Facsimile and static presentation processing – Static presentation processing – Attribute control
Reexamination Certificate
1998-12-11
2002-06-11
Lee, Thomas D. (Department: 2722)
Facsimile and static presentation processing
Static presentation processing
Attribute control
C358S504000, C358S523000
Reexamination Certificate
active
06404511
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates generally to the self-calibration of a network copier system, and more particularly to a calibration technique to enable different printers of the same type to generate high fidelity color reproductions of an original image with minimal or no variation between the reproductions produced by the different printers.
2. Description of the Related Art
A network copier system typically includes input devices, such as color scanners, for scanning an original color image and for producing scanner color signals representing the image, output devices, such as color printers, for reproducing the color image, and a digital image processor for transforming scanner color signals into printer color signals.
Each color input and output device uses a device-dependent color-coordinate system to specify colors. These coordinate systems are often specified in some color space that naturally maps the color coordinates to the color-generation mechanism of the device. The term color space refers to an N-dimensional space in which each point in the space corresponds to a particular color.
Many color spaces are possible; some of the more common are RGB, CMY(K) and CIELAB color spaces. In the RGB color space, each point in the space represents a particular color which is formed by additive amounts of red (R), green (G) and blue (B) colorants. Scanners are typically controlled by signals that are specified in RGB color space. In the CMYK color space, each point in the space represents a particular color that is formed from a subtractive combination of cyan (C), magenta (M), yellow (Y) and black (K) color dyes. If black (K) is not used, the color space is designated as CMY. Ink printers normally operate in CMY(K) color space in which the colors are superimposed in selected amounts on a reflective background surface such as white paper. The dyes selectively absorb certain ranges of wavelengths of light and the eye perceives the reflected light; thus the term “subtractive.” The CIELAB color space is an internationally standardized color space which provides a relatively uniform perceptual space for describing colors. A uniform perceived change for a given input change is a very desirable property in that the precision required to express colors to a particular degree of fidelity can be more readily specified in a color space with uniform perceptual characteristics. Thus, the CIELAB color space is particularly useful in applications requiring precise color reproduction. The dimensions in this color space are defined by L*, a* and b* which are used to represent luminance (or lightness), hue angle and chrominance (or colorfulness).
Many practical devices are capable of sensing or reproducing only a portion of the full range of colors that can be discerned by a human observer. A device color gamut refers to the range of colors that can be sensed or reproduced by a particular device. For example, a scanner color gamut G
s
corresponds to the set of colors which can be detected by that scanner and a printer color gamut G
p
corresponds to the set of all colors which can be printed by that printer.
The scanner color gamut G
s
is determined by a variety of factors including the spectral response of the scanning sensor, spectral characteristics of the color filters used to extract color values for a given color input, spectral characteristics of the illuminant, and the resolution and linearity of analog-to-digital converters. The printer color gamut G
p
is also determined by a variety of factors including properties of the media and ink, resolution or dots per inch of the printed image, halftoning methods, and device drivers. Different printers typically have different color gamuts.
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 generally would not be satisfactory because the device-dependent coordinate systems and color spaces for the input and output devices are generally not the same. Even if the two sets of coordinate systems and color spaces are the same, the fidelity of the reproduced image as compared to the 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. Values representing “out-of-gamut” colors that are not in the output device gamut cannot be reproduced exactly. Instead, some “in-gamut” color that is in the gamut of the output device must be substituted for each out-of-gamut color.
Color image reproduction systems can achieve high-fidelity reproductions of original images by applying one or more transformations or mapping functions to convert point coordinates in one color space into appropriate point coordinates in another color space. These transformations may be conveniently performed by the digital image processor, mentioned above. In particular, with respect to the output device gamut, transformations are used to convert values representing in-gamut and out-of-gamut colors in an input-device-dependent color space (DDCS) into values representing in-gamut colors in an output-DDCS.
The transformation of output device in-gamut colors for many practical devices are non-linear and cannot be easily expressed in some analytical or closed form; therefore, practical considerations make accurate implementations difficult to achieve. Many known methods implement these transformations as an interpolation of entries in a look-up table (LUT) derived by a process that essentially inverts relationships between device responses to known input values. For example, a transformation for an input device may be derived by using a medium conveying patches of known color values in some device-independent color space (DICS) such as the CIELAB space, scanning the medium with the input device to generate a set of corresponding values in some input-DDCS such as RGB color space, and constructing an input LUT comprising table entries that associate the known color L*a*b* values with the scanned RGB values. In subsequent scans of other images, scanned RGB values can be converted into device-independent L*a*b* values by finding entries in the input LUT having RGB values that are close to the scanned values and then interpolating between the associated L*a*b* values in those table entries. Various interpolation techniques such as trilinear, prism, pyramidal and tetrahedral interpolation may be used.
Similarly, a transformation for an output device may be derived by producing a medium with color patches in response to color values selected from some output-DDCS such as CMYK color space, determining the color value of the patches in a DICS such as CIELAB space by measuring the patches using a spectral photometer, and constructing an output LUT comprising table entries that associate the measured color L*a*b* values with the corresponding CMYK values. In subsequent output operations, L*a*b* color values can be converted into device-dependent CMYK values by finding entries in the output LUT having L*a*b* values that are close to the desired values and then interpolating between associated CMYK values in those table entries. Various interpolations such as those mentioned above may be used.
In operation, a color image reproduction system scans an original image to obtained scanned value in some input-DDCS, transforms the scanned values into some DICS, transforms these device-independent values from the DICS into some output DDCS and, in response, generates a replica of the original image. As mentioned above, the transformations described thus far apply only to output device in-gamut colors.
By definition, output device out-of-gamut colors cannot be reproduced exactly. Instead, high-quality color image reproduction systems use transforms or mapping functions that substitute an in-gamut color for each out-of-gamut color. Preferably, these transforms attempt to minimize the perceptible difference between each out-of-gamut color and the corresponding su
Lin Tsung-Nan
Shu Joseph
Gabrik Michael T.
Lee Thomas D.
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