Abstract:
Aspects of the present invention relate to systems and methods for performing white balance operations for an LED display backlight. Some aspects related to an iterative process wherein display backlight luminance and color are sampled at an intermediate resolution between the resolution of the LED backlight and the resolution of the LCD display. Some aspects relate to a process wherein r, g and b driving value differences are determined using a deconvolution technique.

Description:
FIELD OF THE INVENTION 
     Embodiments of the present invention comprise methods and systems for display backlight element white balance. 
     BACKGROUND 
     Some displays, such as LCD displays, have backlight arrays with individual elements that can be individually addressed and modulated. The displayed image characteristics can be improved by systematically addressing backlight array elements. 
     SUMMARY 
     Some embodiments of the present invention comprise methods and systems for performing white balance operations for an LED display backlight. Some aspects related to an iterative process wherein display backlight luminance and color are sampled at an intermediate resolution between the resolution of the LED backlight and the resolution of the LCD display. Some aspects relate to a process wherein r, g and b driving value differences are determined using a deconvolution technique. 
     The foregoing and other objectives, features, and advantages of the invention will be more readily understood upon consideration of the following detailed description of the invention taken in conjunction with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL DRAWINGS 
         FIG. 1  is a diagram showing a typical LCD display with an LED backlight array; 
         FIG. 2  is a flow chart showing exemplary steps in a white balance process of an embodiment of the present invention; 
         FIG. 3  is a diagram showing an exemplary test pattern of geometric display configuration; 
         FIG. 4  is a diagram illustrating an exemplary filtering method for obtaining target luminance values; 
         FIG. 5  is a diagram showing an exemplary contrast sensitivity function of the human visual system; 
         FIG. 6  is a diagram illustrating exemplary display geometry and sampling dimensions; and 
         FIG. 7  is a flow chart illustrating an exemplary iterative process for determining a backlight driving value difference. 
     
    
    
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     Embodiments of the present invention will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The figures listed above are expressly incorporated as part of this detailed description. 
     It will be readily understood that the components of the present invention, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of the embodiments of the methods and systems of the present invention is not intended to limit the scope of the invention but it is merely representative of the presently preferred embodiments of the invention. 
     Elements of embodiments of the present invention may be embodied in hardware, firmware and/or software. While exemplary embodiments revealed herein may only describe one of these forms, it is to be understood that one skilled in the art would be able to effectuate these elements in any of these forms while resting within the scope of the present invention. 
     Some embodiments of the present invention comprise systems and methods for accomplishing a white point balance process for an LED display backlight. In some embodiments, the LED white point balance can be performed without an LCD panel. In some embodiments, the white point balance can be performed with the LCD panel installed. In embodiments with the LCD panel, the LCD may be set to white to avoid an LCD gray tracking issue. 
     Some aspects of the systems and processes involved in white point balancing may be described in relation to  FIG. 1 , which shows an exemplary LED white balance system. In this exemplary system, a computing device  16 , such as a personal computer, may control LCD control circuitry  2  and the associated LCD  4 , LED control circuitry  8  and the associated LED backlight  6  and an imaging colorimeter  10 . In this exemplary system control from the computing device  16  may be achieved through connections,  12 ,  14  and  18 , which may comprise various wired and wireless connections. In some embodiments, the imaging colorimeter  10  may be connected to the computing device  16  via a universal serial bus (USB) connection. In some embodiments, the computing device  16  may be connected to the LED control circuitry  8  with a USB connection, a video cable connection such as a digital visual interface (DVI) connection, a video graphics array (VGA) cable or some other connection  14 . In some embodiments, the computing device  16  may be connected to the LCD control circuitry  2  with a USB connection, a video cable connection such as a digital visual interface (DVI) connection, a video graphics array (VGA) connection or some other connection  14 . In some embodiments, the computing device  16  may be connected to the imaging colorimeter  10 , LCD control circuitry  2  and/or the LED control circuitry  8  with a wireless connection. 
     In an exemplary white balance process, the LED backlight  6  is illuminated using initial LED driving values transmitted to the LED control circuitry  8  from the computing device  16  over a connection  14 . The imaging colorimeter  10  then measures the light output from the LED panel  6  and determines the chromaticity of the backlight  6 . The LCD panel  4  may or may not be present and, if present, may be set to a full white condition. Based on the measurements from the imaging colorimeter  10 , the LED backlight driving values may be adjusted to correct the chromaticity of the LED backlight  6 . This process may be repeated until the correct chromaticity is detected by the imaging colorimeter  10 . 
     Some embodiments of the present invention may be described with reference to  FIG. 2 , which shows a flow chart of an exemplary white balance algorithm for an LED display backlight. Initially, display parameters  20  may be established for the display. These display parameters may comprise geometric display parameters, such as the size, shape, orientation and number of LED blocks and/or LCD pixels. Geometrical calibration  22  may also be performed between the captured camera data and the display. In some embodiments, geometrical calibration  22  may comprise correlating captured camera/colorimeter pixels to display LED positions. 
     In some embodiments, color calibration  24  may also be performed. The color calibration process  24  may comprise calculation of one or more color conversion matrices, such as an RGB to XYZ matrix and its inverse XYZ to RGB matrix. 
     Following color calibration  24 , an iterative process  25  may be followed to achieve LED backlight white balance. This iterative process  25  may comprise display of the LED backlight set to a white value and measurement of the actual color of the backlight output  26 . Based on the measured luminance profile, a target luminance may then be determined  28  that minimizes the visible luminance variation (Mura). This may be based on reduced sensitivity at both low spatial frequencies and high spatial frequencies of the human visual system. 
     In some embodiments, the target color X and Z may be computed  30  with the desired chromaticity (e.g., x 0  and y 0 ). An exemplary process is expressed as Equation 1, below. In some embodiments, the difference in XYZ coordinates between the measured XYZ and target XYZ may also be determined  32 . An exemplary method for this step is expressed as Equation 2, below. In some embodiments, the iterative process  25  may then continue by obtaining  34  the corresponding normalized RGB, e.g., via Equation 3, below. In some embodiments, de-convolution may then be used  36  to determine the LED driving values r, g, and b, such as with the Equation 4, below. 
     In some embodiments, a new LED driving value may be determined  38 , such as by using Equation 5, below. In some embodiments, LED driving values may be normalized  40  to the maximum pulse width modulation (PWM) so that the led driving values are not out of range. 
     This iterative process  25 , which comprises steps numbered  26  through  40  in  FIG. 2 , as described above, may then be repeated until the target color is reached for the LED white balance algorithm. Further details of these step are described below. 
     In an exemplary embodiment comprising an LCD panel  4 , geometrical calibration  22  may be performed by displaying a grid pattern on the LCD  4  while the camera/colorimeter  10  captures the grid pattern and detects the grid position in the captured image. 
     Some aspects of some embodiments of the present invention may be described with reference to  FIG. 3 . In these embodiments, when no LCD  4  is present, the four corner LED blocks  50 ,  52 ,  54  and  56  may be turned on and then captured by the camera/colorimeter  10 . In some embodiments, perspective transformation may be used to map the captured image to the LED backlight position. In some embodiments, in addition to the LED backlight position, a center LED  58  or another LED that is not proximate to a display edge, may also be turned on. This non-edge or center LED  58  may be used to derive the point spread function (PSF) of the LED panel  6 . 
     In some embodiments, color calibration  24  may also be performed. The color calibration process  24  may comprise calculation of one or more color conversion matrices, such as an RGB to XYZ matrix and its inverse XYZ to RGB matrix. In some embodiments, this process may be performed using the following steps:
         1. Turn on R, G, and B backlight LEDs one at a time;   2. Capture the color with a colorimeter, e.g., a CA2000 imaging colorimeter;   3. Average the measured color (XYZ) and fill the RGB2XYZ matrix;   4. Calculate the XYZ2RGB matrix as the matrix inversion of the RGB2XYZ matrix.   In another embodiment of the present invention, a XYZ2RGB and RGB2XYZ matrices may be derived for each LED by the corresponding measured color values associated with that LED.       

     Embodiments of the present invention may also comprise the following iterative process.
         1. Display  26  ( FIG. 2 ) the white (set R G B so that the display output is close to the target white).   2. Measure the color of the display (e.g., CIE tri-stimulus values: X, Y, Z, and CIE chromaticity x, y). Note that the measured data may have a spatial resolution higher than the LED resolution.   3. Based on the measured luminance profile, determine  28  a target luminance that minimizes the visible luminance variation (Mura). This may be based on:
           a. reduced sensitivity at both low spatial frequencies and high spatial frequencies of the human visual system as shown in  FIG. 5 ; and   b. there is no need to correct luminance variation that cannot be seen by human visual system.   
               

     In some embodiments, the target luminance may be set to approximately the low-pass-filtered backlight luminance as illustrated in  FIG. 4 . 
     In some embodiments, the target color X and Z may be computed  30  with the desired chromaticity x 0  and y 0  using the following equation: 
     
       
         
           
             
               
                 
                   
                     
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                       target 
                     
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     In some embodiments, the difference in XYZ coordinates between the measured XYZ and target XYZ may be determined  32  with the following equation: 
     
       
         
           
             
               
                 
                   
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     In some embodiments, the corresponding normalized RGB may be obtained  34  with the following equation: 
     
       
         
           
             
               
                 
                   
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     In some embodiments, de-convolution may be used  36  to determine the LED driving values r, g, and b with the following equation: 
                     (           Δ   ⁢           ⁢   r               Δ   ⁢           ⁢   g               Δ   ⁢           ⁢   b           )     =     arg   ⁢           ⁢   min   ⁢     {             Δ   ⁢           ⁢   R     -     Δ   ⁢           ⁢   r   *   psf                   Δ   ⁢           ⁢   G     -     Δ   ⁢           ⁢   g   *   psf                   Δ   ⁢           ⁢   B     -     Δ   ⁢           ⁢   b   *   psf             }               (   4               
wherein * denotes the convolution operation.
 
     Aspects of some embodiments of the present invention may be explained with reference to  FIG. 6 , which illustrates the relative geometry of a typical display  60  and various sampling elements. The exemplary display  60  may comprise a backlight array with backlight LED elements having a size defined by backlight grid lines  62  and backlight element cells  63 , which are illuminated by a backlight element, such as a single LED. The display  60  may also comprise an LCD panel with pixels  66 , which are typically much smaller than the backlight LEDs  63 . For the purposes of some exemplary methods of embodiments of the present invention, an intermediate grid may also be established at a resolution that is between that of the LCD pixels  66  and the backlight LED elements  63 . This intermediate sampling grid may be defined by grid lines  64 . In some embodiments, sampling at the intermediate resolution may be performed by downsampling the LCD pixel values. In some embodiments, the intermediate resolution elements may be qualified as on-grid or off-grid based on their proximity to an LED grid defined by grid lines  68  that pass through the center points of the LED elements. If an intermediate element is on, adjacent to, or within a specified distance of an LED grid line  68 , that element may be considered to be on-grid. If the element does not meet the on-grid criterion, it is considered off-grid. 
       FIG. 7  further illustrates the de-convolution process. Since the de-convolution was done at a higher intermediate resolution than the LED resolution, each backlight location (x,y) is designated  80  as an LED (on-grid) location (ledGrid=1) or a no-LED (off-grid) location (ledGrid=0). The algorithm may iteratively change  82  the LED driving value (Δrgb) to minimize the difference {ΔRGB(x,y)−psf(x,y)*Δrgb i (x,y)}, where * denote the convolution operation. When a difference threshold is met  84  or a maximum number of iterations is reached, the process may be stopped and a new driving value difference is obtained  86 . 
     In some embodiments, a new LED driving value may be determined  38  using the following equation: 
     
       
         
           
             
               
                 
                   
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     In some embodiments, LED driving values may be normalized  40  to the maximum pulse width modulation (PWM) so that the led driving values are not out of range. 
     Steps numbered  26  through  40  in  FIG. 2 , as described above, may then be repeated until the target color is reached for the LED white balance algorithm. 
     The terms and expressions which have been employed in the foregoing specification are used therein as terms of description and not of limitation, and there is no intention in the use of such terms and expressions of excluding equivalence of the features shown and described or portions thereof.