Abstract:
A system and method manipulates and corrects the color of digital images. The invention addresses, inter alia, the problem of the differences in chromaticity of two systems by characterizing the chromaticity of the hues of a color model to minimize the perceived color difference between a digital image and its real world counterpart.

Description:
FIELD OF THE INVENTION  
       [0001]     The present invention relates to a corrective color system and a method and system for correcting the color of a digital image.  
       DESCRIPTION OF RELATED ART  
       [0002]     There exist many theoretical models that may provide a reasonable approximation of the human visual system, such as color spaces or color appearance models. These models provide a transformation between a native device color space and a particular human visual color space such as CIE XYZ. The CIE XYZ color space utilizes a set of spectral weighting functions that model human color perception. These functions, illustrated as curves and defined numerically, are referred to as the {overscore (x)}, {overscore (y)}, and {overscore (z)} color matching functions (CMFs) for the CIE Standard Observer and are shown in  FIG. 1 . As seen in  FIG. 1 , the color matching functions  100  include the {overscore (x)} weighting function  110 , the {overscore (y)} weighting function  115 , and the {overscore (z)} weighting function  120 . Each of the color matching functions  100  is plotted for wavelengths of light ranging from 400 nm to 700 nm, which is approximately the range of human color perception. Examples of other well-known color models include linear Red-Green-Blue (RGB), nonlinear RGB, Hue-Saturation-Value (HSV), and Cyan-Magenta-Yellow (CMY).  
         [0003]     While a color space ideally contains all information necessary to describe every color, for reasons of complexity, such “full color” spaces are difficult to implement in real world devices. As such, physical devices generally encode color using a “color coding” method, which can be simple and efficient at representing a wide range of colors.  
         [0004]     Once a physical device, such as a digital camera, encodes an image of a physical object using, for example, additive RGB, the image can be converted into a data file and viewed on a standard color monitor using a standard computer. While the CIE XYZ color space and its derivates can be successful in achieving proper color management, there is currently a lack of an effective approach to reproduce with high fidelity the image capture information with the CIE and other color systems. Since there is no standard selection of primary colors (e.g., red, green, and blue), the image may appear differently as compared to the colors of the actual physical object itself, which forms the basis of the image. For example, a digital camera may have a different intensity response to a hue of red compared to the primary red phosphor used by the viewing monitor, resulting in an inaccurate rendition of the perceived reproduced color when compared to the physical object.  
         [0005]     The tristimulus values of CIE are based upon a sampling from incandescent sources with color added using external filtration. The RGB model describes the production of color using phosphorescent sources. The chromaticity of these two systems is not the same. A result is that digital signals characterized by trichromatic theory (CIE) or by other color spaces and displayed using a phosphorescent emitter (RGB) produce images that are not accurately representative of their real world counterpart.  
       SUMMARY OF THE INVENTION  
       [0006]     The present invention addresses, inter alia, the problem of the differences in chromaticity of two systems by characterizing the chromaticity of the hues of a color model to minimize the perceived color difference between a digital image and its real world counterpart. Accordingly, the invention identifies a process for color correcting a digital image by establishing a simultaneous viewing evaluation for the express purpose of determining the color fidelity of an image recorded using a photoelectric sensor and the original subject of the recording.  
         [0007]     It is an aspect of the present invention to provide a method and apparatus for more accurately rendering the color of digital images generated by an image capture device such as digital cameras, digital camcorders, digital video telephones, digital cellular telephones, and digital scanners. In doing so, the invention takes into account that when an image capture device employs a color model (e.g., a RGB color model) and is recording an image of a uniform blue hue, a change of the illumination or of the luminance of that hue (i.e., a change in the intensity of the blue light) is perceived by a human observer to be accompanied by a change in chromaticity. Thus, for a digital image to reproduce a change in illumination or luminance, the intensity values of the primary colors produced by the display device must, in general, vary even when the change in intensity is detected by the capture device to be occurring only along one primary color axis.  
         [0008]     It is an aspect of the present invention to provide a method and system for relating the color of generated digital images, including at least three generated primary colors as defined in a color model, to the primary color intensities detected by the digital capture device, wherein at least one of the generated primary colors varies as a function of at least two of the detected primary color intensities.  
         [0009]     It is an aspect of the present invention to provide a method and system for the generation of an image, the colors of which are comprised of at least three image primary colors, derived from at least three detected primary colors detected by an image capture device, wherein at least one of the image primary colors varies as a function of at least two detected primary colors.  
         [0010]     It is an aspect of the present invention to provide a method and system for the correction of colors in a digital image of a real-life object, by implementing a data structure that relates acquired digital color values to corrected digital color values useful in producing a digital image, wherein said data structure was modified by a process comprising: comparing a real-life target of a first luminance to a first generated image, the first generated image being displayed using color values derived from the data structure to correspond to the acquired digital color values originating from the digital image capture device, altering the data structure if necessary until a color of the real-life target of the first luminance and the corresponding color of the first generated image match, comparing a second real-life target of a second luminance to a second generated image, the second generated image being displayed using color values derived from the altered data structure to correspond to the acquired digital color values originating from the digital image capture device, and altering the data structure if necessary until a color of the real-life target of the second luminance and the corresponding color of the second generated image match. It is another aspect of the invention to perform multiple comparison and alteration iterations for the same or different luminances.  
         [0011]     It is also an aspect of the present invention to provide a method and system for better rendering and ameliorating the colors of an image comprised of at least three primary colors derived from the primary color information acquired by an image recording device, by manipulation of the primary color values or luminance values of the reproduced image in accordance with the principles elucidated hereinafter. The manipulation can include acquiring a reference digital image of a real-life, physical reference target on a viewing monitor; and comparing at least one color in the reference digital image with a corresponding color in the real-life reference target. By real-life reference target or physical reference target, we mean the physical object that is the subject of a digital image, i.e., the object whose likeness is reproduced in a digital image displayed on a viewing device or on printed media. The manipulation can include calibrating the viewing monitor and environmental conditions. The manipulation can include obtaining the uncorrected primary color values using a digital image capture device that defines the uncorrected primary colors in an additive RGB color space. As noted above, in this way, the method provides for color correcting an acquired digital reference image by establishing a simultaneous viewing evaluation to determine the color fidelity of the acquired image and the original reference target.  
         [0012]     It is an aspect of the invention to store a first, second, and third color detected intensity of light measured by a digital image recording device, and replace the first, second, and third color detected intensities by a first, a second, and a third corrected color intensity, wherein each of the three corrected color intensities is a function of the value of at least two of the first, second and third detected color intensities, and output the first, second and third corrected color intensities for a data receiving device, which may be a display device or a storage medium, to include a magnetic, optical, or electronic storage medium. It is an aspect of the present invention to replace the first, second, and third color detected intensities by a first, a second, and a third corrected color intensity in accordance with an explicit relationship, to include a lookup table, derived by comparative analysis. It is an aspect of the invention to replace detected intensities and output corrected color intensities using electrical paths.  
         [0013]     It is another aspect of the present invention for the explicit relationship to be determined by acquiring a reference digital image of a real-life reference target on a viewing monitor and comparing at least one color in the reference digital image with a corresponding color in the real-life reference target. It is an aspect that the explicit relationship be derived by a Digital Color Fidelity process, as described herein.  
         [0014]     It is an aspect of the invention for systems and devices involved in manipulating the colors of digital images to be part of computers, semiconductor chips, display devices, to include computer monitors, digital television, cellular telephones, and digital video telephones, and apparatus that produce images on a printed medium, to include printers and facsimile machines.  
         [0015]     The features and advantages of the present invention will be more readily apparent and understood from the following detailed description of the invention, which should be read in conjunction with the accompanying drawings and the claims appended to the end of the detailed description. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0016]      FIG. 1  is a diagram showing the three color matching functions {overscore (x)}, {overscore (y)}, {overscore (z)}, of CIE XYZ.  
         [0017]      FIG. 2  is an exemplary color correction procedure according to the present invention.  
         [0018]      FIG. 3  shows a Gretag MacBeth Color Checker.  
         [0019]      FIG. 4  is an exemplary color evaluation procedure according to the present invention.  
         [0020]      FIG. 5  shows a subtractive CMY color model.  
         [0021]      FIG. 6  shows an exemplary evaluation and correction procedure according to the present invention.  
         [0022]      FIG. 7  shows the relationship between the uncorrected and corrected primary color values that exist in an uncorrected color space and a corrected color space, respectively.  
         [0023]      FIG. 8  shows various devices to capture, store, and reproduce images as well as ameliorate said image colors according to one embodiment.  
         [0024]      FIGS. 9A, 9B , and  9 C illustrate devices that can modify color data to more accurately render images according to various embodiments of the present invention. 
     
    
     DETAILED DESCRIPTION  
       [0025]     For purposes of illustration only, and not to limit the scope of the present invention, the invention will be explained with reference to the embodiments of the invention indicated in the drawings. One skilled in the art would understand that the present invention is not limited to the specific examples disclosed and can be more generally applied to methods and systems for relating the color of digital images to the primary color intensities detected by digital capture devices. Furthermore, as understood by one skilled in the art, the primary colors referred to herein are defined by the system or system user, and can be, for instance, an orthogonal set of three colors for a particular color space, like RGB or CMY, or, alternatively, the primary colors are arbitrarily chosen and are nonorthogonal (e.g., CMY or CMYRGB).  
         [0026]     Referring to  FIG. 2 , a flow chart showing the functionality of an exemplary color correction procedure  205  is illustrated. Color correction procedure  205  is a method of comparative analysis (i.e., comparative color analysis). Color correction procedure  205  begins at start step  210  and proceeds to target acquisition step  215 , in which a digital image of a reference target is obtained. Then, the color correction procedure  205  proceeds to calibration step  220 , in which a viewing monitor, as well as environmental variables and conditions are calibrated and normalized. Then, evaluation step  225  is executed, in which the digital image of the reference target is evaluated and corrected. Using the results of the color correction and evaluation step  225 , a repeatable procedure for color correction is constructed in procedure construction step  230 . Then, color correction procedure  205  exits at exit step  235 .  
         [0027]     As described above, target acquisition step  215  acquires a digital image of a reference target, which may be any physical, real-life object, picture, drawing, etc., that is capable of being photographed and compared to the digital image of the reference target once acquired. The reference target may include, for example, a soda can, a soda bottle, a trademark, a photograph, a color card, a monkey, etc. One such possible reference target is the industry standard Gretag MacBeth Color Checker  340 , as shown in  FIG. 3 .  
         [0028]     Gretag MacBeth Color Checker  340  includes  24  colored squares  345 , including shades of color  350 , as well as a gray scale  355  from white to black. It is considered that the Gretag MacBeth Color Checker  340  is a good reference target because it is made of pure pigments, which are consistent in color.  
         [0029]     Any standard recording device may be used to acquire the digital image, such as a digital camera, camcorder, or scanner. In one exemplary embodiment according to the present invention, an eyelike MF digital camera back is used, the camera back housing a Phillips semiconductor CCD attached to a Rollei X-Act camera body using a Rodenstock 105 mm lens with a shutter speed of 1/250 at aperture f8.  
         [0030]     The environmental lighting conditions within which the digital image is acquired should be normalized and calibrated to equalize color density and to help reduce color cast caused by camera filtration and lighting conditions. If the Gretag MacBeth Color Checker  340  is used as the reference target, for example, illumination may be adjusted so that the white target  360  on the Gretay MacBeth Color Checker  340  measures at a value between 240 and 253 RGB (where each color has a range, in this example, of from 0 to 255). Illumination is provided using a Hensel Studiotechnik Strobe set at a color temperature of substantially 5400 degrees Kelvin and a softbox operating at 2300 Watts, to evenly illuminate the reference target Gretag MacBeth Color Checker  340 . The white target  360  can be balanced using conventional methods, such as by employing proprietary software packaged with the digital camera used to acquire the digital image.  
         [0031]     The digital image can be recorded in any digital format, such as pdf, TIF, jpeg, or a proprietary format, with or without compression. In one exemplary embodiment, the digital image is recorded in TIF format with no data compression.  
         [0032]     After the digital image of the reference target is obtained in target acquisition step  215 , environmental variables are calibrated in calibration step  220 , so that the evaluation of the digital image in evaluation step  225  is not corrupted by ambient lighting conditions, monitor settings, etc. The environmental calibration step  220  is the calibration of the viewing environment, including calibration of a computer monitor on which the digital image will be evaluated. Monitor calibration can help ensure that the monitor is properly displaying the digital image of the reference target relative to the environment in which the monitor is viewed.  
         [0033]     Before calibration of the monitor begins, however, the monitor should be turned on for at least half an hour to help ensure the stability of its display, after which the viewing environment should be calibrated, as described below. Then, the background color of the monitor should be set to a light neutral gray to help prevent the background color from interfering with the observer&#39;s color perception while calibrating the monitor. The hardware white point temperature of the monitor should be set in accordance with the type of monitor being used, so that the monitor exhibits a sufficiently high color temperature to better display the color space (e.g., additive RGB) used to display images. For example, with a Sony Trinitron Multiscan E400 monitor the hardware white point color temperature is set to approximately 9300 degrees Kelvin.  
         [0034]     Furthermore, the environmental illumination should be set before monitor calibration to help ensure the best monitor calibration and color evaluation. The environmental illumination can be set to between 6000 and 7000 degrees Kelvin (i.e., the color temperature of normal diffuse daylight); for a diffuse daylight color profile the illumination is set to approximately 6550 Kelvin, as measured using a Minolta Color Meter IIIF. The illumination is important, since an observer&#39;s eye adapts to the brightest source of light, which should be the viewing monitor.  
         [0035]     After the monitor&#39;s hardware white point is set and the viewing environment calibrated, monitor calibration is performed. Monitor calibration can include, for example, calibration of the monitor&#39;s contrast, brightness, gamma (midtones), and color balance to optimal settings. These settings are then used to characterize or create a profile (e.g., an ICC profile) for the monitor. To help determine these optimal settings, any conventional gamma adjustment tool can be used, such as the Adobe Gamma Control Panel of Adobe Photoshop software, which is produced by Adobe Systems, Inc. of Delaware.  
         [0036]     Referring again to  FIG. 2 , after calibration step  220 , evaluation step  225  of the color correction procedure  205  is executed. In this step, the colors of the digital image produced from the real-life reference target are evaluated and compared to the appearance of the real-life reference target itself. During this evaluation step, the viewing conditions should remain approximately similar to those used in calibrating the monitor, so that the evaluation of the digital image will not be corrupted, for example, by changes in illumination. In one exemplary embodiment according to the present invention, evaluation step  225  is performed in a white light viewing booth.  
         [0037]     Referring now to  FIG. 4 , there is seen an exemplary evaluation procedure  400  for execution in evaluation step  225  of the color correction procedure  205 .  
         [0038]     The evaluation procedure  400  begins at start step  405  and proceeds to basic evaluative definition step  410 , in which a set of basic evaluative colors is defined for evaluation and correction by the color correction procedure  205  according to the present invention. In one exemplary embodiment, red, green, and blue are selected as the set of basic evaluative colors. In another exemplary embodiment, red, green, blue, and yellow (RGBY) are selected. However, it should be appreciated that other colors may be selected for the set of basic evaluative colors, and the set of basic evaluative colors may contain any number of colors. For example, the set of basic evaluative colors may be selected in accordance with a set of colors provided by a customer, for example, a set of colors that may be identified with a particular product, such as 7-UP green or Coca Cola Red. In this manner, an exemplary color correction procedure  205  according to the present invention may preserve the likeness of a customer&#39;s product, thereby “normalizing” the color correction procedure  205  to a particular set of colors deemed important to the customer and, as such, worthy of more accurate correction.  
         [0039]     After the set of basic evaluative colors is selected in evaluative color definition step  410 , an expansion step  415  is executed, in which a selected one of the basic evaluative colors is expanded to fit the entire viewing surface of the monitor.  
         [0040]     Next, evaluate and correct step  420  is executed, in which the basic evaluative color selected in expansion step  415  is evaluated and corrected.  
         [0041]     Then, a query step  425  determines whether all colors in the set of basic evaluative colors have been evaluated and corrected. If not, a new color in the set of basic evaluative colors is selected in color selection step  430 , this color then being evaluated and corrected in evaluate and correct step  420 . After all the basic evaluative colors have been corrected once, query step  425  can direct step  430  to perform another iteration through the set of basic evaluative colors. Step  430  will select for a second time a color in the set of basic evaluative colors, this color then being re-evaluated and corrected in evaluate and correct step  420 . After all the basic evaluative colors have been corrected twice, step  425  can determine an additional iteration. Step  425  can require a number of iterations pre-determined by the system user, or step  425  can determine if another iteration is necessary based upon the corrections made to the set of basic evaluative colors in the previous iteration. If the query indicates that the iteration is completed, the evaluation and correction procedure exits at exit step  435 . In another embodiment, only one iteration cycle through the set of basic evaluative colors is performed.  
         [0042]     The evaluate and correct step  420  operates to correct for color variations between the digital image of the reference target and the real-life reference target itself. For this purpose, an observer (e.g., an expert color observer or group of observers trained in the art of color comparison) compares the color of at least a portion of the digital image to the color of the corresponding portion of the real-life reference target itself, and modifies the color of the digital image color portion to better match the corresponding portion of the real-life reference target.  
         [0043]     In one embodiment, a subtractive CMY evaluation and correction procedure is used to correct color variations between the digital image of the reference target and the real-life reference target itself. For this purpose, there is seen a discriminative CMY color model  510  in  FIG. 5 . Color model  510  may be used by an observer to evaluate the color of, for example, the digital image of the reference target. Color model  510  displays both the additive primary colors red  515 , green  520 , and blue  525 , as well as their corresponding subtractive primaries cyan  530 , magenta  535 , and yellow  540 . Additionally, the model  510  displays a gray scale with reference to neutral gray  545 .  
         [0044]     In this manner, the observer evaluates one (e.g., red) of the basic evaluative colors selected in step  410 , which also exists in the digital image and the real-life reference target itself. Then, the observer compares the (red) in the digital image to the corresponding (red) of the real-life reference target. Using, for example, a subtractive CMY correction procedure, the observer may, for example, add cyan (or subtract both magenta and yellow) to the digital image if the (red) of the digital image is too red as compared to the corresponding (red) of the real-life reference target. An exemplary list of corrective color combinations for a subtractive CMY evaluation and correction process are listed below in the following chart:  
                                               Basic   Subtractive   Subtractive   Additive   Additive       color   Corrective   Corrective   Corrective   Corrective       Selected   color   color   color   color       in Step   combination   combination   combination   combination       410   choice 1   choice 2   choice 3   choice 4                   Too Cyan   Subtract Cyan   Add both   Add Red   Subtract           (−Cy)   Magenta and   (+Rd)   both Green               Yellow       and Blue               (+Mg, +Yl)       (−Gr, −Bl)       Too Blue   Add Yellow   Subtract both   Subtract   Add both           (+Yl)   Cyan and   Blue (−Bl)   Red and               Magenta       Green               (−Cy, −Mg)       (+Rd, +Gr)       Too Green   Add Magenta   Subtract both   Subtract   Add both           (+Mg)   Cyan and   Green   Red and               Yellow   (−Gr)   Blue               (−Cy, −Yl)       (+Rd, +Bl)       Too Red   Add Cyan   Subtract both   Subtract Red   Add both           (+Cy)   Magenta and   (−Rd)   Green and               Yellow       Blue               (−Mg, −Yl)       (+Gr, +Bl)       Too   Subtract   Add both Cyan   Add Green   Subtract       Magenta   Magenta (−Mg)   and Yellow   (+Gr)   both Red and               (+Cy, +Yl)       Blue                       (−Rd, −Bl)       Too   Subtract   Add both Cyan   Add Blue   Subtract       Yellow   Yellow (−Yl)   and Magenta   (+Bl)   both Red and               (+Cy, +Mg)       Green                       (−Rd, −Gr)       Too Dark   Add neutral   —           density       Too Light   Subtract   —           neutral density                  
 
         [0045]     Thus, for example, if a target color in the digital image is both too cyan and too blue, an observer may correct the color discrepancy, for example, by subtracting cyan (−Cy) (to correct for too cyan) and adding yellow (+Y1) (to correct for too blue). Alternatively, instead of subtracting cyan to correct for too cyan, the observer may add both magenta and yellow (+Mg, +Y1) (to correct for too cyan). Further, instead of adding yellow to correct for too blue, the observer may subtract both cyan and magenta (−Cy, −Mg) (to correct for too blue). This results in four choices to correct for a basic evaluative color using the “subtractive primaries” CMY: 
        a) subtracting cyan to correct for too cyan and adding yellow to correct for too blue (−Cy, +Y1);     b) subtracting cyan to correct for too cyan and subtracting both cyan and magenta to correct for too blue (−−Cy, −Mg);     c) adding both magenta and yellow to correct for too cyan and subtracting both cyan and magenta to correct for too blue (−Cy, +Y1); and     d) adding both magenta and yellow to correct for too cyan and adding yellow to correct for too blue (+Mg, ++Y1).        
 
         [0050]     The observer may, for example, perform all four color corrections separately, and then choose the color correction that appears to better correct for the color discrepancy.  
         [0051]     Referring now to  FIG. 6 , there is seen an exemplary evaluation and correction procedure  600  of step  420  of  FIG. 4 . Evaluation and correction procedure  600  begins at cyan/red query step  605 , in which the observer evaluates the digital image of the reference target and determines whether the basic evaluative color selected in step  410  (which is also present in the digital image of the reference target) is too cyan, too red, or neither too cyan nor too red. If the observer determines that the basic evaluative color in the digital image is too red, magenta/yellow query step  610  is executed. Alternatively, if the observer determines that the basic evaluative color in the digital image is too cyan, blue/green query step  615  is executed. Or, if the observer determines that the basic evaluative color in the digital image is neither too red nor too cyan, light/dark query step  620  is executed.  
         [0052]     If the observer determines that the basic evaluative color in the digital image is too red, magenta/yellow query step  610  is executed, in which the observer determines whether the basic evaluative color in the digital image is too magenta, too yellow, or neither too magenta nor too yellow. If the observer determines that the basic evaluative color in the digital image is too magenta, red/magenta correction step  625  is executed, in which the excess red and magenta is corrected for by one of the following choices:  
                                                   Basic evaluative color both   Resulting Color Correction           too Red and too Magenta   Combination                           Add Cyan to correct for too   (+Cy, −Mg)           Red (+Cy); subtract Magenta           to correct for too Magenta           (−Mg)           Add Cyan to correct for too   (++Cy, +Yl)           red (+Cy); add both Cyan and           Yellow to correct for too           Magenta (+Cy, +Yl)           Subtract both Magenta and   (−−Mg, −Yl)           Yellow to correct for too Red           (−Mg, −Yl); subtract Magenta           to correct for too Magenta           (−Mg)                      
 
         [0053]     The observer can, for example, perform all three of the above color corrections and then choose which of the three choices appears to best correct for the color discrepancy.  
         [0054]     Alternatively, if the observer determines, from magenta/yellow query step  610 , that the basic evaluative color in the digital image is both too red and too yellow, red/yellow correction step  630  is executed, in which the excess red and yellow is corrected for by one of the following choices:  
                                                   Basic evaluative color both   Resulting Color Correction           too Red and too Yellow   Combination                           Add Cyan to correct for too Red   (+Cy, −Yl)           (+Cy); subtract Yellow to           correct for too yellow (−Yl)           Add Cyan to correct for too Red   (++Cy, +Mg)           (+Cy); add both Cyan and           Magenta to correct for too           Yellow (+Cy, +Mg)           Subtract both Magenta and   (−Mg, −−Yl)           Yellow to correct for too Red           (−Mg, −Yl); subtract Yellow to           correct for too Yellow (−Yl)                      
 
         [0055]     The observer can, for example, perform all three of the above color corrections and then choose which of the three choices appears to best correct for the color discrepancy.  
         [0056]     Alternatively, if the observer determines, from magenta/yellow query step  610 , that the basic evaluative color in the digital image is too red, but neither too magenta nor too yellow, red correction step  635  is executed, in which the excess red is corrected for by one of the following choices:  
                                                       Resulting Color Correction           Basic evaluative color too Red   Combination                           Add Cyan to correct for too Red   (+Cy)           (+Cy)           Subtract both Magenta and   (−Mg, −Yl)           Yellow to correct for too Red           (−Mg, −Yl)                      
 
         [0057]     The observer can, for example, perform both of the above color corrections and then choose which of the two choices appears to best correct for the color discrepancy.  
         [0058]     If the observer determines, in cyan/red query step  605 , that the basic evaluative color in the digital image is too cyan, blue/green query step  615  is executed, in which the observer determines whether the basic evaluative color in the digital image is too blue, too green, or neither too blue nor too green. If the observer determines that the basic evaluative color in the digital image is too blue, cyan/blue correction step  645  is executed, in which the excess cyan and blue is corrected for by one of the following choices:  
                                                   Basic evaluative color both too   Resulting Color Correction           Cyan and too Blue   Combination                           Subtract Cyan to correct for too   (−Cy, +Yl)           Cyan (−Cy); add Yellow to correct           for too Blue (+Yl)           Subtract Cyan to correct for too   (−−Cy, −Mg)           Cyan (−Cy); subtract both Cyan           and Magenta to correct for too           Blue (−Cy, −Mg)           Add both Magenta and Yellow to   (+Mg, ++Yl)           correct for too Cyan (+Mg, +Yl);           add Yellow to correct for too Blue           (+Yl)                      
 
         [0059]     The observer can perform all three of the above color corrections and then choose which of the three choices appears to best correct for the color discrepancy.  
         [0060]     Alternatively, if the observer determines, from blue/green query step  615 , that the basic evaluative color in the digital image is both too cyan and too green, cyan/green correction step  650  is executed, in which the excess cyan and green is corrected for by one of the following choices:  
                                   Basic evaluative color both too   Resulting Color Correction       Cyan and too Green   Combination                   Subtract Cyan to correct for too Cyan   (−Cy, +Mg)       (−Cy); add Magenta to correct for too       Green (+Mg)       Subtract Cyan to correct for too Cyan   (−−Cy, −Yl)       (−Cy); subtract both Cyan and Yellow       to correct for too Green (−Cy, −Yl)       Add both Magenta and Yellow to   (++Mg, +Yl)       correct for too Cyan (+Mg, +Yl); add       Magenta to correct for too Green       (+Mg)                  
 
         [0061]     The observer can perform all three of the above color corrections and then choose which of the three choices appears to best correct for the color discrepancy.  
         [0062]     Alternatively, if the observer determines, from blue/green query step  615 , that the basic evaluative color in the digital image is too cyan, but neither too blue nor too green, cyan correction step  655  is executed, in which the excess cyan is corrected for by one of the following choices:  
                                                       Resulting Color Correction           Basic evaluative color too Cyan   Combination                           Subtract Cyan to correct for too   (−Cy)           Cyan (+Cy)           Add both Magenta and Yellow to   (+Mg, +Yl)           correct for too Cyan (+Mg, +Yl)                      
 
         [0063]     The observer can perform both of the above color corrections and then choose which of the two choices appears to best correct for the color discrepancy.  
         [0064]     It should be noted that, although the various exemplary embodiments described above recite specific color correction combinations for correcting color discrepancies in the set of basic evaluative colors, there exist an infinite number of color combinations to correct for a particular color discrepancy, and these color combinations may include one or more of an infinite number of colors. Accordingly, this description is not intended to be limited to the color combinations to those above, but rather is intended to cover any and all corrective color combinations for correcting color discrepancies in any of the basic evaluative colors selected in step  410 .  
         [0065]     After the selected one of the color correction steps  625 ,  630 ,  635 ,  645 ,  650 ,  655  is executed, the cyan/red query step  605  is repeated. If the observer determined, in cyan/red query step  605 , that the basic evaluative color in the digital image is neither too red nor too cyan, light/dark query step  620  is executed, in which it is determined whether the basic evaluative color in the digital image is too light or too dark. If the observer determines that the basic evaluative color in the digital image is too light, light correction step  665  is executed, in which the excess lightness of the basic evaluative color in the digital image is corrected for by subtracting neutral density. Alternatively, if the observer determined, in light/dark query step  620 , that the basic evaluative color in the digital image is too dark, dark correction step  670  is executed, in which the excess darkness of the basic evaluative color in the digital image is corrected for by adding neutral density. After executing step  665  or  670 , the cyan/red query step  605  is repeated.  
         [0066]     Alternatively, if the observer determined, in light/dark query step  660 , that the basic evaluative color in the digital image is neither too light nor too dark, the evaluation and correction procedure ends at exit step  675 .  
         [0067]     The evaluation and correction procedure  600 , begins at cyan/red query  605  and does not end until reaching step  675 , even though executing step  605  more than once before reaching step  675 . As shown in  FIG. 4 , the evaluation and correction procedure  600 , which is executed in step  420 , is performed once per iteration for each color in the selected group of colors defined in the evaluative definition step  410 .  
         [0068]     Once the evaluation and correction procedure is performed for all colors in the set of basic evaluative colors defined in step  410  of  FIG. 4 , the evaluation step  225  of  FIG. 2  ends, and the construction step  230  is executed. In construction step  230 , a repeatable procedure for color correction is constructed. For this purpose, the corrective color combinations produced by the evaluation and correction procedure  420  for each of the colors defined in step  410  may be written, along with interpolated values, if desired, to a corrective sequence file, which is be saved, for example, on the hard drive of a computer, a floppy disk, or any other storage medium. Alternatively, the corrective results from the above corrective procedures  205  and  420  can be implemented in hardware, such as, for example, discrete logic, a Field Programmable Gate Array (FPGA), or an Application Specific Integrated Circuit (ASIC). Whether implemented in hardware or software, however, the corrective color combinations for each of the colors defined in step  410  can be used to correct the color of any subsequent digital image, for example, a digital image of a flower, a monkey, a landscape, etc, by use of the explicit relationship discussed herein. After correction, the colors of the image are more faithful to the colors of the real-world target object, as perceived by a qualified observer.  
         [0069]     It should be noted that, although the various exemplary embodiments described hereinabove generally teach how evaluation and correction procedures can be used to improve the color fidelity of an image, the present invention is not limited to the above evaluative, iterative procedure. Instead, in one embodiment of the present invention depicted in  FIG. 7 , there is a relationship  706  between uncorrected and corrected primary color luminance or intensity values, which exist, for example, in an uncorrected color space  705  and a corrected color space  707 . The explicit relationship  706  between the corrected and uncorrected colors can be derived by the evaluative procedures taught herein, or it can have been derived by another method, but the relationship  706  is explicitly defined in for example, a matrix, a transformation table, a lookup chart, a computer algorithm, an electronic circuit, or in another explicit relationship known to one skilled in the art. The relationship  706  can also include values that were interpolated between color values that were actually corrected by the evaluative procedures described above, or the relationship  706  can be adapted to permit an algorithm or a processor to interpolate color values from those included in relationship  706 .  
         [0070]     The relationship  706  is informed by the knowledge that when an image capture device detects an image of a hue (e.g., a red hue), a change of the illumination of that hue (e.g., a change in the intensity of the red light) is perceived by the human eye to be accompanied by a change in chromaticity; for a digital image to reproduce the colors of the changed illumination with fidelity, the intensity values of the primary colors produced by the display device must, in general, vary even when the change in intensity is detected by the capture device to be occurring only along one primary color axis. The same is true for different luminance values of a hue as for a change in illumination of a hue. The relationship  706  can map each uncorrected primary color luminance value in the space  705  to a corrected primary luminance color value in the corrected color space  707 .  
         [0071]     In one embodiment, a color corrected digital image has plural colors, and the colors themselves are, in general, composed of at least three corrected primary colors according to a color model. The corrected primary colors are related by an explicit relationship, as described hereinabove, to the uncorrected primary colors derived from a digital image capture device, wherein each of the corrected primary colors are multiply dependent upon (i.e., can be each a multivariable function of) the uncorrected primary colors. Alternatively, fewer than all of the corrected primary colors each vary as a function of all of the uncorrected primary colors, and in another embodiment, only one corrected primary color is a function of all the uncorrected primary colors. In one embodiment, a corrected primary color can be a function of fewer than all the uncorrected primary colors. In another embodiment, at least one corrected primary color varies as a function of at least two uncorrected primary colors.  
         [0072]     The tristimulus values of CIE are based upon a sampling from incandescent sources with color added using external filtration. The RGB model, describes the production of color using phosphorescent sources. The chromaticity of these two systems, CIE and RGB, is not the same. In another embodiment of the present invention, the characterization of the CIE data by the color correction process of relating the corrected and uncorrected colors by an explicit relationship as described hereinabove is termed Digital Color Fidelity (“DCF”). DCF is a characterization of CIE data that defines the chromaticities of the hues of a color model (e.g., RGB or CMY) based on a method of comparative analysis, which results in a more visually color accurate digital image. DCF can be developed by the DCF process: comparing a digital image of a reference target to the real world reference target and adjusting the individual hues of the digitally rendered reference target to minimize the perceived differences between the two, as described hereinabove. In particular, the DCF Process is a process for color correcting a digital image by establishing a simultaneous viewing evaluation for the express purpose of determining the color fidelity of an image recorded using a photoelectric sensor and the original subject of the recording.  
         [0073]     DCF produces hues, whose chromaticity is not perceptually uniform and not mathematically constant. The DCF characterization of the chromaticity of the hues differs from the default chromaticity of the hues in the RGB color model. In general, the DCF characterization of the chromaticity of the hues differs from the RGB default as follows: 
        Blue at low luminance values is darker and redder;     Blue at medium luminance values is equally light and redder;     Blue at high luminance values is darker and redder.     Green at low luminance values is lighter, redder, and bluer;     Green at medium luminance values is equally light, redder, and bluer;     Green at high luminance values is equally light, redder, and less blue.     Red at low luminance values is darker, less red, and bluer;     Red at medium luminance values is unchanged;     Red at high luminance values is equally light and less blue.     Yellow at low luminance values is lighter and greener;     Yellow at medium luminance values is equally light;     Yellow at high luminance values is equally light and less blue.     Magenta at low luminance values is equally light, greener, and bluer;     Magenta at medium luminance values is lighter and greener;     Magenta at high luminance values is lighter and greener.     Cyan at low luminance values is darker, redder, and less blue;     Cyan at medium luminance values is equally light and redder;     Cyan at high luminance values is unchanged.        
 
         [0092]     Referring to  FIG. 8 , in one embodiment of the present invention, the data comprising the digital image can be recorded by any image recording or image capture device  1100 , which can be a document scanner, a video telephone, a cellular telephone, a digital video recorder, and a digital camera, or another image capture device known to one skilled in the art. The color corrected digital image and related data can be stored before and after the color correction process that relates the corrected and uncorrected colors by an explicit relationship as described in conjunction with  FIG. 7 . The data can be stored on any volatile or non-volatile memory, and can be stored on any electronic, magnetic, or optical medium, including a MiniDisc, a CD  1102 , a floppy disk  1103 , a hard drive, a Flash RAM, or other storage device known to one skilled in the art. The color corrected digital image can be displayed on a visual display device  1104 , including a computer monitor, a television, and a telephone, and the color corrected image can be reproduced in a printed medium  1106 , including by a printer and a facsimile machine. The color corrected digital image can be transmitted over a computer network  1108 . The systems and methods of the present invention do not preclude translating the digital image into another color model having different primary colors either before or after the color correction process, using, for example, a computer system  1110 .  
         [0093]     In one embodiment of the present invention, the color correction process of relating the corrected and uncorrected colors by an explicit relationship as described in conjunction with  FIG. 7  above occurs on a computer (e.g., on computer  1110  in  FIG. 8 ), on a network server, or over a network (e.g., on computer network  1108 ). Referring to  FIG. 9A , in one embodiment, the color correction process occurs on the digital image capture device  1202 . Alternatively, referring to  FIG. 9B , the color correction process occurs at the image display device  1204  or at the printer (e.g., printer  1106  in  FIG. 8 ). The explicit relationship and the algorithm to replace the uncorrected color data by the corrected color data as specified by the relationship can be stored on a computer, on data storage media, or, referring to  FIG. 9C , on a semiconductor chip  1206 .  
         [0094]     Having described the embodiments of the invention, it should be apparent that various combinations of embodiments may be made or modifications added thereto as is known to those skilled in the art without departing from the spirit and scope of the invention.