WO2004017261A2 - Method of color accentuation - Google Patents

Abstract

The color accentuation method determines the relative magnitude of each color component in each pixel or area. T selects and adjusts the magnitude of one or more of the colors as a function of the determined relative magnitudes of each color component. The type and amount of the adjustment may be a function of the relative magnitude differences. One or more of the magnitudes is adjusted to change the relative magnitudes. Typically, the difference in a subtractive color space s between the lowest and middle magnitude color and n an additive color space is between the highest and the middle magnitude color. Also, typically, the lowest color component s reduced in the subtractive color space and the highest is increased in the additive color space. Various scaling functions and compensations or adjustments of the color accentuation may be used.

Description

BACKGROU D AND SUMMARY OF THE INVENTION

[0001 ] The present invention relates generally to color processing systems and more specifically to a color accentuation system and a component of a color processing system.

[0002] Color processing falls into two general categories, namely light projections or displays which are known as additive color systems and pigment or printing systems which are known as subtractive color systems. Color correction systems have been developed to correct for errors in the reader or scanner of the original material, signal transmission or limitations of the display or printing process. Color correction systems are also used to enhance images or video taken under sub-optimal conditions (for example, poor lighting). In the printing process, the correction can be directed to ink migration and physical color discontinuity. In an image or a video display, color correction can be for errors in the processing system and/or for changing the quality or color of the picture to meet certain criteria and/or tastes.

[0003] Examples of prior art systems include US Patents 4,674,963; 5,883,984;

6,053,609; 6,057,931 and 6,097,501.

[0004] In video and television, there are continuous developments of new formats.

The present color accentuation system will help improve digital cameras, TV and other video display devices, video recording devices, and HDTV picture quality in both large and small formats. It will also improve color image printing. Digital still cameras and digital video cameras may have a button or command that triggers various levels of accentuation that would improve the picture quality. For example, one might take a picture on a dull, overcast day. When the accentuation button is pressed, the image will look like it was taken on a bright day. In another example, pictures taken with florescent lighting will look as if they were taken with more natural light.

[0005] The present invention is directed to the concept of accentuating the ultimate color image to be more vivid, color diverse, interesting to the eye and having higher color contrast. The present invention would be compatible with almost any video or print media. This patent description translates well to the CMYK color space, which is the system generally associated with the printing industry. CMYK stands for Cyan, Magenta, Yellow, and Black. These colors are related to the primary colors, red, yellow and blue, with black being considered by this invention as the absence of color. TN's and video use the RGB (Red, Green, and Blue) and Y Cb Cr and its related color spaces. The color accentuation system described herein can be converted into any known or new color space or system, whether additive (light) or subtractive (ink, paint, etc.) using well-known algebraic transformations. In addition, in some additive color spaces, the same equations can be used if certain adjustments are made to mitigate for the fact that the color components in some of these color spaces are very different hues from the primary colors. This approach achieves the benefit of the invention, with computational efficiency at the sacrifice of precision, which maybe an acceptable trade off in some applications.

[0006] The primary colors are red, yellow, and blue. Rainbow colors are generally considered the vivid, bright colors and are either a primary color or two primary colors mixed at some ratio/percentage. In a subtractive primary color space or process, as the percentage of the lowest percentage third color component increases, the overall color becomes more dirty and eventually becomes shades of grays and/or browns. This directly relates to additive color processes and spaces through color space conversion.

[0007] The system determines the relative magnitude of each color component.

The color components are the set of colors that are the axes in a given color space. For example, in Red, Blue, Yellow, RBY (the primary color space), R, B and Y are the color components. The invention selects and adjusts the magnitude of one or more of the colors as a function of the determined relative magnitudes of each color component. The type and amount of the adjustment is a function of the relative magnitude differences between the components. One or more of the magnitudes is adjusted to change the relative magnitudes. Typically, the difference in a subtractive color space (e.g., CMY(K)) is between the lowest and middle magnitude color and in an additive color space (RGB) is between the highest and the middle magnitude color. Also, typically, the lowest color component is reduced in the subtractive color space, and the highest color component is increased in the additive color space. In CMY(K), black (K) is not considered a color in the initial color accentuation step.

[0008] The invention can be applied to an image on a pixel by pixel basis (where the accentuation function is calculated and applied to each pixel individually) or on an area by area basis (where the function is calculated for an area of the image and the same function applied to each pixel in the area). An area in an image is a set of adjacent pixels in the image that have substantially the same color, in other words, substantially the same color component magnitudes. A practitioner of ordinary skill will recognize that the benefit of the invention can be attained by determining the accentuation function once for all the pixels in an area because the adjacent pixels have substantially the same color component magnitudes. [0009] Scaling functions and compensations may also be used. These include brightness compensation, dominant color compensation and saturation compensation or adjustments using various scaling functions. The arguments of the scaling functions may include the difference of the magnitude of the color components relative to each other or other arguments.

[00010] Other objects, advantages and novel features of the present invention will become apparent from the following detailed description of the invention when considered in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[00011 ] Figure 1 is a color processing system in which the present invention can be incorporated.

[00012] Figure 2 is a subtractive space color wheel.

[00013] Figure 3 is a single slice color wheel for RYB from color pipe of Figure 5 with scaling functions.

[00014] Figure 4 is a look up table in CMYK correlating the original to the accentuated color.

[00015] Figure 5 is a conceptual view of the color pipe.

[00016] Figure 6 is a flow chart of color accentuation according to the principles of the present invention.

[00017] Figure 7 shows graphs of a scaling function and its components incorporating the principles of the present invention.

[00018] Figure 8 shows graphs of various scaling functions incorporating the principles of the present invention.

[00019] Figure 9 shows graphs of additional scaling functions incorporating the principles of the present inventions. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[00020] The core of this invention is developed from the primary colors (Red,

Yellow, Blue). However, the system functions in both additive and subtractive color spaces through mathematical color-space transforms.

[00021 ] The present invention can be used in two modes. In a first mode, an image, that is encoded using any first color space, is converted into the color component magnitudes of a second color space and has the accentuation function applied in that color space. The resulting image can be converted back to the original color space. Alternatively in a second mode, the accentuation function can be determined in a first color space and then the accentuation function is transformed to any other color space so that an image need not be converted—the transformed function is applied to the image in the color space of the image. It is also possible to approximate the calculation in such a way that the image and scaling function is not entirely transformed into another color space, but parts of the algebraic transformation are used to calculate intermediate results that provide a close approximation of the invention.

[00022] By this means, a practitioner of ordinary skill will recognize that either of these modes is theoretically equivalent, but the second choice is preferred so that data loss by transforming the image in and out of a primary color space (due to numerical rounding and the like) is avoided. Although transformations exist between most color spaces, they are not always perfect, and some loss of color information can take place when converting to and from color spaces. Although the invention can be equivalently used in any color space, the use of the color black in some color space schemes requires special attention. The use of scaling functions and adjustment of scaling function coefficients can mitigate these color distortions.

[00023] RYB, the primary color space, is the ideal color space and will be initially used to explain the concept of the invention with respect to Figures 2, 3 and 5.

[00024] Since RYB is not presently available in a typical system, the invention will also be explained also with respect to CMY and RGB (RGB being used in video applications and which is also an additive color space). CMY(K) (a subtractive color space) is used as the color space for an embodiment of this system because it is a commonly used subtractive color space. The RGB and CMY(K) color spaces have known direct mathematical relationships to each other. However, because the magenta in the CMYK color space has a small blue component, operations on magenta affect two colors (red and blue), not one (red).

[00025] The present system looks at the relative differences between the colors and makes the correction based on a function of such differences. In CMYK, K, the black, is not adjusted in the initial function. But black may still be part of the color percentage, so that the conversion of CMYK to another color space is accurate. Note that the conversion of RGB to CMY does not include the black component. When all three colors CMY are substantially equal in color, they are "dirty" in color. As the differences in percentage between the colors becomes larger, the higher magnitude perceived primary colors become more dominant. The lowest magnitude value color component of the three colors creates, in the combination the other two colors, a pastel dirtiness, grayness, brown-ness or a perceived lack of contrast, vividness or perceived sharpness. The present invention creates a higher color contrast, sharper, clearer picture or color and reduces the effect of the lower of the three color components, pixel by pixel or area by area. Note that the accentuation adjustment may be to one or more of the three colors.

[00026] Transformation to or the use of color components in a polar color space will also be described. Thus, color components are the variables used to describe the color space.

[00027] An overview of the accentuation process is illustrated in Figure 6. A color space component (CSC) is provided at 30. Depending upon the type of color space being additive or subtractive at 32, the accentuation process is applied in at least one of two ways. The relative magnitude of the color components is determined at 34a or 34b. The relative magnitude determination at 34 may be a single step and may be performed before the determination of the type of color space at 32. In a device including the program of the method, the color space is pre-defined, and the method would include only one leg 34-42. There is no need for a decision in the process of determining the color space; that is, the color space is typically pre-determined by the design of the entire imaging signal chain. If it is an additive color space, the difference between the MAX and MID is determined at 36a. If it is a subtractive color space, the difference between the MID and the MDSf is determined at 36b. These differences are used at 40a and 40b, respectively, to modify the color components as a function of these differences. The output is provided as a new color space component (CSCnew) at 44.

[00028] As will be described, various scaling functions 38a or 38b may be used in modifying the color components, as well as various compensations at 42a or 42b. The compensation at 42a and 42b may be part of the color component modification 40a and 40b or may be a post-process modification. The selection of scaling may precede the steps of 34, 36 or 40 and may be incorporated as part of step 40. In the determining the relative magnitude of the color components, it may require normalizing the color component value ranges in cases where the color components do not have the same numerical range.

[00029] Depending upon the system and the color space components, the color space components may be converted to a different color space using the previously developed modified color component as a function of the differences, or the function of the differences may be converted to other color spaces. The interaction of the various components of the method will be described more fully below. It is possible to approximate the result by using any additive color space components whose value ranges are normalized in the equation otherwise derived, for example, for RGB, as further discussed below.

[00030] A pixel containing the collection of values for individual color components can be analyzed in percentage magnitudes of those color components. This is the relative magnitude relative to full scale. For example, in a 24 bit, 8 bits per color, 3 color space like RGB, the R, G or B value is divided by 255 to calculate the percentage. In the CMY(K) space, the new value of the minimum- value color component (other than black) is calculated based on one of the following equations:

(a) %MIN_NeW = [100% - (%MID - %MIN)%] * %MIN where:

MIN is the color component (excluding Black, K) in a pixel or area that has the minimum percentage value;

MID is the color component (excluding Black, K) in a pixel or area that has the middle percentage value,

MAX is the color component (excluding K, Black) in a pixel or area that has the maximum percentage value, and MDSf_New is the accentuated minimum percentage value color component (excluding

Black, K); or

(b) %MIN_New = [100% - f(%MID - %MIN)]* %MIN where f(%MID - %MIN) is a modifying or scaling function that takes the value %MΓD-%MIN as an argument.

[00031 ] The modifying or scaling function f(%MID - %MIN) result may be set to zero if the difference between MID and ML is very small. The scaling function f may be a constant times (%MID - %MLN), as in equation (a). The modifying function f(%MID - %MLN) may also increase, decrease or change the adjustment signified by the difference as a function of any of the color components present or the specific percentage relationship of the color components.

[00032] Instead of decreasing the minimum color component MLN, the maximum color component MAX may be increased. Also, both MLN may be decreased and MAX increased. The middle color component MID may also be adjusted. All adjustments are a function of the difference MED - MLN as reflected by the following formulas: (c) %MAX_new = %M AX * f_max (%MID - %MLN)

(d) %MrD„_ew = %MΓD * f_mid (%MΓD - %MΓN)

(e) %MιNnew = %MIN * f_min (%MID - %MIN)

[00033] The scaling function for its equivalent modifies one or more of the component color values based on the argument of the difference between the two lowest percentage color component values. This can be algebraically converted to any other color space using well-known mathematical conversions.

[00034] In order to maintain brightness close to the pre-processed image, an additional brightness compensation adjustment to some or all color components then takes place, dependent upon the initial amount of adjustment that occurs. All or some components of a pixel or area of pixels can be modified once the function has been calculated for such pixel or area in order to maintain the original brightness or to modify the brightness of the image. Two examples are given below for RGB and YCbCr color spaces. [00035] In general, scaling functions of any type, including non-linear functions for example a quadratic, logarithmic or exponential function or a combination of the three, may be applied to equations (a) - (e) based on any combination of the color component values. Some circumstances may require that more or less scaling occur, for example, as discussed with respect to equation (b). This applies also to equations (c)- (e). In addition to brightness compensation, a dominant color compensation and display or printing device specific compensation or scaling functions discussed below may be used.

[00036] Accentuation may be equivalently performed based on lookup tables.

Because the range of MAX, MID and MIN are known (for example, typically ranging between 0 and 255 in the case of 24 bit encoded RGB), pre-calculation of the scaling function f can be performed and a look-up table created using the non- normalized values for R, G and B as input and output. The new color component values are determined by matching the original color component values to those in the table and reading the new color component values out of the table for that color component set. The middle two columns of Figure 4 would be a partial example of such a lookup table.

[00037] Utilizing lookup tables as the basis for fetching a value from an input value may increase processing performance in certain circumstances. For example, the value (%MID - %MIN) may be utilized as an offset into a lookup table or a two- dimensional index of (%MAX, %M1D), whether MID and MLN are expressed as percentage of full scale value or as the actual numerical values. In the embodiment for the RGB color space, the non-normalized values may be used. Common assembly-level computing instruction sets and higher-level languages such as C, C++, and many others have inherent indexing capabilities that make such an implementation very efficient. The need for complicated mathematical calculations being performed during run time can be eliminated or reduced. Further, the lookup tables can be directly coded into read only memory in hardware logic implementations .

[00038] Other rules and functions can apply such that some darker wood tones and other muddy, dull or low intensity colors would not be changed. The goal for color accentuation can be changed through scaling functions to, for example, maintain a particular color's dullness and make some chosen colors brighter or more intense or to literally change some colors by increasing or decreasing one primary color more than another. As was discussed with respect to equations (b)-(e).

[00039] Figure 1 illustrates a color processing system 20 for reproducing a color image 10, as image 12, on a media 14. If this is a printing process, then media 14 is the object on which the printing is performed. If it's a display like a television or CRT, then media 14 is a display. The color processing system 20 generally includes a lens 22 providing input signals of the image 12 to a color separator 24. The color separator 24 provides a minimum of three colors and in this example, four color signals to the signal processor 26. The signal processor 26 then provides appropriate drive signals to projectors or printers 28, depending upon whether it is a printer or a light projector.

[00040] Four projectors/printers are shown but other projector or printers may be used depending upon the number of colors being processed. For example, it could be a three color additive system, a four color separation system, or a six color system.

[00041 ] The color processing system 20 can be thought of as a combination of components to process the color signal. For example, The lens 22 would introduce a color image to a color encoding system 24 that color separates a pixel into color components for a given color space. The encoded image information is presented to a signal processor 26 that applies color accentuation using the scaling functions and may also apply color space transformations. Upon completion of the signal processing, the image information is transferred to the projector/printer 28 to recombine color components through either a light projection, ink printing system, or other recombinant method to form the processed image 12. Practitioners of ordinary skill will recognize that the digital data comprising the original encoded image or the processed image can be stored as digital files on digital recording media and/or transmitted as digital files such that the components of the system depicted in Figure 1 may be separated physically and not reside within a single apparatus.

[00042] The color accentuation of the present method would be in the signal processor 26. The signal processor 26 may be part of the original camera or scanner and/or may be in the signal processor 26 for the projector or printer. The signal processor 26 may be part of a device that either plays back pre-recorded video media or processes video signals received by the device. These may include, for example, television or other display devices, as well as DND-R or other video storage devices. The signal processor 26 may include well-known signal correction software modified to incorporate the present invention.

[00043] The present method will be described with respect to one color separation system, for example, CMYK, in Figure 4 with the principles applicable to other color separations including the color formats RGB, RYB and color spaces LCH, HLS, YUN, YCbCr, YPbPr, HSN, HLS and CIE-LUN. Some of these systems deal with hue (H), saturation (S), luminance or lightness (L, Y), and chrominance (C) or the difference of a three-component color system (U, N; Cb, Cr; Pb, Pr). Saturation is the degree of color intensity. Hue is also known as the name of the color and luminance is the degree of light/dark of the color.

[00044] In Figure 2, note that any color on the outside of the wheel is vivid and/or pure. Any color on the outside of the wheel is either one primary color or combinations of two primary colors, as in a rainbow. In a subtractive color space, if any amount of a third primary color is added to the outside of the wheel, the color starts becoming dirty, less vivid, and moves into the interior of the wheel. As it approaches the center, it becomes dirty gray or brown, depending on its component colors. Eventually, as the color component percentages become large and near equal, the color becomes dirty gray which is the center of the wheel.

[00045] The Figure 3 wheel is the 100% slice through a solid color cylinder ("color pipe"), the surface of which contains the three primary colors Red, Yellow, Blue, equally spaced along the circumference. The slice of the color cylinder ranges in intensity from 0% at one end of the cylinder to 100% at the other end. Figure 5 shows a conceptual view of the color pipe.

[00046] The percentage shown on the color pipe signifies the maximum value of any of the three primary colors. Thus, if Red is the maximum color at 80%, the color wheel would be the 80% wheel of the color pipe.

[00047] The representations of the pipe and the wheel are to illustrate the principles fundamental to this invention. To be on the outside of the color wheel, one color may be at 100% for a 100% slice of Figure 3, a second color may be at any percentage, but the third color must be at 0%. Any multi-component color which contains more than two of the primaries Red, Yellow, Blue must be inside the "color pipe", and not on the surface. The colors within the circle appear dirty, having tones of brown and gray. A scaling function Si is shown which increases between the center and the outside of the wheel. This function increasingly reduces the contribution of the minimum third color (in a subtractive space) as that third color gets closer to the outside of the wheel. The equivalent dynamic in an additive space is that the function increases the contribution of the maximum color component. A set of scaling function adjustments S₂, S₃ and S₄ are also shown. They illustrate that the scaling function varies as the color moves from dirty, for example, toward pure. S₂ shows adjustment for an original color close to a pure color. S₃ and S show additional smaller adjustments.

[00048] The arrows show the adjustment of the value of the color components using a scaling function that modifies the total color component values so that the total color moves towards the outside vivid portion of the circle. The scaling function is based on differences between color component values. The length of the arrow represents the relative adjustment for one example scaling function. The amount of color accentuation relates directly to the arrow length for that pixel. The closer a color is to the outside of the wheel, the more it is accentuated towards a vivid pure color on the outside of the wheel. However, as explained below, this process can break down for pixels already very close to the edge of the color wheel, that is, for pixels that already are substantially a primary color. The scaling function is designed to attenuate itself so that the color accentuation occurs primarily in an annular ring around the center of the color wheel.

[00049] In the example illustrated in Figure 4 for the CMYK color system, the original value is shown in one column as a percentage of saturation for each of the component colors. Black or K has not been shown for sake of clarity since it is not used to determine the adjustment nor is it adjusted. During the next phase in Figure 4, for example, the accentuated/adjusted numbers are shown in the third column and the last column shows the percentage of accentuation. In this example, the difference between the middle and lowest color magnitude is taken and this difference is the accentuation percentage factor.

[00050] In the present system, no specific color is adjusted, but the lowest of three colors is the one that is adjusted downward in magnitude. This system works in such a way that grays, browns and pastels do not change or change little. When the color is gray-brown, for example, 70% for cyan, magenta and yellow, there is no accentuation because there are not substantial differences between the minimum color percentages.

[00051 ] Although the example is shown as reducing the percentage of the lowest color, the other color components may also be adjusted. For example, the highest may be increased by itself or in combination with lowering the lowest. Also, the middle color can be raised. All of these reduce the effect or contribution of the third or lowest color.

[00052] Also, depending upon the order of the percentage of the color or other color component information, the scaling function may be a modification of the numerical difference of the middle and lowest percentage of color components, as discussed with respect to equations (b)-(e) for a subtractive color space. The primary colors have different degrees of dirtiness. Blue contributes more dirtiness than red which contributes more than yellow for example. Thus if blue is the lowest percentage color component it will be reduced more than if red or yellow was the lowest percentage color component. Also, different colors saturate quicker than others and differently in different color spaces. For example, in typical media devices, red often saturates quicker or more than green or blue and, thus, would use a different scaling function. In the embodiment for an RGB color space, each of R, G and B have distinct scaling functions. Saturation is discussed in detail below.

[00053] It is well understood in the art that equations describing calculations in a given color space may be transformed algebraically into different but functionally equivalent calculations in a different color space using well-known mathematical transformations such that the results are substantially equivalent. For example, the practitioner in the art will recognize that the equation (b) which is defined for use in a subtractive color space (e.g. CMYK), can be transformed for use in an additive color space (including RGB) as follows, for example:

(f) %MAX_New = %MAX + f(%MAX-%MLD) * (100% - %MAX). [00054] An example of a non-linear function of f(%MAX-%MID) for RGB (or other additive color spaces) is as follows:

(g) %MAX_New = %MAX + a*(l - e^{(' * (%MAχ}-^%MID») *o_/oMAχ * ₍₁₀₀ ^o _/o _ %MAX) where a and b are numerical constants. The nonlinear equation (g) can be transformed into any other color space. In addition, the practitioner of ordinary skill in the art will recognize that the scaling function for use in RGB space can be itself transformed into other color spaces using well-known transformations, including to YCbCr or YUN.

[00055] The most general form of the invention for additive color spaces would be:

(h) %MAXnew = %MAX*f(%MAX-%MLD).

[00056] The practitioner of ordinary skill in the art will recognize that equation (f) is an example of equation (h). The form of equation (h) may provide computational efficiencies and is easier to manipulate in conversions between color spaces. For clarification, the practitioner of ordinary skill in the art will recognize that "%MAX" is the number equal to the value of the MAX color component divided by its range. Thus, as an example, in the typical 24 bit RGB space, if the MAX component value is 128, then %MAX = 128/255 = .50. The practitioner of ordinary skill will recognize that the look-up table implementations can use the component values rather than percentages.

[00057] A more general form of non-linear scaling function of f(%MAX-%MID) for RGB (or other additive color spaces) can be used that avoids over-saturating color by having a shape that rolls-off when the MAX-MID approaches its maximum. One example of a scaling function that has six parameters to adjust the overall shape of the function to meet the requirements of particular display or output devices is:

(i) f(%MAX-%MLD) = Zl * Z2 * Z3, where:

_Z1=a* ._e(-b(MAX-MID)/25SX

Z2=-((MAX-MID)/(255*c))^d+l Z3=-(((MAX-MID)/(255*g))-l)^h+l

[00058] This scaling function has six parameters, a, b, c, d, g, and h that can be adjusted to change the shape of the scaling function. In cases where the color data coding uses more than 8 bits per color component, the 255 divisor in these equations will be changed to be equal to 2^{(# its Per comP}°^nent>-l. The parameters are typically set so that there is an initial upward sloping or monotonically increasing section near where MAX-MLD is close to zero that then enters a concave downward or plateau peak area where the color accentuation effect is at its maximum, which then rolls off back down or monotonically decreases toward the minimum effect to be applied for large values of MAX-MID.

[00059] An example where a=0.6, b=l .0, c=l .2, d=4.0, g=l .0 and h=4.0 is shown in

Figure 7. The percentage of scaling from zero to 100% is graphed as a function of the difference from 0 to 255 for the three functions Zl, Z2 and Z3 and the product f(%MAX-%MID). The initial rise or increase from zero can be between and extend over a portion or all of 0% to 50% of the range of differences. The peak, which may be a plateau, may be between and extend over a portion or all of 0% to 80% of the range of differences. The final decline or decrease may be between and extend over a portion or all of 40% to 100% of the range of differences.

[00060] Figure 8 shows examples of four other scaling functions using equation (i).

The constants are as follows:

[00061] Figure 9 shows two other examples (superl and super2) of the scaling function compared to an exponential (exp) and linear (liner.4) version. The constants for exp, superl and super2 for equation (i) are:

[00062] The linear f(MAX-MID) is 0.4 times (MAX-MID). A review of the curve for superl shows a peak or relative plateau above 0.5 in the range of 80 to 150 or approximately 27% of the total difference range. Super2 peaks or plateaus above 0.3 in the range of 55 to 145 or 35% of the total difference range. Also, whereas superl rises over 40% of the total difference range and decreases over 22% of the total difference range, super2's rises and falls are more equal over 22% of the total difference range. Both are at zero over 30%ι of the total difference range.

[00063] This general scaling function shape can be adjusted to optimize the color accentuation effect to meet the requirements of particular storage, transmission, display or output devices. The practitioner of ordinary skill will recognize that a variety of algebraic functions can be devised that produce an equivalent shape that provides maximum color accentuation in a region between the lowest values and highest values for MAX-MID (in an additive color space) or the lowest values for MID-MrN in a subtractive space. The equation (i) can be transformed into any other color space. Alternatively, it can be used in some additive color spaces, for example, Y Cb Cr or Y U V, as an approximation, as described below.

[00064] In this example, the algebraic transformation of the equation from a subtractive space to an additive space converts the comparison of the two minimum color component magnitudes to examining the magnitudes of the two maximum color components and scaling the color component values based on the difference between the maximum and middle values of the three color components. In other words, the practitioner of ordinary skill will recognize that lowering the magnitude of the mimmum color in CMYK is the equivalent of raising the magnitude of the maximum color in RGB space.

[00065] It is also possible in some cases to use equation (h) and other equations derived for the RGB color space in other additive color spaces without transforming the algebra into that color space as an approximation. This is most easily accomplished if the scaling function is adjusted to accommodate this approximation. Thus, in a YCbCr space, the color components are normalized so that they have the same range of values, and then the MAX-MID is calculated and adjustment made to the appropriate Y, Cb or Cr component. The result is then de- normalized to produce the output Y Cb Cr pixel value in the numerical range required for the Y Cb Cr signal definition. This is especially effective if each of the Y, Cb and Cr components have a unique corresponding scaling function. It is also equivalent to incorporating the normalization and de-normalization directly into the scaling function corresponding to the maximum color component. [00066] This approach is equivalent to using three normalized axes on the color wheel other than R Y or B, but which each represent pure hues comprised of two primary colors. The adjustment moving vectors SI, S2, S3 or S4 in Fig. 3 toward the outer rim of the wheel can be accomplished by adjusting the component value along one of such axes, even if it is not a pure primary color axis. For pixels where the MAX color component is the substantially predominant in the pixel, the movement of the pixel color value on the color wheel is substantially radial, and thus this approximation is sufficiently accurate. For pixels where the color is a hue where the MAX color component is closer to the MID, then there may be hue changes when the color accentuation takes place. In these cases, the scaling function can be designed to compensate.

[00067] One compensating scaling function takes the MAX-MID argument, but also adjusts the value of the MED component so that the pixel color position on the color wheel moves radially outward. Adjustment of the MAX produces an equivalent effect. In other words, all three color components are adjusted so that the effect is to push the apparent color towards the outer ring of primaries on a color wheel.

[00068] When one reviews the following well-known conversion equations from

RGB to Y Cb Cr, one can see that this approximation is sufficiently accurate.

Y = .257*R+.504*G +.098*B + 16 (j) Cr = (.439*R) - (.368*G) - .071*B + 128 Cb = -1*.148*R - .291*G + .439*B + 128

For example, if Y is increased, green is increased relative to the other two colors. When Cb is increased, blue is increased relative to the other two colors. When Cr is increased, red is increased relative to the other two colors. Also, when one takes the difference of Y Cb Cr, again, only one color is more dominant and moves further from another color. For example, in Y minus Cb, green is increased while blue is decreased. When one takes the difference of Y minus Cb, one will see that it includes green minus blue. When one takes the difference of Y minus Cr, it includes the difference of green minus red. When one takes the difference of Cb minus Cr, it includes the difference of blue minus red. These are mere approximations because their coefficient values are associated with each of the color components and, therefore, it is not a one-to-one correspondence. However, it does show that there is a correlation and a rough estimation to provide a first order approximation. This approximation is improved by multiplying one equation by a constant before the subtraction. Further, if the Y component is increased in order to boost green, the Cb and Cr components can be adjusted to compensate for the change in blue and red induced by increasing Y. As previously stated, these functions can be encoded in look-up tables, so the computational overhead is replaced by pre-calculating these relationships and encoding them in a read only device or the equivalent. This is but one example of where the concept of the present invention works using the difference between the MAX and MLD for an additive color space not using RGB. Another method of approximation in the YCrCb space using known scaling functions from the RGB space is as follows. The following difference equations are calculated:

R-G = 2.409*(Cr - 128) + .391*(Cb - 128) (k) R-B = 1.596*(Cr - 128) - 2.018*(Cb- 128) G-B = -.813*(Cr - 128) - 2.409*(Cb - 128)

A logic table determines whether R, G or B is the MAX or MLD, and MAX-MLD is already calculated. This difference is used in a look-up table to determine the scaling function F of RGB for the corresponding MAX. For the present example, green G is assumed to be the MAX and, consequently, green G is to be accentuated. The following equations are an approximation of the adjustment:

Ynew = Y + .504*F*ANG(G) (1) Crnew = Cr - .368*F*ANG(G) Cbnew - Cb - .291*F*ANG(G) where ANG is an average value for R, G, or B and generally selected to be in the middle portion of the difference range as discussed with respect to Figures 8 and 9. The argument for ANG is the color component that is to be accentuated, hence, in this example, it is ANG(G). Alternatively, ANG can be locally calculated in the region surrounding the location of the pixel. Although the same ANG may be used for each of the three Y, Cr, Cb equations, a different ANG may be used for each of Y, Cr, Cb. Where R is MAX, the coefficients of F in equation (1) would be (.257, .439, -1.148) for Ynew, Crnew, Cbnew, respectively, and, if B is MAX, the coefficients of F would be (.098, .-071, .439). Thus, an approximation of the attenuation is performed without a complete conversion to RGB nor an exact conversion of the scaling equations which would require substantial computation. Another advantage is that the MAX-MID is calculated once for two pixels because Y falls out of the equation. The practitioner of ordinary skill will recognize that many video systems share a single Cb and Cr value pair between two different pixels, where the Y value is the only color component difference between the two pixels. The practitioner of ordinary skill will recognize that the coefficients, which are derived from equation (k), will be different if different coefficients are used in the assumed conversion from YCrCb to RGB.

[00070] The above coefficients relating to YCrCb and RGB are but an example of one set used for one standard conversion between YCrCb and RGB. There are other known and possibly to be developed standards with different coefficients that can be used with the present method.

[00071] As previously discussed, brightness compensation acts to offset the overall brightness change in an image after the initial color accentuation takes place. In RGB or other additive color spaces, color accentuation acts to brighten a pixel by adjusting one color component upward in value based on the color accentuation function. The accumulation of accentuation across an image therefore increases the "brightness" of the image. The brightness compensation may affect all three components in a pixel proportionally to the amount of accentuation on the accentuated component in the pixel.

[00072] The operation describing Brightness Compensation for all three components is as follows:

(m) %MAXnew2 = %MAXnew * BrightnessScale *(%MAXnew - %MAX) + %MAXnew

(n) %MIDnew = %MID * BrightnessScale * (%MAXnew - %MAX) + %MID (o) %MINnew = %MLN * BrightnessScale * (%MAXnew - %MAX) + %MEN wherein the input components to brightness compensation, after color accentuation are %MAXnew, %MID, and %MLN and the output after brightness compensation are MAXnew2, MIDnew and MLNnew. A user controlled or set multiplier called BrightnessScale is a parameter used to further scale the magnitude of the brightness compensation operation.

[00073] It should be noted that brightness compensation may also be performed in

RYB, CMY and CMYK color spaces as well as using the brightness, luminance or lightness L of other polar color spaces for scaling. The operation of this process may be transformed through standard color space conversions and are equivalent.

[00074] Brightness compensation may also be performed to preserve the characteristic brightness as described by the "Y" value in color spaces YUN, YCbCr, etc. The process is as follows:

• Perform the color accentuation step on the image in RGB or any other color space, after conversion from YUN or YCbCr, as the case may be, to RGB (or that other color space).

• Calculate the original and new Y values Y and Ynew through the color space conversion equations that define the conversions from RGB to YUN, or RGB to YCbCr (if the other color space is RGB, for example).

• Using the arithmetical relation of Y and Ynew (for example, their ratio), scale the magnitudes of the two color components of the pixel that have not been adjusted by color accentuation (e.g., MIDnew and ML new in RGB color space). The resulting three components are the pixel output in RGBnew (or whatever the other color space is).

• Transform the new RGBnew result (or whatever the other color space is) to YUNnew or YCbCrnew using well-known transform arithmetic, resulting in a YUN or YCbCr brightness compensation.

[00075] Alternatively, the brightness compensation in Y may scale all three color components or just one color component. The number of color components scaled may be a function of the transformation equations for Y. Also, the brightness correction should not substantially diminish the results of the color accentuation. [00076] If the color accentuation is applied in Y Cb Cr space directly, then the brightness adjustments can take place in the scaling function and conversion into and out of RGB space described above are skipped.

[00077] When a particular color component of a pixel is especially prominent in an image, color accentuating the image can make the image appear "over saturated" in that dominant color. This is especially the case because color imaging devices have a finite range of color component values. The result may be unsatisfactory. Dominant color compensation may be used to limit the amount of color accentuation that is applied to a dominant color to minimize over saturation of the dominant color in the frame or image.

[00078] Dominant color compensation begins with measuring the image as a whole for the relative prominence of a particular color component. In RGB space, an additive color space, this test is for Red, Green, and Blue. In CMY or CMYK color spaces, subtractive color spaces, the test is for Cyan, Magenta, or Yellow, where black is ignored in the CMYK color space. One preferred embodiment is to average the separate color component values across the entire image. A result for each color is obtained. For the RGB color space, an average value for each of Red, Green, and Blue are obtained. The highest value is considered the prominent color.

[00079] The difference between the highest average color value and the next- highest average color value is used to scale the amount of color accentuation applied to any pixel. This difference between the highest and next-highest average color values are inputs to a mathematical function, which then creates a color prominence multiplier. This is implemented by multiplying the result of the average-value difference function by the resulting scaling function for that pixel. It is applied only to those pixels where the maximum color component for the pixel is the same color component as the maximum average color component of the image.

[00080] The following equation describes this process for RGB or other additive color space:

(p) %MAXnew = %MAX + f(%MAX - %MID) * g(ANGmax - ANGmid) where

ANGmax is the averaged color component value across all pixels in an image that has the largest resulting value; ANGmid is the averaged color component value across all pixels in an image that has the next-largest resulting value; g(ANGmax - ANGmid) is a function that calculates the amount of color prominence scaling that should be applied to an image when the MAXold color and ANGmax color are the same color component.

[00081 ] For subtractive color spaces, the inverse would apply. The dominant color component would be the minimum color component and the compensation or prominence scaling would be g(ANGmid - ANGmin) in equation (b) for %MIΝ.

[00082] This adjustment for color dominance in a region can also be achieved using convolution. For a given pixel with a maximum color component, a convolution is performed that integrates over all the neighboring pixels within some radius R, the cumulative sum of each magnitude of the same color component divided by their corresponding distances from the given pixel. The scaling function applied to the given pixel is multiplied by a coefficient inversely proportional to the convolution result. In this manner, when a pixel resides within a region where the same maximum color component is heavily dominant, the scaling function is reduced in effect. The practitioner of ordinary skill in the art will recognize that similar convolution results can be achieved by using the distance to some power, or the color component magnitude to some power or some combination thereof. An example equation is presented:

[00083] The convolution result for a pixel located at point x,y in the image is calculated as: x =x+x₀ y =y+y₀ %MAX(x ,y )

(q) Cx,y = ∑ ∑ _\2 _\N x=_x-x₀ y=_y-y₀ (.(^χ - ^χ) + (y - y) ) where %MAX(x',y') is the value of the color component being analyzed at point (x',y') in the image. X₀,Y₀ are the dimensions of the region of convolution, and N is the selected sharpness of the convolution function. When the MAX color is dominant in the region of convolution, Cx,y is large. Thus, the scaling function can be attenuated by a number inversely proportional to Cx,y or Cx,y raised to some degree. The practitioner of ordinary skill in the art will recognize that this technique is equivalent to convolving across any shape surrounding the point X,Y. For most images, the computationally easiest form is the rectangular shape, with the convolution calculated discretely, as demonstrated above.

[00084] As previously discussed, the scaling functions can be applied such that a different scaling function is applied depending on which color component is the MAX (in the case of an additive color space) or MIN (in the case of a subtractive color space). In other words, each color can have a different scaling function for the same differences. This is another way of dealing with the over saturation problem in at least some colors. For example, often R is accentuated too much, while the G and B are acceptable when all three use the same scaling function. The practitioner of ordinary skill will recognize that each color component can have its own scaling function such that when a given pixel has a color component selected as MAX (in the additive case), then the scaling function for that color is used for that pixel. In the typical case, the R scaling function is less than the scaling function for G and B. The practitioner of ordinary skill will recognize that the selection and shape of the scaling functions for the different color components will depend on the characteristics or requirements of the particular display or image output device, storage device or where the color coding and decoding signal process is situated.

[00085] In certain cases, a particular display or printing device may have particular visual characteristics, in other words, its color response function may have nonlinear aspects. Therefore, the scaling function can be modified to complement these effects. For example, where the display device would appear to over saturate at certain levels when color accentuation is applied, the scaling function can be modified to level off when %MLD-%MIN (in a subtractive space) reaches a certain threshold and roll-off when it reaches a second threshold. Similarly, when %MLD- %MLN is less than a certain threshold, the scaling function can be set to a set amount. Practitioners of ordinary skill in the art can construct smooth transitions from the scaling function domain across the threshold to the domains where the scaling function value is set to a different function.

[00086] The present system is considered a color accentuation system, not a color correction system, although it is expected that this process can become a new kind of color correction. Color correction implies that the to be printed or displayed color is corrected to be identical to the original image. In many cases, the image taken has color flaws that depart from the original, or the intended original.

[00087] The present method or system has used the amplitude of the color components as the parameter to be measured and adjusted. Other parameters of the system may be used for the relative measures and adjustment. They could include any of color, hue, saturation, luminance, chrominance, focus or any other video control. Also, the scaling function, adjustments and compensation may use functions whose arguments do not include the differences of color component magnitudes.

[00088] Although the present invention has been described and illustrated in detail, it is to be clearly understood that the same is by way of illustration and example only, and is not to be taken by way of limitation. The scope of the present invention is to be limited only by the terms of the appended.

Claims

WHAT IS CLAIMED:

1. A method of color adjustment of a digital image comprising: determining, for at least one pixel in a color image, which of the color components of the pixel are, relative to each other, either the maximum and middle components for an additive space or the middle and minimum magnitudes for a subtractive space; and adjusting the magnitude of either the maximum color component by a scaling function, whose argument includes the difference of the maximum and middle component magnitudes in an additive color space, or the magnitude of the minimum color component by a scaling function, whose argument includes the difference of the middle and minimum component's magnitudes in a subtractive color space; wherein the absolute value of the scaling function initially increases from an initial value to a maximum value as the difference increases from its minimum to its maximum, whereby the maximum absolute value in the scaling function is reached when the value of the difference is less than its maximum range.

2. The method according to Claim 1, wherein the absolute value of the scaling function initially increases from an initial value to a maximum value and finally decreases to a final value which is less than the maximum value.

3. The method according to Claim 1, wherein the initial value is zero.

4. The method according to Claim 1, wherein the initial increase is between and extends over all or a portion of 0% to 50% of the range of the differences, the peak is between and extends over all or a portion of 0% to 80% of the difference range and the final decrease is between and extends over all or a portion of 40% to 100%) of the difference range.

5. The method according to Claim 1, wherein the initial increase is 20% to 40% of the total range of the differences, the peak is 25% to 35% of the total difference range and the final decrease is 20% to 25% of the total difference range.

6. The method according to Claim 1 , including determining the most dominant color component and next dominant color component in a group of pixels; and adjusting the most dominant color component as a function of a comparison of the most dominant color component to the next dominant color component.

7. The method of Claim 6 where the determining step is made by calculating a convolution on all neighboring pixels within a bound area.

8. A method according to Claim 1, wherein the color components are translated from a first color space into a second color space before the determining steps and translated back to the first color space from the second color space after the adjusting step.

9. A method according to Claim 1, including transforming the determining steps and the adjusting step from a second color space to a first color space; and performing the adjusting step in the first color space.

10. A method according to Claim 1, wherein the process is performed on an area basis.

11. The method according to Claim 1, wherein the additive color space is one of red, green, blue and red, yellow, blue.

12. The method according to Claim 1, wherein the color components of the subtractive color space that are used in the process include cyan, magenta and yellow.

13. The method according to Claim 1 , wherein the method of color accentuation is transformed for use in a polar color space including LCH, HLS, YUN, YCbCr, YPbPr, HSN, HLS, AND CIE-LUN.

14. The method according to Claim 13, wherein the transformation for use in a polar color space is an approximation.

15. The method according to Claim 1, wherein the color components are in a polar color space including LCH, HLS, YUN, YCbCr, YPbPr, HSN, HLS, AND CIE-LUN.

16. A method according to Claim 1 , wherein the magnitude is adjusted by a scaling function whose value is determined by the color of the color component being adjusted.

17. The method according to Claim 1, including after the magnitude adjusting, adjusting the magnitude of all the color components by a brightness scaling function.

18. The method according to Claim 1 , including after the magnitude adjusting, determining the brightness of the color components before and after the magnitude adjustment; and adjusting some of the color components as a function of the comparison of the before and after brightnesses.

19. A color accentuation method for a pixel of a digital color image comprising: calculating either a new maximum color component value of the pixel as a function of the maximum color component for that pixel and the value of the same color component among a pre-determined number of local pixels for an additive color space or a new minimum color component value of the pixel as a function of the minimum color component for that pixel and the value of the same color component among a pre-determined number of local pixels for a subtractive color space; calculating a scaling function using either the calculated new maximum color component value for the additive color space or the new minimum color component value for the subtractive color space; and adjusting the value of either the new maximum color component for the additive color space or the new minimum color component value for the subtractive color space of the pixel by the amount of the scaling function.

20. A method according to any of Claims 1-19, wherein the process is performed on a signal processor.

21. A digital processor that applies the method according to any of Claims 1-19 to video or image data read from media or inputted video or image signals.

22. The method of Claim 7, wherein the convolution is calculated for a pixel located at point x,y in the image is calculated as:

₌ ^x' ° ^{y' y}° %MAX(x ,y )

^{X,y ~} xΛyΛ^χ -^χf Hy -y)Υ where %MAX(x',y') is the value of the color component being analyzed at point (x',y') in the image, Xo,Yo are the dimensions of the region of convolution, and N is the selected sharpness of the convolution function.

23. A method of color adjustment of a digital image made up of pixels residing in a color signal processing system comprising: increasing the saturation of at least one color component in at least one pixel whose position on a color wheel lies substantially within an annular ring around the center of the color wheel while not substantially increasing the saturation of said at least one color component for the pixel that lies outside the annular ring.

24. The method according to Claim 23, wherein the amount of saturation increase gradually increases as the location of the at least one pixel moves from the interior region on said color wheel surrounded by said annular ring to within the annular ring.

25. The method according to claim 23 where the amount of saturation increase gradually decreases as the location of the at least one pixel moves from within the said annular ring to the region on said color wheel exterior the annular ring.

26. A method of color adjustment of a digital image made up of pixels encoded in a polar color space, residing in a color signal processing system comprising: determining for at least one pixel in the image the difference of the amount of at least two of the set of red, green, blue and yellow by calculating a linear combination of at least two of the polar color components of said pixel.

27. A method of color adjustment of a digital image made up of pixels encoded in a polar color space, residing in a color signal processing system comprising: determining for at least one pixel in the image, the maximum, middle and minimum amounts of three of the set of red, green, blue and yellow; and adjusting the apparent intensity of at least one of the set of red, green, blue and yellow by calculating new values for the polar color components as a function of the difference between said maximum and middle amounts.

28. The method according to Claim 27 where the determining step is the method according to Claim 26.

29. The method according to any of Claims 26-28, wherein said polar color space is one of LCH, HLS, YUN, YCbCr, YPbPr, HSN, HLS, and CIE-LUN.

30. The method according to any of Claims 26-28 where the results of applying the method are pre-calculated across the range of values in the polar color space and stored in a table, wherein said table is a computer memory or device.