Image analysis – Color image processing – Color correction
Reexamination Certificate
1999-10-04
2003-05-06
Tran, Phuoc (Department: 2621)
Image analysis
Color image processing
Color correction
C358S001900, C358S518000
Reexamination Certificate
active
06560358
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to a color reproduction technique for color images among different color image devices, such as a color scanner, a color monitor, a color printer etc. More particularly, it relates to a color matching method and apparatus required for converting an optional color in an originating color space to that of a target color space, in meeting with the chromatic adaptation state of the human visual system, as the color appearance correspondence is maintained between different color systems having different white references.
BACKGROUND OF THE INVENTION
When a color image displayed on a monitor such as a cathode-ray tube (CRT) monitor for color reproduction between different color image devices is to be output to a color printer, color reproduction frequently presents a problem. In general, the correlated color temperature of the reference white, set as a default reference, in most CRT monitors, is set to approximately 9000 K. In the case of a printer, on the other hand, the color when illuminated with D50 (correlated color temperature: 5000 K), as the standard light source for color evaluation for printing, is evaluated. In short, for color reproduction between monitor and printer, the color displayed on a monitor set to the standard white of 9000 K needs to be compared to the color of the printer output illuminated with the standard light source of 5000 K. However, even insofar as only the white is concerned, the appearance of the color with the correlated color temperature of 9000 K perceived by us differs from that with the correlated color temperature of 5000 K.
For sensibly realizing this difference between the two whites, two monitors are provided, with one of them being set to a standard white with a correlated color temperature of 9000 K, with the remaining monitor being set to a standard white with a correlated color temperature of 5000 K. If the respective whites are displayed on the two monitors and compared to each other, the difference in the color appearance can be perceived easily. If, in the state where the user's eye is completely adapted to the monitor of the standard white with the correlated color temperature of 9000 K, the user sees the white displayed on the monitor of the standard white with the correlated color temperature of 5000 K, the latter is perceived as being the yellowish color clearly different from the white. The reverse is also true, that is, if the user's eye is completely adapted to the monitor of the standard white with the correlated color temperature of 5000 K, the user sees the white with the correlated color temperature of 9000 K as being palish (bluish) white.
However, if, in an environment that can control the ambient light, such as in a darkroom and, with a partition placed between both eyes, the monitor of 9000 K and that of 5000 K continue to be viewed with left and right eyes, respectively, the color appearance of the two whites gradually becomes similar (approach each other) due to progressive chromatic adaptation of both eyes. That is, since the color appearances of the two whites differ due to the state of our chromatic adaptation, such color conversion which takes our chromatic adaptation into account is indispensable in order to realize color coincidence between color image devices having different reference whites.
As a color conversion method, which takes the human chromatic adaptation into account, the von Kries model is well-known. This conversion method is shown in FIG.
10
. According to this method, the chromatic adaptation is carried out based on the change in the RGB spectral sensitivity in the human visual system such that the RGB spectral sensitivity is upon change in illumination, changed in its sensitivity balance without changes in shape of the spectral curves so as to bring the two whites into coincidence. Assume RGB values of the illumination
1
be (R
0
, G
0
, B
0
), the RGB values of an object (article) in illumination
1
be (R, G, B), and RGB values of illumination
2
be (R
0
′, G
0
′, B
0
′), with RGB values of the same object under illumination
2
being (R′, G′, B′), the tri-color sensual quantities of the visual system of the object color are expressed by: R/R
0
, G/G
0
, B/B
0
, R′/R
0
′, G′/G
0
′, B′/B
0
′. In order for the color appearance of the object to be coincident under the illumination
1
and under the illumination
2
, it suffices if the above-mentioned tri-color sensual quantities are coincident, as shown below:
[
R
/
R
0
G
/
G
0
B
/
B
0
]
=
[
R
′
/
R
0
′
G
′
/
G
0
′
B
′
/
B
0
′
]
(
1
)
[
1
/
R
0
0
0
0
1
/
G
0
0
0
0
1
/
B
0
]
&AutoLeftMatch;
[
R
&AutoLeftMatch;
G
B
]
=
[
1
/
R
0
′
0
0
0
1
/
G
0
′
0
0
0
1
/
B
0
′
]
[
R
′
G
′
B
′
]
(
2
)
The RGB values can be obtained by linear transformation of tristimulus values X, Y, Z:
[
R
G
B
]
=
M
[
X
Y
Z
]
,
[
R
′
G
′
B
′
]
=
M
[
X
′
Y
′
Z
′
]
(
3
)
It is noted that R
0
, G
0
, B
0
, R
0
′, G
0
′, B
0
′ in the above formula (1) may be obtained by substituting tristimulus values (X
0
, Y
0
, Z
0
), (X
0
′, Y
0
′, Z
0
′) of the illumination
1
and the illumination
2
shown in
FIG. 11
into formula (3).
In the XYZ→CRGB transformation matrix M of formula (3), Pitt's matrix or Estevez' matrix may be used.
By substituting equation (3) into equation (2), the following von Kries chromatic adaptation prediction formula is obtained:
[
X
′
Y
′
Z
′
]
=
M
-
1
DM
[
X
Y
Z
]
(
4
)
In the above formula (4),
D
=
[
R0
′
/
R0
0
0
0
G0
′
/
G0
0
0
0
B0
′
/
B0
]
(
5
)
It is seen from above that the color on the reproducing side corresponding to tristimulus values (X, Y, Z) of the input color on the original side in an observing booth shown in
FIG. 11
can be calculated from the von Kries chromatic adaptation prediction formula (4).
Nayatani et al proposed a chromatic adaptation model combining the linear process in which the von Kries chromatic adaptation model is valid and the non-linear process in which an exponent varies responsive to the adaptation level. This chromatic adaptation model was recommended by CIE in 1986 as a chromatic adaptation prediction formula. This chromatic adaptation prediction formula is hereinafter explained.
First, tristimulus values X, Y, Z of the input color on the original side in
FIG. 11
are transformed, by using Estevez' matrix, into basic stimulus values RGB in accordance with the following formula (6):
[
R
G
B
]
=
[
0.40024
0.70760
-
0.08081
-
0.22639
1.16532
0.04570
0.0
0.0
0.91822
]
[
X
Y
Z
]
(
6
)
From the basic stimulus values RGB of the input color, basic stimulus values R′, G′, B′ of the corresponding colors are calculated.
R′=(100&rgr;
0
′&xgr;′+1){(R+1)/(100&rgr;
0
&xgr;+1)}
Pr
−1
G′=(100&rgr;
0
′&eegr;′+1){(G+1)/(100&rgr;
0
&eegr;+1)}
Pg
−1
R′=(100&rgr;
0
′&zgr;′+1){(B+1)/(100&rgr;
0
&zgr;+1)}
Pb
−1 (7)
For the corresponding colors R′, G′, B′, the formula (6) is inverse transformed (as shown by the following formula (8)) to calculate tristimulus values X′, Y′, Z′ of the corresponding color:
[
X
′
Y
′
Z
′
]
=
[
1.85995
-
1.12939
0.21990
0.36119
0.63881
0.0
0.0
0.0
1.08906
]
[
R
′
G
′
B
′
]
(
8
)
In the above formula (7), &rgr;o, &rgr;o′ denote reflectances of the surrounding environments on the original and reproducing sides, respectively, with 0.2≦&rgr;o≦0.1 and 0.2≦
Foley & Lardner
NEC Corporation
Sherali Ishrat
Tran Phuoc
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