuminated test chart
shall be effectively spectrally neutral within the visible wavelengths.

Key
1 matte black wall or black surround
2 test chart
3 illumination sources
4 digital camera
5 baffles to prevent direct illumination of the camera lens
6 distance is adjusted to frame test chart
Figure 1 — Test chart illumination method
4.2 Camera framing and lens focal length setting
The camera shall be positioned to properly frame the test target. The vertical framing arrows are used to
adjust the magnification and the horizontal arrows are used to centre the target horizontally. The tips of
the centre vertical black framing arrows should be fully visible, and the tips of the centre white framing
arrows should not be visible. The test chart shall be oriented so that the horizontal edge of the chart is
approximately parallel to the horizontal camera frame line. The approximate distance between the camera
and the test chart should be reported along with the measurement results.
4.3 Camera focusing
The camera focus should be set either by using the camera autofocusing system, or by performing a series
of image captures at varying focus settings and selecting the focus setting that provides the highest average
modulation level at a spatial frequency approximately 1/4 the camera Nyquist frequency. (In the case of a
colour camera, the Nyquist frequency is of the conceptual monochrome image sensor without colour filter
array). Auto focus accuracy is often limited, and this limitation might have an impact on the results.
4.4 Camera settings
The camera lens aperture (if adjustable) and the exposure time should be adjusted to provide a near
maximum signal level from the white test target areas. The settings shall not result in signal clipping in
either the white or black areas of the test chart, or regions of edge transitions.
Most cameras include image compression, to reduce the size of the image files and allow more images to
be stored. The use of image compression can significantly affect resolution measurements. Some cameras
have settings that allow the camera to operate in various compression or resolution modes. The values of all
camera settings that might affect the results of the measurement, including lens focal length, aperture and

image quality (i.e. recording pixel number or compression) mode (if adjustable), shall be reported along with
the measurement results.
Some cameras include adaptive tone mapping, which means that different parts of the image may have
different OECFs (opto-electronic conversion functions). Because the use of adaptive tone mapping
might affect resolution measurements, it should be turned off, if possible, when performing resolution
measurements. Since adaptive tone mapping is often used when the camera operates in HDR (high dynamic
range) mode, the HDR mode should be turned off, if possible, when performing resolution measurements.
Multiple SFR measurements may be reported for different camera settings, including a setting that uses the
maximum lens aperture size (minimum f-number) and maximum camera gain.
4.5 White balance
For a colour camera, the camera white balance should be adjusted, if possible, to provide proper white
balance [equal red, green, and blue (RGB) signal levels] for the illumination light source, as specified in
ISO 14524.
4.6 Luminance and colour measurements
Resolution measurements are normally performed on the camera luminance signal. For colour cameras
that do not provide a luminance output signal, a luminance signal should be formed from an appropriate
combination of the colour records, rather than from a single channel such as green. See ISO 12232 for the
luminance signal calculation. Colour-filtered resolution measurements can be performed as described in
Annex G.
4.7 Gamma correction
The signal representing the image from the camera will probably be a nonlinear function of the scene
luminance values. Since the SFR measurement is defined on a linearized output signal and such a nonlinear
response might affect SFR values, the signal shall be linearized before the data analysis is performed.
Linearization is accomplished by applying the inverse of the camera OECF to the output signal via a lookup
table or appropriate formula. The measurement of the OECF shall be as specified in ISO 14524, using OECF
patches integrated on the resolution test chart (as shown in Figures 4a, 4b, and 6) or using the standard
reflection camera OECF test chart specified in ISO 14524.
5 Visual resolution measurement
5.1 General
The visual resolution is the maximum value of the spatial frequency in LW/PH within a test pattern that is
able to be visually distinguished. A black and white hyperbolic wedge is used as the test pattern.
Because of aliasing artefacts in the high frequencies, actual resolution judgements can be ambiguous. The
objective visual resolution method described herein using a hyperbolic wedge test pattern gives more stable
results by adopting the visual judgement rules described in 5.3 which have been used by a highly skilled
observer.
It can be measured analytically using computer analysis of captured images, as defined in Annex B. The
computer analysis method is intended to correlate with the subjective judgement of visual resolution made
by a skilled observer but is likely to yield a more consistent and objective result compared to actual visual
judgements. However, if there is a discrepancy between the results of the computer analysis method and the
judgement of a human observer, the judgement of the human observer takes priority.

5.2 Test chart
5.2.1 General
The preferred test chart for measuring the visual resolution is the CIPA resolution chart, which is shown in
Figure 2 and specified in Annex A.
The chart shown in Figure 2 is designed to measure cameras having a resolution of less than 2 500 LW/PH.
Nevertheless, it is possible to use the chart to measure the resolution of a digital camera having a resolution
greater than 2 500 LW/PH. This is accomplished by adjusting the camera to target distance, or the focal
length of the camera lens, so that the test chart active area fills only a portion of the vertical image height
of the camera. This fraction is then measured in the digital image, by dividing the number of image lines in
the camera image by the number of lines in the active chart area. The values of all test chart features, in LW/
PH, printed on the chart or specified in this document, are multiplied by this fraction, to obtain their correct
values. For example, if the chart fills 1/2 of the vertical image height of the camera, then the multiplication
factor is equal to 2 and a feature labelled as 2 000 LW/PH on the chart corresponds to 4 000 LW/PH using
this chart framing.
NOTE Figure 2 includes an improved version of the test chart features originally defined in ISO 12233:2000. This
original test chart defined in ISO 12233:2000 is described in Annex I.
5.2.2 Material
The test chart may be either a transparency that is rear illuminated or a reflection test card that is front
illuminated. A reflection
...