KR20240022084A - Apparatus and Method for Compensating Mura - Google Patents

Abstract

A mura compensation device according to an embodiment of the present invention that detects mura in an image displayed through a display panel and compensates for the detected mura, wherein the test image supply unit supplies first image data and second image data to the display panel. ; and a test image capture unit that captures a first image and a second image displayed on the display panel in response to the first image data and the second image data, respectively.

Description

Mura compensating device and method for compensating Mura {Apparatus and Method for Compensating Mura}

Representative display devices that display images include liquid crystal displays (LCD) using liquid crystals and organic light emitting diodes (OLED) displays using organic light emitting diodes.

Such display panels may have defects in which bright spots or stains are visible in specific pixels or certain areas of the display panel due to non-uniformity in the manufacturing process.

The present invention is intended to solve the above-mentioned problems, and provides a mura compensation device and a mura compensation method to minimize defects in which bright spots or stains are recognized in specific pixels and some areas due to unevenness in the manufacturing process of the display panel. Make it an assignment.

The present invention is intended to solve the above-mentioned problems, and provides a mura compensation device and a mura compensation method to minimize defects in which bright spots or stains are recognized in specific pixels and some areas due to unevenness in the manufacturing process of the display panel. Make it an assignment.

A mura compensation device that detects mura in an image displayed through a display panel and compensates for the detected mura, comprising: a test image supply unit that supplies first image data and second image data to the display panel; and a test image capture unit that captures a first image and a second image displayed on the display panel in response to the first image data and the second image data, respectively, wherein the test image capture unit captures the first image. Characterized by capturing the first image during a first reference exposure time to generate first captured image data, and capturing the second image during a second reference exposure time different from the first reference exposure time to generate second captured image data. do.

The mura compensation device and mura compensation method according to an embodiment of the present invention can minimize defects in which bright spots or stains are visible in specific pixels and some areas due to unevenness in the manufacturing process of the display panel.

1 is a diagram illustrating a process for detecting mura in a display panel using a mura compensation device according to an embodiment of the present invention.
Figure 2 is a block diagram of a mura compensation device according to an embodiment of the present invention.
Figures 3A to 3C are diagrams showing a process of generating representative image data for each gray level according to an embodiment of the present invention.
Figure 4 is a graph showing a low-gray-scale mura compensation equation for generating low-gray-scale representative image data according to an embodiment of the present invention.
Figure 5 is a graph showing the process of generating low gray level representative image data using a low gray level mura compensation equation according to an embodiment of the present invention.
Figure 6 is a flow chart of the process of generating representative image data for each gray level according to an embodiment of the present invention.
Figure 7 is a flow chart of the process of calculating a mura compensation equation for each gray level and generating low gray level representative image data according to the calculated mura compensation equation according to an embodiment of the present invention.

Like reference numerals refer to substantially the same elements throughout the specification. In the following description, detailed descriptions of configurations and functions known in the technical field of the present invention and cases not related to the core configuration of the present invention may be omitted. The meaning of terms described in this specification should be understood as follows.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and will be implemented in various different forms. The present embodiments only serve to ensure that the disclosure of the present invention is complete and that common knowledge in the technical field to which the present invention pertains is not limited. It is provided to fully inform those who have the scope of the invention, and the present invention is only defined by the scope of the claims.

The shapes, sizes, proportions, angles, numbers, etc. disclosed in the drawings for explaining embodiments of the present invention are illustrative, and the present invention is not limited to the matters shown. Like reference numerals refer to like elements throughout the specification. Additionally, in describing the present invention, if it is determined that a detailed description of related known technologies may unnecessarily obscure the gist of the present invention, the detailed description will be omitted.

When 'includes', 'has', 'consists of', etc. mentioned in this specification are used, other parts may be added unless 'only' is used. When a component is expressed in the singular, the plural is included unless specifically stated otherwise.

When interpreting a component, it is interpreted to include the margin of error even if there is no separate explicit description.

In the case of a description of a temporal relationship, for example, if a temporal relationship is described as 'after', 'successfully after', 'after', 'before', etc., 'immediately' or 'directly' Unless used, non-consecutive cases may also be included.

Although first, second, etc. are used to describe various components, these components are not limited by these terms. These terms are merely used to distinguish one component from another. Accordingly, the first component mentioned below may also be the second component within the technical spirit of the present invention.

The term “at least one” should be understood to include all possible combinations from one or more related items. For example, “at least one of the first, second, and third items” means each of the first, second, or third items, as well as two of the first, second, and third items. It can mean a combination of all items that can be presented from more than one.

Each feature of the various embodiments of the present invention can be combined or combined with each other, partially or entirely, and various technological interconnections and operations are possible, and each embodiment can be implemented independently of each other or together in a related relationship. It may be possible.

Hereinafter, with reference to FIGS. 1 to 5, a mura compensation device according to an embodiment of the present invention will be described in detail.

FIG. 1 is a diagram showing a process for detecting mura in a display panel using a mura compensation device according to an embodiment of the present invention, and FIG. 2 is a block diagram of a mura compensation device according to an embodiment of the present invention. 3A to 3C are diagrams illustrating a process of generating representative image data for each gray level according to an embodiment of the present invention, and FIG. 4 is a diagram illustrating a low gray level murabo for generating low gray level representative image data according to an embodiment of the present invention. This is a graph that represents common sense. Figure 5 is a graph showing the process of generating low gray level representative image data using a low gray level mura compensation equation according to an embodiment of the present invention.

Referring to FIG. 1, the mura compensation device 200 provides test image data to the display panel 100, measures mura by taking an image displayed on the display panel 100, and performs compensation to compensate for the measured mura. The value is calculated and provided to the driver 300 that drives the display panel 100.

At this time, the display panel 100 can display an image of a certain gray level using light emitted from the backlight unit. The display panel 100 may be a flat display panel, such as a Liquid Crystal Display (LCD) panel or an Organic Light Emitting Diode (OLED) panel.

Although not shown, the display panel 100 includes a plurality of gate lines, a plurality of data lines, and a plurality of pixels. Each of the plurality of gate lines receives a scan pulse. Each of the plurality of data lines receives a data signal during the display period (DP). Each of the plurality of gate lines and the plurality of data lines is positioned to intersect each other on the substrate to define a plurality of pixels. Each of the plurality of pixels may include a thin film transistor connected to adjacent gate lines and data lines, a pixel electrode connected to the thin film transistor, and a storage capacitor connected to the pixel electrode.

A pixel of the display panel 100 may include subpixels of a first color, a second color, and a third color, and may further include subpixels of a fourth color. At this time, the first color may be one of red®, green (G), and blue (B), and the second color may be another one of red®, green (G), and blue (B), respectively. 3 The color may be another one of red®, green (G) and blue (B). Additionally, the fourth color may be white (W). For example, each subpixel may be formed repeatedly in the row direction or may be formed in a 2*2 matrix. At this time, a color filter corresponding to each color is disposed in each of the first, second, and third color subpixels, while a separate color filter is not disposed in the fourth color subpixel. In one embodiment, subpixels of the first color, second color, third color, and fourth color may be formed to have the same area ratio, but may also be formed to have different area ratios.

The display panel 100 may display bright spots or spots in some pixels or some areas due to unevenness in the manufacturing process. According to an embodiment of the present invention, the display quality of the display panel 100 can be improved by compensating for the display defect of the display panel 100.

As shown in FIGS. 1 and 2, the mura compensation device 200 according to an embodiment of the present invention includes a test image supply unit 210, a test image capture unit 220, and a mura compensation unit 230. .

The test image supply unit 210 provides image data to the display panel 100. According to one embodiment of the present invention, the test image supply unit 210 may provide a plurality of image data corresponding to each gray level range to the display panel 100. At this time, each of the plurality of image data may be composed of image data input to each pixel of the display panel 100. Specifically, as shown in FIG. 2, the test image supply unit 210 supplies first to third low gray scale image data (L_IMG1, L_IMG2, L_IMG3) and first to third mid gray scale image data (M_IMG1, M_IMG2, M_IMG3). ) and first to third high grayscale image data (H_IMG1, H_IMG2, H_IMG3) are provided to the display panel 100.

The first to third low gray-scale image data (L_IMG1, L_IMG2, L_IMG3) are the first to third middle gray-scale image data (M_IMG1, M_IMG2, M_IMG3) and the first to third high gray-scale image data (H_IMG1, H_IMG2, H_IMG3). It may have a grayscale lower than or equal to that of the first to third medium grayscale image data (M_IMG1, M_IMG2, M_IMG3) and the first to third high grayscale image data (H_IMG1, H_IMG2, H_IMG3). You can.

According to an embodiment of the present invention, the first to third low gray scale image data (L_IMG1, L_IMG2, L_IMG3) each have different gray scales, and the first to third medium gray scale image data (M_IMG1, M_IMG2, M_IMG3) Each has a different gray scale, and the first to third high gray scale image data (H_IMG1, H_IMG2, H_IMG3) may each have different gray scales. For example, the first low-gray-scale image data (L_IMG1) has a lower gray-scale than the second and third low-gray-scale image data (L_IMG2 and L_IMG3), and the second low-gray-scale image data (L_IMG2) has a lower gray-scale than the third low-gray-scale image data (L_IMG2 and L_IMG3). It has a lower gray level than (L_IMG3), and the gray level difference between the second low gray level image data (L_IMG2) and the first low gray level image data (L_IMG1) is the third low gray level image data (L_IMG3) and the second low gray level image data (L_IMG2). ) may be the same as the gray level difference. The first relay image data (M_IMG1) has a lower gray level than the second and third relay image data (M_IMG2, M_IMG3), and the second relay image data (M_IMG2) has a lower gray level than the third relay image data (M_IMG3). It has a low gray scale, and the gray scale difference between the second intermediate gray scale image data (M_IMG2) and the first intermediate gray scale image data (M_IMG1) is the gray scale difference between the third intermediate gray scale image data (M_IMG3) and the second intermediate gray scale image data (M_IMG2). may be the same as In addition, the first high gray scale image data (H_IMG1) has a lower gray scale than the second and third high gray scale image data (H_IMG2, H_IMG3), and the second high gray scale image data (H_IMG2) has a lower gray scale than the third high gray scale image data (H_IMG3). ), and the difference in grayscale between the second high grayscale image data (H_IMG2) and the first high grayscale image data (H_IMG1) is that of the third high grayscale image data (H_IMG3) and the second high grayscale image data (H_IMG2). It may be the same as the gray level difference. At this time, the gray level difference between the low gray level image data may be a value smaller than the gray level difference between the mid gray level image data and the gray level difference between the high gray level image data, and the gray level difference between the mid gray level image data may be a value smaller than the gray level difference between the mid gray level image data and the high gray level image data. It may be a value smaller than the gray level difference between data.

For example, the first low gray level image data (L_IMG1) is image data consisting of image data of 20 gray levels, the second low gray level image data (L_IMG2) is image data consisting of image data of 30 gray levels, and the third low gray level image data. The image data (L_IMG3) may be image data composed of 40 gray-scale image data, the first mid-gray-scale image data (M_IMG1) may be image data composed of 40-gray-scale image data, and the second mid-gray-scale image data (M_IMG2) may be image data composed of 40 gray-scale image data. It is image data composed of image data of 60 gray levels, the third middle gray level image data (M_IMG3) may be image data composed of image data of 80 gray levels, and the first high gray level image data (H_IMG1) may be image data of 150 gray levels. It is image data composed of image data, the second high gray-scale image data (H_IMG2) may be image data composed of image data of 180 gray-scale, and the third high-gray-scale image data (H_IMG3) may be image data composed of image data of 210 gray-scale. Accordingly, 10 gray levels, which is the absolute value of the difference between the low gray level image data (L_IMG1, L_IMG2, L_IMG3), is 20 gray levels, which is the absolute value of the difference between the mid gray level image data (M_IMG1, M_IMG2, M_IMG3) and high gray level image data. It may be a value smaller than 30 gray levels, which is the absolute value of the difference between (H_IMG1, H_IMG2, H_IMG3), and 20 gray levels, which is the absolute value of the difference between the mid-gray-scale image data (M_IMG1, M_IMG2, M_IMG3), is the high-gray-scale image data (H_IMG1, It may be a value smaller than 30 gray levels, which is the absolute value of the difference between (H_IMG2, H_IMG3). Additionally, for example, the low gray level image data (L_IMG1, L_IMG2, L_IMG3) may have a gray level of 0 to 45 gray levels, and the medium gray level image data (M_IMG1, M_IMG2, M_IMG3) may have a gray level of 20 to 100 gray levels. It may have a gray level of less than 100 gray levels, and the high gray level image data (H_IMG1, H_IMG2, H_IMG3) may have a gray level of 100 gray levels or more.

The display panel 100 receives first to third low gray scale image data (L_IMG1, L_IMG2, L_IMG3), first to third mid gray scale image data (M_IMG1, M_IMG2, M_IMG3), and first to third low gray scale image data (M_IMG1, M_IMG2, M_IMG3) from the test image supply unit 210. Third high gray scale image data (H_IMG1, H_IMG2, H_IMG3) is received and first to third low gray scale images, first to third mid gray scale images, and first to third high gray scale images are respectively displayed.

The test image capture unit 220 acquires captured image data by capturing an image displayed on the display panel 100. At this time, according to an embodiment of the present invention, the test image capture unit 220 captures the first to third low-gray-scale images by applying the same standard exposure time and the first to third mid-gray-scale images. The same standard exposure time is applied to the first to third high gray scale images, and the same standard exposure time is applied to the first to third low gray scale images, the first to third mid gray scale images, and the first to third high gray scale images. The image displayed on the display panel 100 is photographed by applying different standard exposure times to the first to third high grayscale images. Accordingly, the test image capture unit 220 generates a plurality of captured image data that is calculated in a common sense manner. Specifically, the test image capture unit 220 captures the display panel 100 displaying the first to third low-gray-scale images for a first reference exposure time (t_exp1) to produce first to third low-gray-scale captured image data ( L_capIMG1, L_capIMG2, L_capIMG3) are generated, and the display panel 100 displaying the first to third intermediate gray scale images is photographed for a second reference exposure time (t_exp2) to produce first to third intermediate gray scale captured image data (M_capIMG1). , M_capIMG2, M_capIMG3) are generated, and the display panel 100 displaying the first to third high gray scale images is photographed for a third reference exposure time (t_exp3) to produce first to third high gray scale captured image data (H_capIMG1, Create H_capIMG2,H_capIMG3). At this time, according to an embodiment of the present invention, the first reference exposure time (t_exp1) may be a value greater than the second and third reference exposure times (t_exp2, t_exp3), and the second reference exposure time (t_exp2) may be greater than the third reference exposure time (t_exp2). It may be a larger value than the standard exposure time (t_exp3). For example, the first reference exposure time (t_exp1) may be 40ms, the second reference exposure time (t_exp2) may be 30ms, and the third reference exposure time (t_exp3) may be 15ms. These first to third reference exposure times (t_exp1, t_exp2, t_exp3) can be calculated through the mura compensation unit 230, which will be described later.

The test image capture unit 220 captures images displayed on the display panel 100, generates captured image data, and transmits it to the mura compensation unit 230.

To this end, the test image capture unit 220 may be implemented with a camera, a colorimeter, etc., and may be comprised of, for example, a CCD sensor, a lens, a body, etc. In particular, according to one embodiment of the present invention, the test image capture unit 220 may set the reference exposure time according to the range of grayscale, as described above.

Additionally, the captured image data generated by the test image capture unit 220 by photographing an image displayed on the display panel 100 may be composed of image data corresponding to pixels of the display panel 100. That is, first to third low gray scale captured image data (L_capIMG1, L_capIMG2, L_capIMG3), first to third intermediate gray scale captured image data (M_capIMG1, M_capIMG2, M_capIMG3), and first to third high gray scale captured image data (H_capIMG1). ,H_capIMG2,H_capIMG3) may each be composed of image data corresponding to each pixel of the display panel 100.

The test image capture unit 220 may transmit captured image data in various formats that can be received by the mura compensation unit 230.

Although not shown, the mura compensation device 200 may further include an imaging correction unit to obtain more accurate captured image data. The shooting correction unit receives captured image data obtained by shooting the image displayed on the display panel 100 in the test image capturing unit 220, and corrects the shooting state of the test image capturing unit 220 to determine the test image capturing unit 220. ) can prevent errors caused by For this purpose, the shooting correction unit displays correction information for correcting the shooting condition on a separate display device or sends the correction information to the test image capture unit according to the results of analyzing the captured image data captured by the image displayed on the display panel 100. You can give feedback at (220). When the shooting correction unit displays correction information on a separate display device, the user can check the correction information and correct the shooting state of the test image capturing unit 220. Alternatively, the test image capture unit 220 may automatically correct the capture state by referring to the feedback correction information. At this time, the image data for correcting the shooting condition of the test image capture unit 220 may be a different image from the image data for mura analysis of the display panel 100, and the image data for correcting the shooting condition may be a different image from the image data. It may include patterns that make it easy to analyze the size, degree of rotation (tilt) of the image, and distortion of the image.

The mura compensation unit 230 calculates a mura compensation equation that calculates a mura compensation coefficient. Specifically, the mura compensation unit 230 calculates the standard exposure time for each gray scale range for shooting images for each gray scale range and provides it to the test image capture unit 220, calculates representative image data for each gray scale range, and calculates the standard exposure time for each gray scale range to compensate for the mura compensation. Generates common sense. To this end, the mura compensation unit 230 includes a standard exposure time calculation unit 231, a representative image data calculation unit 232, and a mura compensation calculation unit 233, as shown in FIG. 2 .

The standard exposure time calculation unit 231 sets a first standard exposure time (t_exp1) for photographing the first to third low gray scale images and a second standard exposure time (t_exp2) for photographing the first to third medium gray scale images. And a third reference exposure time (t_exp3) for photographing the first to third high grayscale images is calculated and provided to the test image capture unit 220. The reference exposure time calculation unit 231 provides first to third low gray scale image data generated by photographing first to third low gray scale images, first to third mid gray scale images, and first to third high gray scale images, respectively. Any one of (L_IMG, L_IMG2, L_IMG3), any one of the first to third medium gray scale image data (M_IMG1, M_IMG2, M_IMG3), and any one of the first to third high gray scale image data (H_IMG1, H_IMG2, H_IMG3) Each exposure time that is not saturated is determined as the first reference exposure time (t_exp1), the second reference exposure time (t_exp2), and the third reference exposure time (t_exp3). For example, the standard exposure time calculation unit 231 determines the exposure time at which the second low-gray-scale image data (L_IMG2) is not saturated as the first standard exposure time (t_exp1), and the second mid-gray-scale image data (M_IMG2) The exposure time at which the second high grayscale image data (H_IMG2) is not saturated may be determined as the second reference exposure time (t_exp2), and the exposure time at which the second high grayscale image data (H_IMG2) is not saturated may be determined as the third reference exposure time (t_exp3).

The representative image data calculation unit 232 calculates typical image data as shown in FIGS. 3A to 3C. That is, the representative image data calculation unit 232 calculates low grayscale representative image data (L_repIMG) using the first to third low grayscale captured image data (L_capIMG1, L_capIMG2, L_capIMG3), and uses the first to third intermediate grayscale captured image data (L_capIMG1, L_capIMG3) to calculate low grayscale representative image data (L_repIMG). Captured data (M_capIMG1, M_capIMG2, M_capIMG3) is used to calculate mid-gray scale representative image data (M_repIMG), and the first to third high gray scale captured image data (H_capIMG1, H_capIMG2, H_capIMG3) are used to calculate high gray scale representative image data ( Calculate L_repIMG).

Specifically, as shown in FIG. 3A, the representative image data calculation unit 232 calculates representative brightness code values (L_repIMG1, L_repIMG2, L_repIMG3) for each of the first to third low grayscale captured image data (L_capIMG1, L_capIMG2, L_capIMG3). ) is calculated, and as shown in FIG. 3b, representative brightness code values (M_repIMG1, M_repIMG2, M_repIMG3) are calculated for each of the first to third middle grayscale captured image data (M_capIMG1, M_capIMG2, M_capIMG3), and FIG. 3c As shown, representative brightness code values (H_repIMG1, H_repIMG2, H_repIMG3) are calculated for each of the first to third high grayscale captured image data (H_capIMG1, H_capIMG2, H_capIMG3). At this time, the representative brightness code value may be one of the average value, mode, and median of the image data constituting the captured image data of each gray level. For example, the representative image data calculation unit 232 calculates 80 gray levels, which is the average value of the image data constituting the first low gray level captured image data (L_capIMG1), as the first low gray level representative brightness code value (L_repIMG1), and 2 120 gray levels, which is the average value of the image data constituting the low gray level captured image data (L_capIMG2), is calculated as the second low gray level representative brightness code value (L_repIMG1), and the image data constituting the third low gray level captured image data (L_capIMG3) The average value of 200 gray levels can be calculated as the third low gray level representative brightness code value (L_repIMG3).

The representative image data calculation unit 232 determines a representative image data calculation formula for each gray level using the representative brightness code value for each gray level range. Specifically, the first low gray level representative brightness code value (L_repIMG1) and the second low gray level image data (L_IMG2) of the first low gray level captured image data (L_capIMG1) captured by inputting the first low gray level image data (L_IMG1) are The second low gray level representative brightness code value (L_repIMG2) of the input and captured second low gray level captured image data (L_capIMG2) and the third low gray level captured image data (L_capIMG3) input and captured. ) can be used to calculate Equation 1, which is a low-gray-scale representative image data calculation formula, using the third low-gray-scale representative brightness code value (L_repIMG3).

[Equation 1]

In Equation 1, x is a grayscale value input to the display panel 100, and y is a grayscale value of captured image data obtained by shooting an image displayed on the display panel 100. That is, the representative image data calculation unit 232 includes first low gray scale image data (L_IMG1), first low gray scale representative brightness code value (L_repIMG1), first low gray scale image data (L_IMG2), and second low gray scale representative brightness code. a _L , b _L , and c _L in Equation 1 below are calculated using the value (L_repIMG2), the first low-gray-scale image data (L_IMG3), and the third low-gray-scale representative brightness code value (L_repIMG3). That is, the first low-gray-scale image data (L_IMG1) and the first low-gray-scale representative brightness code value (L_repIMG1) are applied to x and y in Equation 1 below, respectively, and the second low-gray-scale image data (L_IMG2) and the second Apply the low grayscale representative brightness code value (L_repIMG2) to x and y in Equation 1 below, respectively, and apply the third low grayscale image data (L_IMG3) and the third low grayscale representative brightness code value (L_repIMG3) to the math below, respectively. Applying Equation 1 to x and y calculates three simultaneous equations for a _L , b _L and c _L in Equation 1, and using the calculated simultaneous equations, a _L , b _L and c in Equation 1 By calculating _L , a low-gray-scale representative image data calculation formula for the low-gray-scale image data as shown in FIG. 4 can be calculated.

Accordingly, the representative image data calculation unit 232 applies one of the first to third low-gradation captured image data (L_capIMG, L_capIMG2, L_capIMG3) to Equation 2 below, which is a modification of Equation 1, to display the display panel 100. ), it is possible to calculate low-gray-scale representative image data (L_repIMG) that is estimated to be ideally displayed on the display panel 100 by excluding the applied mura compensation value. For example, as described above, each image calculation captured image data consists of image data corresponding to each pixel of the display panel 100, and the representative image data calculation unit 232 provides information on each captured image data. Low-gray representative image data (L_repIMG) can be calculated by applying Equation 2, which is a modified version of Equation 1, to each unit block containing at least one piece of image data corresponding to each pixel of the display panel 100.

[Equation 2]

That is, as shown in FIG. 5, the representative image data calculation unit 232 calculates the low grayscale image data of each unit block of the second low-gray-scale captured image (L_capIMG2) to Calculate grayscale representative image data (L_repIMG).

Although the representative image data calculation unit 232 has been described based on low-gradation image data (L_IMG1, L_IMG2, L_IMG3), the representative image data calculation unit 232 uses mid-gradation image data (M_IMG1, M_IMG2, M_IMG3) and high-gradation image data (M_IMG1, M_IMG2, M_IMG3). The same method is used for the image data (H_IMG1, H_IMG2, H_IMG3) to calculate mid-gray scale representative image data (M_repIMG1, M_repIMG2, M_repIMG3) and high gray scale representative image data (H_repIMG1, H_repIMG2, H_repIMG3).

The mura compensation calculation unit 233 uses the low gray level representative image data (L_repIMG), mid gray level representative image data (L_repIMG), and high gray level representative image data (L_repIMG) calculated by the representative image data calculation unit 232 to determine mura. Calculate the compensation formula. Specifically, the mura compensation calculation unit 233 generates low-gray-scale representative image data (L_repIMG), mid-gray-scale representative image data (L_repIMG), and high-gray-scale representative image data (L_repIMG) for each unit block including image data corresponding to at least one pixel. Using each image data of the image data (L_repIMG), a _F , b _F , and c _F in Equation 3 below are calculated to calculate the mura compensation equation. That is, any one of the first to third low gray-scale image data (L_IMG1, L_IMG2, L_IMG3) and the low gray-scale representative image data (L_repIMG) are applied to x and y in Equation 3 below, respectively, and the first to third Any one of the low gray scale image data (M_IMG1, M_IMG2, M_IMG3) and the mid gray scale representative image data (M_repIMG) are applied to x and y in Equation 3 below, respectively, and the first to third high gray scale image data (H_IMG1, One of H_IMG2,H_IMG3) and high-grayscale representative image data (H_repIMG) are applied to x and y in Equation 3 below, respectively, to calculate three simultaneous equations for a _F , b _F , and c _F in Equation 3 And, a _F , b _F , and c _F in Equation 3 are calculated to calculate the mura compensation equation.

[Equation 3]

The mura compensation calculation unit 233 calculates a compensation coefficient according to the input gray level for each pixel of the display panel 100 through the mura compensation equation and provides the compensation coefficient to the driver 300 that drives the display panel 100.

Accordingly, the mura compensation device according to an embodiment of the present invention is a photographing equipment of the test image capture unit 220 using the captured image data (L_capIMG1, L_capIMG2, L_capIMG3) for each gray level generated by photographing the display panel 100. And since the mura compensation coefficient is calculated by obtaining representative image data (L_repIMG, L_repIMG, L_repIMG) for each gray level displayed by the actual display panel 100 regardless of the deviation of the display panels 100, mura can be compensated more accurately. You can.

Hereinafter, with reference to FIGS. 6 and 7, a mura compensation method according to an embodiment of the present invention will be described in detail.

Figure 6 is a flow chart of the process of generating representative image data for each gray level according to an embodiment of the present invention, and Figure 7 shows the mura compensation equation for each gray level according to an embodiment of the present invention, and the calculated mura compensation equation. This is a flow chart of the process of generating low-gradation representative image data.

Referring to FIG. 6, the test image supply unit 210 provides first to third image data for each gray level range to the display panel 100 (s601). Specifically, as described above, the test image supply unit 210 includes first to third low gray-scale image data (L_IMG1, L_IMG2, L_IMG3), first to third middle gray-scale image data (M_IMG1, M_IMG2, M_IMG3), and First to third high grayscale image data (H_IMG1, H_IMG2, H_IMG3) are provided to the display panel 100. According to an embodiment of the present invention, the first to third low gray scale image data (L_IMG1, L_IMG2, L_IMG3) have different gray scales, and the first to third medium gray scale image data (M_IMG1, M_IMG2, M_IMG3) have different gray levels. The first to third high grayscale image data (H_IMG1, H_IMG2, H_IMG3) may have different grayscales. Specifically, the first low-gray-scale image data (L_IMG1) has a lower gray-scale than the second and third low-gray-scale image data (L_IMG2, L_IMG3), and the second low-gray-scale image data (L_IMG2) has a lower gray-scale than the third low-gray-scale image data (L_IMG2). L_IMG3), and the gray level difference between the second low gray scale image data (L_IMG2) and the first low gray scale image data (L_IMG1) is the third low gray scale image data (L_IMG3) and the second low gray scale image data (L_IMG2). It may be the same as the gray level difference of . The first relay image data (M_IMG1) has a lower gray level than the second and third relay image data (M_IMG2, M_IMG3), and the second relay image data (M_IMG2) has a lower gray level than the third relay image data (M_IMG3). It has a low gray scale, and the gray scale difference between the second intermediate gray scale image data (M_IMG2) and the first intermediate gray scale image data (M_IMG1) is the gray scale difference between the third intermediate gray scale image data (M_IMG3) and the second intermediate gray scale image data (M_IMG2). may be the same as In addition, the first high gray scale image data (H_IMG1) has a lower gray scale than the second and third high gray scale image data (H_IMG2, H_IMG3), and the second high gray scale image data (H_IMG2) has a lower gray scale than the third high gray scale image data (H_IMG3). ), and the difference in grayscale between the second high grayscale image data (H_IMG2) and the first high grayscale image data (H_IMG1) is that of the third high grayscale image data (H_IMG3) and the second high grayscale image data (H_IMG2). It may be the same as the gray level difference. At this time, the gray level difference between the low gray level image data may be a value smaller than the gray level difference between the mid gray level image data and the gray level difference between the high gray level image data, and the gray level difference between the mid gray level image data may be a value smaller than the gray level difference between the mid gray level image data and the high gray level image data. It may be a value smaller than the gray level difference between data.

Thereafter, the display panel 100 displays an image corresponding to the image data for each gray level range received (s602). Specifically, the display panel 100 receives first to third low gray-scale image data (L_IMG1, L_IMG2, L_IMG3), first to third middle gray-scale image data (M_IMG1, M_IMG2, M_IMG3), and first to third First to third low gray scale images, first to third mid gray scale images, and first to third high gray scale images respectively corresponding to high gray scale image data (H_IMG1, H_IMG2, H_IMG3) are displayed.

Thereafter, the test image capture unit 220 captures the image displayed on the display panel 100 and generates captured image data (s603). Specifically, the test image capture unit 220 may generate images corresponding to the first to third low gray scale images, first to third intermediate gray scale images, and first to third high gray scale images displayed on the display panel 100. 1 Generate low-gray-scale captured images (L_capIMG1, L_capIMG2, L_capIMG3), first mid-gray-scale captured images (M_capIMG1, M_capIMG2, M_capIMG3), and first high-gray-scale captured images (H_capIMG1, H_capIMG2, H_capIMG3). At this time, the test image capture unit 220 captures the first to third low gray scale images by applying the first standard exposure time (t_exp1), which is the same standard exposure time, and the first to third mid gray scale images by applying the same standard exposure time. The first to third high-gradation images are taken by applying the second standard exposure time (t_exp2), which is the same standard exposure time, and the first to third high-gradation images are taken by applying the third standard exposure time (t_exp3), which is the same standard exposure time. Gray-scale images, first to third mid-gray-scale images, and first to third high-gray-scale images may be captured by applying different standard exposure times. Specifically, the test image capture unit 220 receives the first to third reference exposure times (t_exp1, t_exp2, and t_exp3) from the reference exposure time calculation unit 231 and adds the first to third low grayscale images. 1 Shoot by applying the standard exposure time (t_exp1), shoot by applying the second standard exposure time (t_exp2) to the first to third medium gray scale images, and shoot by applying the third standard exposure time to the first to third high gray scale images. You can shoot by applying (t_exp3). At this time, the first to third reference exposure times (t_exp1, t_exp2, t_exp3) may have different values, and the first reference exposure time (t_exp1) is greater than the second and third reference exposure times (t_exp2, t_exp3). It may be a value, and the second standard exposure time (t_exp2) may be a value greater than the third standard exposure time (t_exp3).

Thereafter, the representative image data calculation unit 232 generates representative image data for each grayscale range using captured image data for each grayscale range (s604). This will be described in detail later with reference to FIG. 7.

Referring to FIG. 7, the representative image data calculation unit 232 calculates a representative brightness code value corresponding to each captured image data (s701). Specifically, the representative image data calculation unit 232 calculates one of the average value, mode, or median value of the image data constituting the captured image data as a representative brightness code value corresponding to the captured image data. For example, the representative image data calculation unit 232 calculates 80 grayscales, which is the average value of the image data constituting the first low grayscale captured image data (L_capIMG1), as the first low grayscale representative brightness code value (L_repIMG1), and 2 120 gray levels, which is the average value of the image data constituting the low gray level captured image data (L_capIMG2), is calculated as the second low gray level representative brightness code value (L_repIMG2), and the image data constituting the third low gray level captured image data (L_capIMG3) The average value of 200 gray levels can be calculated as the third low gray level representative brightness code value (L_repIMG3).

Thereafter, the representative image data calculation unit 232 determines a representative image data calculation formula for each gray level using the representative brightness code values calculated by common sense (s702). Specifically, the representative image data calculation unit 232 generates a first low gray level representative brightness code value (L_repIMG1) for the first low gray level captured image data (L_capIMG1) and a second low gray level captured image data (L_capIMG2). Using the low grayscale representative brightness code value (L_repIMG2) and the third low grayscale representative brightness code value (L_repIMG3) for the third low grayscale captured image data (L_capIMG3), the coefficients of Equation 1, a _L , b _L and c _L Calculate and determine the low-gradation representative image data calculation formula.

Thereafter, in step s702, the representative image data calculation unit 232 applies one of the photographed image data for each gray scale range to Equation 2, which is a modified version of Equation 1 for each gray scale range, which is the representative image data calculation formula for each gray scale range, to obtain representative image data for each gray scale range. Calculate image data (s703). For example, the representative image data calculation unit 232 may calculate low gray level representative image data (L_repIMG) by applying the image data of the unit block of the second low gray level captured image data (L_capIMG2) to y in Equation 2. there is.

Steps S702 and S703 have been explained based on low-gray-scale captured image data, but representative image data is calculated for mid-gray-scale and high-gray-scale captured image data using the same method as the low-gray-scale captured image data.

Referring to FIG. 6 again, the mura compensation formula calculation unit 233 calculates the mura compensation formula using representative image data for each gray level range (s605). Specifically, the mura compensation calculation unit 233 generates low-gray-scale representative image data (L_repIMG), mid-gray-scale representative image data (L_repIMG), and high-gray-scale representative image data (L_repIMG) for each unit block including image data corresponding to at least one pixel. Each coefficient of Equation 3 is calculated using each image data of the image data (L_repIMG), and a mura compensation equation is calculated.

Those skilled in the art to which the present invention pertains will understand that the above-described present invention can be implemented in other specific forms without changing its technical idea or essential features.

Additionally, the methods described herein may be implemented, at least in part, using one or more computer programs or components. This component may be provided as a series of computer instructions on a computer-readable medium or machine-readable medium containing volatile and non-volatile memory. The directives may be provided as software or firmware, and may be implemented, in whole or in part, in hardware components such as ASICs, FPGAs, DSPs, or other similar devices. The instructions may be configured to be executed by one or more processors or other hardware components, which, when executing the set of computer instructions, perform or perform all or part of the methods and procedures disclosed herein. make it possible

Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive. The scope of the present invention is indicated by the claims described below rather than the detailed description above, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. do.

100: display panel 200: mura compensation device
210: Test image supply unit 220: Test image recording unit
230: Mura compensation unit 231: Standard exposure time calculation unit
232: Representative image data calculation unit 233: Mura compensation calculation unit

Claims (13)

A mura compensation device that detects mura in an image displayed through a display panel and compensates for the detected mura,
a test image supply unit that supplies first image data and second image data to the display panel; and
A test image capture unit that captures a first image and a second image displayed on the display panel in response to the first image data and the second image data, respectively,
The test image capture unit captures the first image during a first reference exposure time to generate first captured image data, and captures the second image during a second reference exposure time different from the first reference exposure time to generate a second image data. A mura compensation device characterized in that it generates captured image data. According to paragraph 1,
Generate first representative image data using the first captured image data, generate second representative image data using the second captured image data, and determine mura using the first and second representative image data. A mura compensation device further comprising a mura compensation unit that compensates. According to paragraph 2,
The first image data includes first and second low-gradation image data,
The second image data includes first and second high grayscale image data,
The first captured image data includes first and second low grayscale captured image data,
The second captured image data includes first and second high grayscale captured image data,
The mura compensation department,
First and second low gray scale representative brightness code values are calculated for each of the first and second low gray scale captured image data, and the first representative image data is calculated using the calculated first and second low gray scale representative brightness values. Generate, calculate first and second high gray scale representative brightness code values for each of the first and second high gray scale captured image data, and use the calculated first and second high gray scale representative brightness values to 2 A mura compensation device characterized by generating representative image data. According to paragraph 1,
The first and second low grayscale representative brightness code values and the first and second high grayscale representative brightness code values respectively correspond to the first and second low grayscale captured image data and the first and second high grayscale captured image data, respectively. A mura compensation device characterized in that it is one of the average value, mode, and median of the image data constituting . According to paragraph 1,
The test image supply unit supplies third image data to the display panel,
The test image capture unit captures a third image displayed on the display panel in response to the third image data, and applies the third image to a third reference exposure time different from the first reference exposure time and the second reference exposure time. A mura compensation device characterized in that it generates third captured image data by shooting over a period of time. According to clause 5,
Generating first representative image data using the first captured image data, generating second representative image data using the second captured image data, and generating third representative image data using the third captured image data. A mura compensation device further comprising a mura compensation unit that generates and compensates for mura using the first to third representative image data. According to clause 6,
The first image data includes first to third low gray scale image data,
The second image data includes first to third high grayscale image data,
The third image data includes first to third grayscale image data,
The first captured image data includes first to third low grayscale captured image data,
The second captured image data includes first to third high grayscale captured image data,
The third captured image data includes first to third gray scale captured image data,
The mura compensation department,
Calculate first to third low gray scale representative brightness code values for each of the first to third low gray scale captured image data, and calculate the first representative image data using the calculated first to third low gray scale representative brightness values. create,
Calculating first to third high grayscale representative brightness code values for each of the first to third high grayscale captured image data, and calculating the second representative image data using the calculated first to third high grayscale representative brightness values. create,
Calculate first to third relay scale representative brightness code values for each of the first to third relay scale captured image data, and calculate the third representative image data using the calculated first to third relay scale representative brightness values. A mura compensation device characterized in that it generates. In clause 7,
The first to third low gray scale image data are image data composed of different gray scales, the first to third intermediate gray scale image data are image data composed of different gray scales, and the first to third high gray scale image data are is a mura compensation device characterized in that image data composed of different gray levels. In clause 7,
When the first low-gray-scale image data has a lower gray-scale than the second and third low-gray-scale image data and the second low-gray-scale image data has a lower gray-scale than the third low-gray-scale image data, the second low-gray-scale image data The grayscale difference between the image data and the first low grayscale image data is the same as the grayscale difference between the third low grayscale image data and the second low grayscale image data,
When the first relay image data has a lower gray level than the second and third relay image data and the second relay image data has a lower gray level than the third relay image data, the second relay image data has a lower gray level than the third relay image data. The grayscale difference between the image data and the first grayscale image data is the same as the grayscale difference between the third grayscale image data and the second grayscale image data,
When the first high gray scale image data has a lower gray scale than the second and third high gray scale image data and the second high gray scale image data has a lower gray scale than the third high gray scale image data, the second high gray scale image data has a lower gray scale than the third high gray scale image data. A mura compensation device, wherein a grayscale difference between the image data and the first high grayscale image data is the same as a grayscale difference between the third high grayscale image data and the second high grayscale image data. In clause 7,
The gray scale difference between the second low gray scale image data and the first low gray scale image data includes the gray scale difference between the second mid gray scale image data and the first mid gray scale image data, and the gray scale difference between the second high gray scale image data and the first mid gray scale image data. Has a value smaller than the gray level difference of high gray level image data,
A mura compensation device, characterized in that the gray level difference between the second gray level image data and the first gray level image data has a smaller value than the gray level difference between the second high gray level image data and the first high gray level image data. A mura compensation method for detecting mura in an image displayed through a display panel and compensating for the detected mura, comprising:
providing image data to the display panel;
displaying an image by the display panel;
generating captured image data by capturing the image;
calculating representative image data using the captured image data; and
Compensating for mura using the representative image data,
The image data includes first and second image data,
The image includes a first and a second image,
In the step of capturing the image and generating captured image data,
First captured image data is generated by photographing the first image during a first standard exposure time, and second photographed image data is generated by photographing the first image during a second standard exposure time different from the first standard exposure time. A mura compensation method characterized by: According to clause 11,
The first image data includes first and second low-gradation image data,
The second image data includes first and second high grayscale image data,
The captured image data includes first and second captured image data,
The first captured image data includes first and second low grayscale captured image data,
The second captured image data includes first and second high grayscale captured image data,
The representative image data includes first and second representative image data,
In the step of calculating representative image data using the captured image data, the first representative image data is calculated using the first and second low gray level captured image data, and the first representative image data is calculated using the first and second high gray level captured image data. A mura compensation method characterized by calculating the second representative image data using data. According to clause 11,
The image data further includes third image data,
The first image data includes first to third low gray scale image data,
The second image data includes first to third high grayscale image data,
The second image data includes first to third grayscale image data,
The captured image data includes first to third captured image data,
The first captured image data includes first to third low grayscale captured image data,
The second captured image data includes first to third high grayscale captured image data,
The third captured image data includes first to third gray scale captured image data,
The representative image data includes first to third representative image data,
In the step of calculating representative image data using the captured image data, first representative image data is calculated using the first to third low grayscale captured image data, and the first to third high grayscale captured image data are calculated. A mura compensation method characterized by calculating second representative image data using and calculating third representative image data using the first to third grayscale captured image data.

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