Image analysis – Color image processing – Color correction
Reexamination Certificate
1998-10-29
2002-03-19
Mehta, Bhavesh (Department: 2721)
Image analysis
Color image processing
Color correction
C358S518000
Reexamination Certificate
active
06360008
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a method and apparatus for converting color data for a color image device having a first gamut into color data for a color image device having a second gamut.
2. Description of the Related Art
In view of recent advances in the computer technology and recent availability of computers at lower costs, color image devices, i.e., devices which handle color images, are combined in a growing number of applications to process color image data. For example, a color image that is captured by a digital camera or a scanner is displayed on a CRT display unit or printed by a color printer, or displayed on a CRT display unit in one location and on a liquid crystal display unit in another location.
Generally, different color image devices have different color characteristics. Therefore, a color image may be displayed and printed in different colors on different color image devices. For example, a color image displayed on a display unit may be expressed in different colors when printed by a color printer.
In many applications, a color image is generated on the display screen of a color display unit, and then printed by a color printer. Even if a color image looks fine on a display screen, it may lose the brightness of colors or makes the face of a person pale in the color image when printed. Printing companies generate a color image design or layout on a display screen, and prints a color image based on the color image design or layout displayed on the display screen. If the colors of the color image displayed on the display screen differ from those of the printed color image, then it is necessary to generate a color image design or layout again on the display screen.
For this reason, a gamut conversion technology is required to make image colors look the same on all color image devices.
FIG. 18
of the accompanying drawings shows a conventional gamut conversion system, and
FIG. 19
of the accompanying drawings is a chromaticity diagram showing gamuts of color image devices.
FIGS. 20A
,
20
B, and
20
C of the accompanying drawings are illustrative of how the conventional gamut conversion system operates.
As shown in
FIG. 18
, the conventional gamut conversion system includes a color management system (CMS)
94
which converts color data using profiles representing the color characteristics of color image devices, so that the colors will look the same on all the color image devices. Specifically, input color data supplied from a scanner
90
is converted into a standard signal, e.g., L*a*b* signal, by a color correction circuit
91
. Specifically, the color correction circuit
91
converts the input color data supplied into the standard signal using a profile of the scanner
90
.
For displaying the input color data on a display unit
93
, the standard signal from the color correction circuit
91
is converted into an RGB signal by a color correction circuit
92
. Specifically, the color correction circuit
92
converts the standard signal into the RGB signal using a profile of the display unit
93
. For printing the input color data on a printer
96
, the standard signal from the color correction circuit
91
is converted into a YMC signal by a color conversion circuit
95
. Specifically, the color conversion circuit
95
converts the standard signal into the YMC signal using a profile of the printer
96
.
To obtain the profile of a color image device, sample colors are entered into the color image device and displayed or printed thereby. The sample colors and the displayed or printed colors are associated with each other, thus producing the profile of the color image device.
However, there are some colors that cannot be confirmed by the profile thus produced. For example, the colors displayed on the display unit include colors that cannot be printed on the printer, and the colors that can be reproduced by the printer include colors that cannot be displayed on the display unit.
FIG. 19
illustrates gamuts of various color image devices represented in an XYZ color space. As shown in
FIG. 19
, the ranges of colors they are called “gamut” that can be reproduced by different color image devices, which include a display unit and a printer, are relatively small and different from each other. For example, a clear and bright green can be displayed on the display unit, but cannot be printed by the printer. A dark blue and a deep green cannot be distinguished from black on the display unit, though they can be printed by the printer. This is because the display unit and the printer have different gamuts that can be reproduced thereby.
Colors cannot physically accurately be converted between color image devices which have different gamuts. Stated otherwise, those colors which cannot be reproduced by a color image device cannot be converted into colors for reproduction by another color image device. Therefore, it is necessary to convert gamuts between different color image devices for allowing a color reproduced by the color image devices to be visually perceived as the same color. Such a gamut conversion is also referred to a gamut compression because it is often used to convert a wide gamut for a display unit into a narrow gamut for a printer.
FIGS. 20A
,
20
B, and
20
C illustrate how the conventional gamut conversion system operates. In
FIGS. 20A
,
20
B, and
20
C, regions enclosed by solid lines indicate the gamut of a printer, white dots indicate pixel colors of an image, and black dots indicate colors outputted by the printer.
For a natural image, it is preferable to preserve a balance of the gradations of image data and the colors of the entire image, rather than the accuracy of individual colors of the image. To this end, as shown in
FIG. 20A
, the entire image data that is involved is uniformly reduced such that the overall gamut of a source device, e.g., a display unit, will be contained in the gamut of a destination device, e.g., a printer. The data reduction ratio is varied depending on the magnitude of saturation. For example, if the saturation of a color is small, then the color data is not essentially reduced. As the saturation becomes larger, the data reduction ratio is increased, so that the maximum saturation will enter the gamut of the destination device.
For applications of graphs and computer graphics, the clearness of colors is preserved. As shown in
FIG. 20B
, the saturations of colors are preserved whereas the lightnesses thereof may be changed.
For accurately preserving colors, as shown in
FIG. 20C
, those color data of a source device which fall within the gamut of a destination device are not converted, and the other color data of the source device which fall outside the gamut of the destination device are converted to closest color data in the gamut of the destination device. This process is called gamut mapping.
As described above, the conventional gamut mapping system processes the entire gamut to convert color data of the source device into color data of the destination device.
There has also been known a gamut mapping process for classifying gamuts of input and output image devices into categorical colors, and converting colors in the same gamut. See, for example, “Categorical Color Mapping for Gamut Mapping” presented in 5th Color Imaging Conference held by IS & T and SID, Nov. 18, 1997. According to this gamut mapping process, color category regions are assumed to be three-dimensional ellipses, and a category to which a color belongs is determined by the Mahalabinos Distance from the center of each of the regions to determine a converted color.
FIG. 21
of the accompanying drawings illustrates problems of the conventional gamut mapping process.
The conventional gamut mapping system operates simply to reduce a gamut, and does not ensure that an image of converted colors will look like an image of original colors to the human eye, e.g., depends on the human visual perception. If the overall gamut is reduced, the colors visually perceived by the human eye are altered due to the
Mori Masahiro
Suzuki Shoji
Uchikawa Keiji
Armstrong Westerman & Hattori, LLP
Bayat Ali
Fujitsu Limited
Mehta Bhavesh
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