1. Field of the Invention
This invention generally relates to the field of printer systems, and more particularly relates to a system and method for optimizing color ranges in gamut mapping.
2. Description of Related Art
In color printing, displaying, or reproduction, the term gamut represents the set of all colors that a color-reproduction device is physically able to generate. Every device that displays or reproduces an image, such as a printer, monitor, scanner, or digital camera, may have its own unique color gamut. When an image is transferred from one device to another, the color gamut of each device must be examined.
The color gamut set has two components that need to be considered: The gamut boundary and the number of colors that are realizable within the gamut boundary. The gamut boundary of a device represents the outermost extent of the device""s capabilities in some reference color space. Because of quantization in color reproduction systems, such in digital halftone devices (color halftone printers), not all colors that are within a device""s boundary are realizable. The shape and extent of this volume are generally a function of the device primaries and the viewing environment under which the reproductions are observed. Significant differences can exist between the gamut produced by color imaging systems that utilize different primaries and viewing environments.
When the input color space is bigger than the gamut of the output color device, then gamut-mapping algorithms need to be applied. The gamut mapping process transforms a point in the source gamut to a realizable color inside the gamut of the output device. The form of this transformation can dramatically impact the quality of the reproduced images. As such, care needs to be used in the design and implementation of gamut mapping transformations.
All the current gamut-mapping algorithms are so-called xe2x80x9cone-stepxe2x80x9d gamut mapping, i.e., map all out-of-gamut points directly to the destination gamut. The most typical gamut mappings are
(1) Clipping algorithms: to clip of out-of-gamut points to the destination gamut boundary, and
(2) Scaling algorithms: to scale the input color gamut to output color gamut, i.e., some out-of-gamut points are mapped to inside of the destination gamut, some out-of-gamut points are mapped to the boundary of the destination gamut.
The large variability in past color gamut mapping studies suggests that ideal gamut mapping depends on image content, preservation of perceived hue throughout color space, and the extent of the gamut mismatch in various regions of color space. Image dependent and regional-dependent gamut mappings are preferred. However, image dependent gamut mapping algorithms suffer a performance penalty.
Perceptual gamut mapping is a widely used mapping algorithm in color reproduction. It modifies both in-gamut and out-of-gamut colors from their colorimetric representation in order to provide a pleasing or perceptual appearance. The results of the perceptual gamut mapping normally depend on the input color range and the device color gamut. If the input color range is much bigger than the actual output color range (e.g., images from digital camera, scanner . . . ), the reproduced colors through perceptual color gamut mapping will have lower chroma, and are intended to be less vivid. Moreover, the chroma contrast is significantly reduced. Thus, it decreases the image quality of reproduction. This problem is especially worse for high-end color printers with relatively small color gamut.
Therefore a need exists to overcome the problems with the prior art as discussed above, and particularly for a method of optimizing color ranges in gamut mapping.
According to a preferred embodiment of the present invention, a method finds the color gamut of a first device and a second device in their device-dependent color spaces, converts each color gamut to a device-independent color space, compares the color gamut of the first device to the color gamut of the second device in the device-independent color space, and finds an optimized intermediate color range in the device-independent color space. Then, the method maps the colors from the color gamut of the first device in the device-independent color space to the optimized intermediate color range using a first gamut-mapping algorithm, maps the colors inside the optimized intermediate color range to the color gamut of the second device in the device-independent color using a second gamut-mapping algorithm, and converts the colors in the color gamut of the second device in the device-independent color space back to the color gamut of the second device in the device-dependent color space.
USPTO Backgrounds
USPTO Backgrounds