Gamut mapping algorithm using inverted gamma function

Details Gamut mapping algorithm using inverted gamma function Gamut mapping algorithm using inverted gamma function

1998-12-16

2002-01-29

Nguyen, Madeleine (Department: 2622)

Facsimile and static presentation processing

Static presentation processing

Attribute control

C358S519000

Reexamination Certificate

active

06342951

ABSTRACT:

BACKGROUND OF THE INVENTION
In the color digital image processing arts, the space of colors that a printer (or other output device) is capable of reproducing is referred to as the “gamut” of the printer. Very often, colors specified in a digital image cannot be reproduced by a particular printer when it comes time to output the color digital image to the printer for purposes of rendering a hard copy printed output of the digital image. The printer gamut (also referred to herein as the output gamut) is often limited when compared to the gamut of the source digital image (the input gamut) due to physical limitations of the printer's colorants. Colors in the input gamut but not in the output gamut are said to be “out-of-gamut” and must be accounted for before the digital image may be printed—i.e., areas in the output document where these colors are to be found may not simply be left blank in the final printed document.
One prior technique for dealing with out-of-gamut colors in a digital image involves mapping each out-of-gamut color to a color on the gamut “surface” while leaving the remaining colors in the digital image untouched. This technique, commonly referred to as “clipping,” has heretofore been thought to be desirable for purposes of preserving hue angle, lightness, and/or saturation, or minimizing color errors when mapping the out-of-gamut colors to the surface of the three-dimensional printer gamut. However, viewers often do not like the resulting image. Clipping often leads to unwanted artifacts in the printed image such as the apparent flattening of curved surfaces and loss of color detail information due to its “many-to-one” mapping approach. Accordingly, simply clipping out-of-gamut colors in this manner has been found to be undesirable.
Another prior approach involves “compressing” the input gamut by mapping both in-gamut and out-of-gamut pixels of a digital image to colors in the output gamut through use of three-dimensional look-up tables. A goal of this approach is to preserve smooth color transitions in images. However, this technique has been found to result in undesired desaturation or “washing-out” of images.
In general, when judged in terms of viewer satisfaction, prior gamut mapping techniques have been found to be sub-optimal. While these prior techniques commonly attempt to preserve hue angle, or both hue angle and lightness in an image, the resulting image often lacks perceived contrast due to the fact that the slope of the input-to-output lightness function is reduced to less than 1 in an attempt to preserve information. Furthermore, conventional gamut compression techniques (where the entire input gamut is compressed into the output gamut) are typically implemented in three-dimensional look-up tables which makes modification of the look-up tables for a given image computationally cost prohibitive—i.e., use of three-dimensional look-up tables does not facilitate modification of the gamut mapping method to account for characteristics of a particular digital image due to the computational cost in creating and manipulating a three-dimensional look-up table.
Accordingly, it has been deemed desirable to provide a gamut mapping method not requiring use of a three-dimensional look-up table and wherein perceived contrast in the output image is not reduced and so that the appearance of objects in the image is preserved without undesired desaturation. Furthermore, it has been deemed desirable to provide a gamut mapping method suitable for modification on an image-by-image basis according to image statistical data to improve the resulting image.
SUMMARY OF THE INVENTION
In accordance with the present invention, a new and improved color digital image gamut mapping method is provided.
In accordance with a first aspect of the present invention, a gamut mapping method includes receiving digital image data including a plurality of input pixel values selected from an input color gamut, each of said input pixel values defined in terms of plural gray values wherein each gray value is in the range of 0≦gray value ≦1 or wherein each gray value is scaled into this range. Each input pixel value is respectively mapped to an output pixel value. The mapping operation includes: (a) individually inverting the gray values for each input pixel value according to the equation 1-gray value; (b) applying a gamma value (&ggr;) individually to each inverted gray value according to the equation (inverted gray value)
&ggr;
, the gamma value being related to an amount by which a dynamic lightness range of the digital image data is to be compressed relative to an output color gamut of an image output device, and, (c) inverting each inverted gray value after application of the gamma function thereto according to the equation 1-(inverted gray value)
&ggr;
so that the gray values defining the input pixel values are mapped to gamma-modified gray values defining the output pixel values, respectively.
In accordance with another aspect of the present invention, a digital image processing apparatus comprises means for input of digital image data of an image in terms of a plurality of input pixel values selected from an input gamut and defined in terms of at least one gray value (or scaled gray value) so that 0≦(scaled)gray value <1; means for output of digital image data in terms of an output color gamut; and, an image processing unit for mapping each input pixel value to an output pixel value. The image processing unit includes means for inverting the at least one gray value to an inverted gray value; means for applying a gamma function to the inverted gray value according to: (inverted gray value)
&ggr;y
, wherein
&ggr;
is related to an amount by which the dynamic lightness range of the input image is to be compressed relative to the output color gamut; and, means for converting the inverted gray value, after application of the gamma function, to a non-inverted gray value.
In accordance with yet another aspect of the present invention, a method of mapping an input pixel value defined in terms of a plurality of gray values, which are in or scaled to be in the range of 0≦gray value ≦1, from a value in an input gamut to an output value in an output gamut includes inverting at least one of the gray values to obtain an inverted gray value and applying a gamma function to the inverted gray value to obtain a gamma-modified inverted gray value according to:
gamma-modified inverted gray value=(inverted gray value)
&ggr;
, wherein &ggr; is determined according to:
&ggr;=log(1
−Y
x
′)/log(1
−Y
x
)
Y
x
=(1
−Y
min
)*(1−(
X/
100))+
Y
min
Y
x
′=(1
−Y
min
′)*(1−(
X/
100))+
Y
min
′
X=a compression percentage in the range of 92%-98%
Y
min
=one of: (i) a darkest expected input pixel luminance value in said image; and (ii) a darkest actual input pixel luminance value in said image, wherein Y
min
is expressed in terms of 0 ≦Y
min
≦1
Y
min
′=a darkest output luminance value in said output gamut expressed in terms of 0≦Y
min
′≦1; and,
Thereafter, the gamma-modified inverted gray value is, itself, inverted.
One advantage of the present invention is that it provides a new and improved gamut mapping method for color digital images.
Another advantage of the present invention is found in the provision of a gamut mapping method that uses a simple gamma function to control the lightness compression of an input gamut relative to a printer or other output device gamut.
A further advantage of the present invention resides in the provision of a gamut mapping method which uses a combined approach of application of a gamma function and a subsequent clipping operation.
Still another advantage of the present invention is that it may be implemented using one-dimensional tone reproduction curves (via plural one-dimensional look-up tables) which facilitates modification of the gamma function on an image-by-image basis according to statistical parameters for the image.

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