ISO/IEC 24790:2017/Amd 1:2022

INTERNATIONAL ISO/IEC
STANDARD 24790
First edition
2017-02
AMENDMENT 1
2022-10
Information technology — Office
equipment — Measurement of image
quality attributes for hardcopy output
— Monochrome text and graphic
images
AMENDMENT 1
Technologies de l'information — Équipement de bureau — Mesurage
des attributs de qualité d'image — Texte monochrome et images
graphiques
AMENDEMENT 1
Reference number
ISO/IEC 24790:2017/Amd. 1:2022(E)
© ISO/IEC 2022
ISO/IEC 24790:2017/Amd. 1:2022(E)
© ISO/IEC 2022
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ii
© ISO/IEC 2022 – All rights reserved

ISO/IEC 24790:2017/Amd. 1:2022(E)
Foreword
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iii
© ISO/IEC 2022 – All rights reserved

ISO/IEC 24790:2017/Amd. 1:2022(E)
Information technology — Office equipment —
Measurement of image quality attributes for hardcopy
output — Monochrome text and graphic images
AMENDMENT 1
Clause 2
Add the following two references in Clause 2:
ISO 13655, Graphic technology — Spectral measurement and colorimetric computation for graphic arts
images
IEC 61966 2-1, Multimedia systems and equipment — Colour measurement and management — Part 2-1:
Colour management — Default RGB colour space — sRGB

5.2.2
Replace the first paragraph as follows:
In order to determine the inner boundary, the maximum reflectance factor (R ) is determined by
max
averaging the R values measured in the area selected by the user as background area and the minimum
v
reflectance factor (R ) is determined by averaging the R values measured in the area selected by the
min v
user as image area, in which the visual reflectance R values can be obtained via OECF conversion of
v
the measured data in G channel as specified in 6.2.1. Then, from R and R , R is computed and the
max min 10
inner boundary edge is determined.

5.2.3
Replace b) as follows:
b) Measure the the visual reflectance R (x, y) wholly within the ROI.
v
Replace Y(x, y) in Fomula (1) to R (x, y)
v
5.2.4
Replace b) as follows:
b) Measure the the visual reflectance R (x, y) wholly within the ROI.
v
Replace Y(x, y) in Fomula (2) to R (x, y)
v
5.2.5.2
© ISO/IEC 2022 – All rights reserved

ISO/IEC 24790:2017/Amd. 1:2022(E)
Replace b), c), g) and j) as follows:
b) Measure scanner outputs in terms of R (x, y), G (x, y) and B (x, y) of 360 000 (600×600) pixels,
S S S
evenly-spaced and non-overlapping elements within the ROI, respectively. Then, convert those
values in R (x, y), G (x, y) and B (x, y) to the linearized values in R (x, y), G (x, y) and B (x, y) as
S S S L L L
described in 6.2.3.
c) Convert the values in R (x, y), G (x, y) and B (x, y) to the values in CIE Y (x, y) by using Formula (3),
L L L
derived by converting the matrix in page 4 in “https:// www .color .org/ chardata/ rgb/ sRGB .pdf”,
0,5
and calculate the positive values of the square root of CIE Y (x, y) (Y (x, y) ) as input data for the
wavelet transform:
Yx(),,yR=0 2224 ()xy,,+0 7169Gx(),,yB+0 0606 ()xy, (3)
DL50 LL
when Yx,%yY≥ 100 patchofconformancechart ,
() ()
DD50 50
Yx(),%yY= ()100 patchofconformancechart
DD50 50
when Yx(),%yY< ()100 patchofconformancechart .
DD50 50
Mottle scores calculated by using the method in this document do not show a good agreement
with subjective scores when test patches include noise with CIE Y values lower than the
colourimetrically measured CIE Y value for the solid patch in the confomance test chart. A clipping
procesure in Formula (6) to replace such low CIE Y values to the measured CIE Y value for the solid
patch noticeably improved this issue. Considering consistency throughout this document, not
only Formula (6) for mottle measurement, but also Formula (3) for graininess measurement and
Formula (11) for banding measurement, adopt the same formula with this clipping procedure.
0,5
g) Apply the inverse wavelet transform to get the filtered image Y’ (x, y) .
j) Compute the variance v of each tile of i-th row and j-th column [Formula (4) assumes a total of
i,j
60×60 = 3 600 pixels per tile]:
60 60
05, 05,
 
′′
vY= ()xy, −Y (4)
ij,,ij ij,
∑∑
 
 
60×−60 1
xy==1 1
5.2.6.2
Replace b), c), g) and j) as follows:
b) Measure scanner outputs in terms of R (x, y), G (x, y) and B (x, y) of 14 400 (1 200×1 200) pixels,
S S S
evenly-spaced and non-overlapping elements within the ROI, respectively. Then, convert those
values in R (x, y), G (x, y) and B (x, y) to the linearized values in R (x, y), G (x, y) and B (x, y) as
S S S L L L
described in 6.2.3.
c) Convert the three optical reflectance factors to a single CIE Y (x, y), using Formula (6), and calculate
0,5
the positive values of the square root of CIE Y (x, y) (Y (x, y) ) as input data for the wavelet
transform:
Yx,,yR=0 2224 xy,,+0 7169Gx,,yB+0 0606 xy, (6)
() () () ()
DL50 LL
when ,Yx(),%yY≥ ()100 patchofconformancechart ,
DD50 50
Yx,%yY= 100 patchofconformancechart
() ()
DD50 50
when Yx(),%yY< ()100 patchofconformancechart
DD50 50
0,5
g) Apply the inverse wavelet transform to ge
...