Image analysis – Color image processing – Color correction
Reexamination Certificate
1999-04-22
2002-06-04
Patel, Jayanti K. (Department: 2721)
Image analysis
Color image processing
Color correction
C345S590000, C358S518000
Reexamination Certificate
active
06400843
ABSTRACT:
TECHNICAL FIELD
The present invention relates generally to color image reproduction systems, and relates more particularly to features that improve color matching between original color images and reproductions of those images.
BACKGROUND ART
Color image reproduction systems typically include an input device for obtaining a representation of an original image, an output device for generating a replica of the image, and a controlling device that processes signals received from the input device to generate new signals sent to the output device to produce the replica, which preferably is a high-fidelity reproduction of the original image. The controlling device may be implemented by a general-purpose computer with appropriate software and/or hardware for peripheral control and signal processing. Examples of input devices include hand held, flatbed and sheet-fed optical scanners and digital cameras for sensing an original image, and a wide range of software and devices for creating an original image. Examples of output devices include ink jet, laser and photolithography printers, electrostatic, flatbed and drum plotters, and video displays such as cathode ray tubes (CRT), thin-film-transistor (TFT) and liquid crystal display (LCD) panels.
Generally, input and output devices use signals that represent the colors as coordinates of points in some device-dependent color space (DDCS). These color spaces may be chosen to provide a convenient expression of color coordinates according to the color-sensing or color-generating process of the particular device. The term “color space” refers to an N-dimensional space in which each point corresponds to a particular color.
One example of a three-dimensional color space is an RGB space in which point coordinates specify particular amounts of red (R), green (G) and blue (B) colorant that additively combine to represent a specific color. The operation of many scanners and video display devices may be conveniently controlled by signals that are specified in an RGB space. One example of a four-dimensional color space is a CMYK space in which point coordinates specify particular amounts of cyan (C), magenta (M), yellow (Y) and black (K) colorant that subtractively combine to represent a specific color. Another example of a three-dimensional color space is a CMY space. The operation of many ink jet and laser printers may be conveniently controlled by signals that are specified in CMYK space or CMY space. Other color spaces that are related to particular devices are also known.
Practical devices are generally capable of sensing or reproducing only a portion of the colors that can be discerned by a human observer. A device “gamut” refers to the colors that can be sensed or reproduced by a particular device. For example, the gamut of a particular scanner refers to the colors that can be sensed by that scanner and the gamut of a particular printer refers to the colors that can be reproduced or printed by that printer.
A scanner gamut is determined by a variety of factors including the spectral response of the optical sensors, the spectral characteristics of color filters, spectral characteristics of the illumination source and the resolution and linearity of analog-to-digital converters.
A printer gamut is determined by a variety of factors including spectral characteristics of colorants such as ink, spectral and porosity characteristics of media such as paper, resolution or dots-per-inch of the printed image, half-toning methods and use of dithering, if any.
A video display gamut is determined by a variety of factors including spectral characteristics of the light emitting material, type of display device, resolution of pixels or video lines, and excitation voltage.
Although it is possible in principle to construct a color image reproduction system by merely connecting an output device directly to an input device, the results would not usually be satisfactory because the DDCS for the input and output devices are generally not the same. A “color-space transformation” can account for different color spaces by mapping the coordinates of colors in one color space to the coordinates of corresponding colors in the other color space. These transformations may be provided by the controlling device, mentioned above. For example, a controlling device performing a color-space transformation that maps color coordinates from the RGB space of a particular scanner into the CMYK space of a particular printer could be used to couple that printer to the scanner by converting the scanner RGB signals into the printer CMYK signals.
Even if the differences between color spaces are accounted for by a color-space transformation, however, the fidelity of the reproduced image as compared to an original image would probably be very poor because the gamut of the input device generally is not co-extensive with the gamut of the output device. For example, the color-space coordinates representing “out-of-gamut” colors that are not in the output-device gamut cannot be reproduced. Instead, some “in-gamut” color within the gamut of the output device must be substituted for each out-of-gamut color. A “gamut-mapping transformation” may be used to substitute an in-gamut color for an out-of-gamut color by mapping the out-of-gamut colors to the substitute colors. The gamut-mapping transformation may also be provided by the controlling device, mentioned above.
In many color image reproduction systems, the gamut-mapping and color-space transformations are integrated and cannot be easily isolated. They may be implemented collectively by one or more transformations according to the needs of the application in which they are used. For ease of discussion, the term “calibration transformation” is used herein to refer to both types of transformations.
Known color image reproduction systems generally implement calibration transformations that map colors between an input-DDCS and an output-DDCS according to only the two transformations described above: (1) a color-space transformation that maps colors in the input-device gamut to the corresponding colors in the output-device gamut, and (2) a gamut-mapping transformation that maps colors in the input-device gamut to substitute colors in the output device gamut. A calibration transformation that maps colors according to only these two transformations may be adequate for systems in which each color within the output-device gamut has a corresponding color in the input-device gamut; i.e., the output-device gamut colors are a subset of the input-device gamut colors. The use of only these two types of transformations is not optimum for systems in which the output-device gamut includes a significant set of colors that are not within the input-device gamut.
DISCLOSURE OF INVENTION
It is an object of the present invention to improve the manner in which colors outside an input-device gamut are mapped to colors within an output-device gamut.
According to the teachings of one aspect of the present invention, a method or apparatus performs a compensation transformation in a color image reproduction system that comprises an input device having an input gamut and an output device having an output gamut by receiving an input signal representing color space coordinates of a first color that is in the input gamut and in the output gamut, and applying the compensation transformation to the input signal to generate an output signal representing color space coordinates of a second color that is in the output gamut but not in the input gamut.
According to the teachings of another aspect of the present invention, a method or apparatus derives a compensation transformation for use in a color image reproduction system that comprises an input device having an input gamut and an output device having an output gamut by identifying a first set of colors that are in the output gamut but are not in the input gamut, identifying a second set of colors that are in the input gamut and in the output gamut, and developing the compensation transformation to enhance chromaticity of colors i
Ancin Hakan
Bhattacharjya Anoop
Lin Tsung-Nan
Shu Joseph
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