Patent Publication Number: US-8125696-B2

Title: Color processing apparatus and method thereof

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to color processing for correcting differences in color appearance. 
     2. Description of the Related Art 
     In order to match color representations between different media, e.g., a color displayed on a monitor and a color on a printout, various color conversion methods have been proposed. For example, in order to achieve matching of color presentations between different media, there has been proposed a method of correcting correction factors such that the XYZ value of one medium corresponds with that of the other medium. 
     However, color appearances on different media do not always match even when their XYZ values correspond to each other. The color matching functions defined by Commission Internationale de l&#39;Eclairage (CIE) are based on the average values of a plurality of subjects (in other words, the vision sensitivity or chromatic vision characteristics of a standard observer), and color matching functions differ among individuals. Therefore, when an image is actually observed, its color appearances on different media do not always match. 
     Color matching functions are expressed as a function of light wavelength. Therefore, in order to correct the differences in color matching functions on an image with a high accuracy, it is desirable to correct the measurement data (to be referred to as spectral data or spectral image data, hereinafter) of the spectral radiance. 
     In addition, a technique of absorbing differences in color appearance due to differences in the human chromatic vision characteristics is also disclosed. This technique performs luminance correction on an HSV color space and color correction on an RGB color space such that the color appearance observed by one person who has chromatic vision characteristics with difficulty in distinguishing red from green becomes close to the color appearance observed by another person who has standard chromatic vision characteristics. 
     SUMMARY OF THE INVENTION 
     In the aspect, a color processing apparatus comprising: a setting section arranged to set personal color matching functions and referential color matching functions; an inputting section arranged to input spectral image data; and a corrector arranged to correct the spectral image data based on the personal color matching functions and the referential color matching functions. 
     According to the aspect, it is possible to correct differences in color appearance due to individual differences in color matching functions. 
     Further features of the present invention will become apparent from the following description of exemplary embodiments with reference to the attached drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram showing the arrangement of an image processing apparatus of the first embodiment; 
         FIG. 2  is a flowchart for explaining the processing of the first embodiment; 
         FIGS. 3 and 4  show an example of color matching function profile data; 
         FIG. 5  is a view showing examples of the feature amounts of color matching functions; 
         FIG. 6  is a view illustrating an example of a user interface for setting personal color matching functions and referential color matching functions; 
         FIG. 7  is a flowchart for explaining the process of a spectral image correction unit in the first embodiment; and 
         FIG. 8  is a flowchart for explaining the process of a spectral image correction unit in the second embodiment. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     Color processing of embodiments according to the present invention will now be described in detail with reference to the accompanying drawings. 
     First Embodiment 
     [Arrangement of Apparatus] 
       FIG. 1  is a block diagram showing the arrangement of an image processing apparatus (color processing apparatus) of the first embodiment. 
     Referring to  FIG. 1 , a spectral data obtaining unit  11  includes a measurement unit  17  which measures spectral data and a spectral data storage unit  18  which stores spectral data. The spectral data obtaining unit  11  can obtain the spectral image data of an object. 
     A color matching function setting unit  12  is used to set the profile data of personal color matching functions, and includes the following components. A color matching function storage unit  21  stores personal color matching functions. A color matching function database (DB)  23  stores one or more color matching functions. A color matching function selection unit  22  selects color matching functions from those stored in the color matching function DB  23 . A numerical value setting unit  24  is used to numerically set the feature amounts of color matching functions. The set color matching functions are displayed as a graph on a display unit  25 . An adjustment unit  26  provides a user interface for adjusting the shapes of color matching functions on the graph displayed on the display unit  25 . 
     A referential color matching function setting unit  13  is used to set the profile data of referential color matching functions, and includes a referential color matching function storage unit  31  which stores referential color matching functions. Note that the above-described color matching function DB  23 , color matching function selection unit  22 , numerical value setting unit  24 , display unit  25 , and adjustment unit  26  are used to set referential color matching functions. 
     A spectral image correction unit  14  includes a correction unit  41  and a spectral correction data storage unit  42 . The correction unit  41  is used to correct the spectral data of spectral image data stored in the spectral data storage unit  18 , based on the set personal color matching functions and the set referential color matching functions. The spectral correction data storage unit  42  stores the corrected spectral image data. 
     A color signal conversion unit  15  converts spectral image data stored in the spectral data storage unit  18  or spectral correction data storage unit  42  into a device signal of an image output device  16  such as a printer or a monitor, and outputs it to the image output device  16 . The image output device  16  displays or prints an image in accordance with the input device signal. 
     [Processing] 
       FIG. 2  is a flowchart for explaining the processing of the first embodiment. 
     The spectral data obtaining unit  11  obtains the spectral image data of an object to be color-converted and output to the image output device  16 , and stores the obtained spectral image data in the spectral data storage unit  18  (S 11 ). Note that spectral image data to be processed is not limited to spectral image data which is newly measured by the measurement unit  17 . Spectral image data stored in the spectral data storage unit  18  or various storage media may also be used. 
     The color matching function setting unit  12  sets personal color matching functions (color matching function profile data) by a method to be described later (S 12 ). 
     In order to match the color appearance observed by a person who has the set color matching function profile data as the chromatic vision characteristics, to the color appearance observed by another person, the referential color matching function setting unit  13  sets the color matching function profile data of the other person as referential color matching functions by a method to be described later (S 13 ). Note that since referential color matching functions serve as a target for matching color appearances, the color matching functions of a standard observer defined by CIE may be designated as referential color matching functions. 
     The personal color matching function profile data set in the past can be associated with an identification number or symbol and stored in the color matching function DB  23 . When the personal color matching function profile data to be set by the color matching function setting unit  12  or referential color matching function setting unit  13  exists in the color matching function DB  23 , it need not be newly set but desired data can be selected from the color matching function DB  23 . 
       FIG. 6  is a view illustrating an example of a user interface (UI) for setting personal color matching functions and referential color matching functions. This UI is displayed on the display unit  25  by the numerical value setting unit  24  and adjustment unit  26 . 
     An operator operates text combo boxes  104  and  101  to select personal color matching functions and referential color matching functions from the color matching function DB  23 . Alternatively, the operator operates numerical value input parts  105  and  103  to set personal color matching functions and referential color matching functions. The selected or set color matching functions are displayed as a graph on a graph display part  102 . The operator can adjust the color matching functions by adjusting the shapes of the color matching functions displayed as a graph by using a pointing device such as a mouse. When the setting and adjustment of the color matching functions are completed, the operator presses an OK button  106 . 
     When the setting and adjustment of the color matching functions are completed, the spectral image correction unit  14  corrects the spectral image data to be processed stored in the spectral data storage unit  18 , based on the two sets of color matching functions, and stores the corrected spectral image data in the spectral correction data storage unit  42  (S 14 ). This step will be described in detail later. 
     When the correction of the spectral image data is completed, the color signal conversion unit  15  converts the spectral image data stored in the spectral correction data storage unit  42  into a device signal of the image output device  16 , and outputs it to the image output device  16  (S 15 ). Note that conversion from spectral image data into a device signal of the image output device  16  can be performed by an arbitrary method. For example, when the image output device  16  is an RGB monitor, a device RGB signal can be obtained by using a lookup table (LUT) that describes the correspondence between the spectral image data and the device RGB value of the monitor. Alternatively, a device RGB signal may be obtained by searching for an RGB value, which reproduces the spectral image data, from a table that describes the relationship between the R, G, and B values input to the monitor and the spectral data of the light emitted by the monitor. Note that conversion from spectral image data into a device color signal is not limited to conversion into three colors such as an RGB signal, but conversion into any number of colors can be performed in accordance with the device. 
     Setting of Color Matching Function Profile Data 
       FIG. 3  is a graph showing an example of color matching function profile data. The color matching function profile data represents the relationship between the wavelength and the X, Y, and Z sensitivity characteristics. Setting of color matching function profile data is executed by one of the following methods. 
     In the first method, the color matching function profile data obtained by a color matching experiment or the like is stored in the color matching function DB  23 . An operator operates the color matching function selection unit  22  to select required color matching function profile data from the color matching function DB  23 , and the selected color matching function profile data is stored in the color matching function storage unit  21 .  FIG. 4  is a view showing an example of the color matching function profile data, in which the X, Y, and Z sensitivity data with respect to the wavelength are described. 
     In the second method, an operator operates the numerical value setting unit  24  to set the feature amounts of the color matching functions by numerical values.  FIG. 5  is a view showing examples of the feature amounts of the color matching functions. The peak position, height, half-width, and the like are set for each of the x, y, and z color matching functions. The set numerical values are stored in the color matching function storage unit  21  as the color matching function profile data. 
     In the third method, color matching functions are displayed as a graph on the display unit  25  and its shape is adjusted by the adjustment unit  26 . That is, the display unit  25  and adjustment unit  26  function as a UI for adjusting the shape of each color matching function by a mouse, keyboard, or the like. The adjusted color matching functions are stored in the color matching function storage unit  21  as the color matching function profile data. 
     Spectral Image Correction Unit 
       FIG. 7  is a flowchart for explaining the process of the spectral image correction unit  14 . 
     The spectral image correction unit  14  inputs personal color matching functions and referential color matching functions (S 21 ), and inputs and stores spectral image data in the spectral correction data storage unit  42  (S 22 ). 
     Next, the spectral image correction unit  14  extracts spectral data for one pixel in the raster order from the spectral image data stored in the spectral correction data storage unit  42  (S 23 ). The spectral image correction unit  14  then calculates, based on the referential color matching functions and spectral data, the color values (e.g., X, Y, and Z values Xr, Yr, and Zr) of the pixel of interest when the referential color matching functions are applied (first calculation) (S 24 ), by using: 
                     Xr   =       ∑     λ   =   380     780     ⁢       xr   ⁡     (   λ   )       ×     R   ⁡     (   λ   )             ⁢     
     ⁢     Yr   =       ∑     λ   =   380     780     ⁢       yr   ⁡     (   λ   )       ×     R   ⁡     (   λ   )             ⁢     
     ⁢     Zr   =       ∑     λ   =   380     780     ⁢       zr   ⁡     (   λ   )       ×     R   ⁡     (   λ   )                     (   1   )               
where xr(λ), yr(λ), and zr(λ) are the referential color matching functions; and
 
     R(λ) is the spectral data. 
     Next, the spectral image correction unit  14  calculates, based on the personal color matching functions and spectral image data, the color values (e.g., X, Y, and Z values Xp, Yp, and Zp) of the pixel of interest when the personal color matching functions are applied (second calculation) (S 25 ), by using: 
                     Xp   =       ∑     λ   =   380     780     ⁢       xp   ⁡     (   λ   )       ×     R   ⁡     (   λ   )             ⁢     
     ⁢     Yp   =       ∑     λ   =   380     780     ⁢       yp   ⁡     (   λ   )       ×     R   ⁡     (   λ   )             ⁢     
     ⁢     Zp   =       ∑     λ   =   380     780     ⁢       zp   ⁡     (   λ   )       ×     R   ⁡     (   λ   )                     (   2   )               
where xp(λ), yp(λ), and zp(λ) are the personal color matching functions.
 
     The spectral image correction unit  14  calculates the absolute values of the differences between the two sets of calculation results Xp, Yp, and Zp and Xr, Yr, and Zr, respectively (S 26 ).
 
 Mx=|Xp−Xr| 
 
 My=|Yp−Yr| 
 
 Mz=|Zp−Zr|   (3)
 
     The spectral image correction unit  14  compares each of the absolute values Mx, My, and Mz of the differences with a threshold th (S 27 ). When at least one of the absolute values of the differences is equal to or larger than the threshold a (Mx≧th, My≧th, or Mz≧th), the spectral image correction unit  14  corrects the spectral data of the pixel of interest stored in the spectral correction data storage unit  42 , based on the sum of the absolute values Mx, My, and Mz of the differences or the differences Xp−Xr, Yp−Yr, and Zp−Zr (S 28 ), and returns the process to step S 25 . 
     In correction of spectral data, spectral data R(λ) is adjusted such that the Xp, Yp, and Zp values become close to the Xr, Yr, and Zr value, respectively. In adjustment of spectral data, it is preferable to adjust the spectral data over the entire wave range such that the sum of the absolute values Mx, My, and Mz of the differences becomes minimum. However, for example, when the absolute value Mx of the difference is large, the spectral data corresponding to the wavelength near the peak of the color matching function x(λ) may be adjusted in accordance with the difference Xp−Xr. 
     On the other hand, when all the absolute values of the differences are smaller than the threshold th (Mx&lt;th, My&lt;th, and Mz&lt;th), the spectral image correction unit  14  advances the process to step S 29 . Alternatively, when all the absolute values of the differences between the Xr, Yr, and Zr values calculated in step S 24  and the Xp, Yp, and Zp values calculated from the spectral value corrected in step S 25 , respectively, are smaller than the threshold th, the spectral image correction unit  14  advances the process to step S 29 . Then, the spectral image correction unit  14  determines whether the above-described correction process is applied to all the pixels of the spectral image data (S 29 ). The processing from steps S 23  to S 28  is repeated until the above-described correction process is applied to all pixels. 
     In this manner, personal color matching functions and referential color matching functions are set, the Xp, Yp, and Zp values are calculated from the spectral data by using the personal color matching functions, and the Xr, Yr, and Zr values are calculated by using the referential color matching functions. Then, spectral image data is generated that includes the spectral correction data obtained by adjusting the spectral data corresponding to each pixel of the spectral image data such that the Xp, Yp, and Zp values correspond with the Xr, Yr, and Zr values, respectively (or the difference between each corresponding two values becomes smaller than a predetermined threshold). Accordingly, it is possible to make, with a higher accuracy, the color appearance obtained when a person, who corresponds to the set personal color matching functions, observes an image displayed or printed based on the spectral correction data close to the color appearance obtained when a person, who has the chromatic vision characteristics set as the reference or the standard chromatic vision characteristics, observes the same image. 
     Second Embodiment 
     The color processing of the second embodiment according to the present invention will now be described. Note that the same components as in the first embodiment are denoted by the same reference numerals in the second embodiment, and a detailed description thereof will not be repeated. 
       FIG. 8  is a flowchart for explaining the process of a spectral image correction unit  14  in the second embodiment. 
     The spectral image correction unit  14  inputs personal color matching functions and referential color matching functions (S 31 ), and inputs and stores spectral image data in a spectral correction data storage unit  42  (S 32 ). 
     Next, the spectral image correction unit  14  calculates the ratios of the personal color matching functions to the referential color matching functions (S 33 ).
 
 kx (λ)= xr (λ)/ xp (λ)
 
 ky (λ)= yr (λ)/ yp (λ)
 
 kz (λ)= zr (λ)/ zp (λ)   (4)
 
     The spectral image correction unit  14  then corrects each spectral data of the spectral image data by using the ratios calculated by equation (4) to obtain spectral correction data (S 34 ). For example, in order to match the appearance of X, the spectral data is corrected using:
 
 R ′(λ)= R (λ)· kx (λ)  (5)
 
where R(λ) is the spectral data before the correction; and
 
     R′(λ) is the spectral data after the correction. 
     The X value calculated using the personal color matching function xp(λ) and the corrected spectral image data R′(λ) corresponds with the X value calculated using the referential color matching function xr(λ) and the spectral image data R(λ) before the correction, as expressed by: 
     
       
         
           
             
               
                 
                   
                     
                       
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     In order to match the appearances of all the X, Y, and Z, spectral data is corrected using:
 
 R ′(λ)= R (λ)·{ kx (λ)× ky (λ)× kz (λ)}  (7)
 
Note that fine adjustment may be performed after the correction by equation (7), as needed.
 
     In this manner, the spectral data corresponding to each pixel of the spectral image data is corrected based on the ratios of the personal color matching functions to the referential color matching functions. Accordingly, it is possible to make, with a higher accuracy, the color appearance obtained when a person, who corresponds to the set personal color matching functions, observes an image displayed or printed based on the spectral correction data close to the color appearance obtained when a person, who has the chromatic vision characteristics set as the reference or the standard chromatic vision characteristics, observes the same image. 
     Embodiments 
     The present invention can be applied to a system constituted by a plurality of devices (e.g., host computer, interface, reader, printer) or to an apparatus comprising a single device (e.g., copying machine, facsimile machine). 
     Further, the present invention can provide a storage medium storing program code for performing the above-described processes to a computer system or apparatus (e.g., a personal computer), reading the program code, by a CPU or MPU of the computer system or apparatus, from the storage medium, then executing the program. 
     In this case, the program code read from the storage medium realizes the functions according to the embodiments. 
     Further, the storage medium, such as a floppy disk, a hard disk, an optical disk, a magneto-optical disk, CD-ROM, CD-R, a magnetic tape, a non-volatile type memory card, and ROM can be used for providing the program code. 
     Furthermore, besides above-described functions according to the above embodiments can be realized by executing the program code that is read by a computer, the present invention includes a case where an OS (operating system) or the like working on the computer performs a part or entire processes in accordance with designations of the program code and realizes functions according to the above embodiments. 
     Furthermore, the present invention also includes a case where, after the program code read from the storage medium is written in a function expansion card which is inserted into the computer or in a memory provided in a function expansion unit which is connected to the computer, CPU or the like contained in the function expansion card or unit performs a part or entire process in accordance with designations of the program code and realizes functions of the above embodiments. 
     In a case where the present invention is applied to the aforesaid storage medium, the storage medium stores program code corresponding to the flowcharts described in the embodiments. 
     While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions. 
     This application claims the benefit of Japanese Patent Application No. 2007-237260, filed Sep. 12, 2007, which is hereby incorporated by reference herein in its entirety.