Gray scale optimization method, display device and electronic equipment

Abstract

The gray scale optimization method, display device and electronic equipment, the gray scale optimization method comprises: judging whether the display brightness value of a pixel point is less than or equal to a brightness compensation threshold value; when the display brightness value is less than or equal to the brightness compensation threshold value, judging whether the gray scale value of the pixel point is less than or equal to a gray scale threshold value; when the gray scale value is less than or equal to the gray scale threshold value, the initial pixel data of the pixel point is converted from the RGB color space to the YUV color space according to the threshold range where the display brightness value is located to perform different degrees of brightness compensation. The method can automatically judge whether the optimization function needs to be enabled and select the corresponding optimization adjustment curve in the application scene, and can realize display gray scale optimization to improve the picture display effect.

Description

Technical Field

[0001] This invention relates to the field of display technology, and more specifically, to a grayscale optimization method, a display device, and an electronic device. Background Technology

[0002] Currently, smartphones, wearable devices, and other new electronic devices typically use Organic Light-Emitting Diode (OLED) display modules. OLED display modules are self-emissive, and the screen generally uses a real RGB pixel arrangement, meaning a white pixel is composed of three sub-pixels: red (R), green (G), and blue (B). OLED display modules use DBV (data brightness value) to represent brightness control, with grayscale values ​​representing the data of a single pixel in the displayed image. Taking wearable devices as an example, DBV typically uses 256 levels of subdivision for brightness adjustment, from 0 to 255. When DBV is 255, the display brightness is set to its maximum value. The grayscale value is calculated by combining the data from the R, G, and B sub-pixels.

[0003] Because smart wearable devices are characterized by all-day or nighttime displays, the displayed objects are mostly low grayscale color images with very low brightness. Furthermore, because the luminous efficiency of the three sub-pixels R, G, and B in an OLED display module is different, in low-brightness application scenarios, the visual effect of the low grayscale color image module is prone to problems such as the inability to distinguish changes in grayscale values. For example, there may be grayscale gradients that cannot be distinguished from the image, or display defects such as black spots.

[0004] Therefore, to address the aforementioned problems and shortcomings, this invention proposes a grayscale optimization method to improve the display effect of the image and ensure that the optimized image does not lose color accuracy. Summary of the Invention

[0005] In view of this, this disclosure provides a grayscale optimization method that can automatically determine whether the application scenario requires the optimization function and the corresponding optimization adjustment curve based on the DBV value of brightness control without the need for additional instructions from the terminal main control chip. This method can process the data of each pixel in the display device one by one to optimize the low grayscale part separately without changing the high grayscale part of the image, thereby improving the display effect of the image at low grayscale and ensuring that the optimized image does not lose color.

[0006] One aspect of this disclosure provides a grayscale optimization method, comprising: inputting the display brightness value and grayscale value of a pixel; determining whether the display brightness value of the pixel is less than or equal to a brightness compensation threshold; when the display brightness value is less than or equal to the brightness compensation threshold, determining whether the grayscale value of the pixel is less than or equal to a grayscale threshold; when the grayscale value is less than or equal to the grayscale threshold, converting the initial pixel data of the pixel from the RGB color space to the YUV color space according to the threshold range in which the display brightness value is located, and performing different degrees of brightness compensation.

[0007] In some embodiments, the grayscale optimization method further includes: if the display brightness value of a pixel is greater than the brightness compensation threshold or the grayscale value of a pixel is greater than the grayscale threshold, then no brightness compensation is performed on the pixel.

[0008] In some embodiments, the brightness compensation threshold range includes multiple compensation intervals, each with a different compensation function, and different degrees of brightness compensation are applied to the YUV color space according to the different compensation functions.

[0009] In some embodiments, the compensation function is a quadratic function, which is obtained by curve fitting at multiple points within the compensation interval.

[0010] In some embodiments, converting the initial pixel data of a pixel from the RGB color space to the YUV color space includes: converting the initial pixel data of a pixel from the RGB color space to the YUV color space according to a first conversion function, wherein the first conversion function includes:

[0011] Y = 0.32R + 0.56G + 0.125B + 0.25

[0012] U = -0.1825R - 0.31G + 0.5B + ​​128

[0013] V = 0.5R - 0.4325G - 0.062B + 128

[0014] Where Y is the luminance component in the converted YUV color space, representing the image grayscale; U and V are the chrominance components in the converted YUV color space, representing the color saturation; R is the grayscale value of the red subpixel in the initial pixel data; G is the grayscale value of the green subpixel in the initial pixel data; and B is the grayscale value of the blue subpixel in the initial pixel data.

[0015] In some embodiments, the grayscale optimization method further includes: converting the brightness-compensated YUV color space to the RGB color space to obtain compensated pixel data.

[0016] In some embodiments, converting the brightness-compensated YUV color space to the RGB color space includes: converting the brightness-compensated YUV color space to the RGB color space according to a second conversion function, wherein the second conversion function further includes color offset compensation for the RGB color space.

[0017] In some embodiments, the second conversion function includes:

[0018] R′=Y′-0.079U+1.327V-r_offset

[0019] G'=Y'-0.327U-0.748V+g_offset

[0020] B'=Y'+1.748U+0.027V-b_offset

[0021] Where R′ is the grayscale value of the red sub-pixel in the compensated pixel data, G′ is the grayscale value of the green sub-pixel in the compensated pixel data, B′ is the grayscale value of the blue sub-pixel in the compensated pixel data, Y′ is the compensated brightness after brightness compensation, U and V are the chromaticity components after brightness compensation, r_offset is the color shift compensation of the grayscale value of the red sub-pixel, g_offset is the color shift compensation of the grayscale value of the green sub-pixel, and b_offset is the color shift compensation of the grayscale value of the blue sub-pixel.

[0022] Another aspect of this disclosure provides a display device, including: a driver chip capable of performing the grayscale optimization method as described in any of the preceding claims.

[0023] Another aspect of this disclosure provides an electronic device, comprising: a storage medium storing executable program instructions; and a processor capable of executing the grayscale optimization method as described in any of the preceding claims by invoking the program instructions.

[0024] In summary, the grayscale optimization method, display device, and electronic device provided by this invention, by linking grayscale brightness optimization with display brightness value (DBV), can automatically determine the grayscale optimization switch and select the optimization curve without the need for additional instructions from the terminal main control chip. It provides precise and automatic optimization for low display brightness value scenarios, effectively avoiding color distortion caused by overcompensation in high display brightness value scenarios, while also saving power consumption.

[0025] Furthermore, the optimization method provided by this invention can adjust pixel data for different grayscale levels individually, effectively improving the display effect of low grayscale detail changes in the image while maintaining color accuracy in the optimized image. Moreover, the low grayscale brightness optimization supports flexible adjustment of RGB pixel data across multiple nodes, allowing for the simultaneous setting of multiple brightness adjustment curves to optimize different grayscale ranges, meeting the optimization needs of different grayscale pixel data, and achieving effective display of low grayscale gradient details in complex images without affecting the color display of high grayscale levels. This invention can adaptively optimize display devices for applications in all-weather or nighttime display scenarios. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly introduced below. Obviously, the drawings in the following description only relate to some embodiments of the present invention, and are not intended to limit the present invention.

[0027] Figure 1 This is a flowchart of a grayscale optimization method according to an embodiment of the present disclosure;

[0028] Figure 2 This is a schematic diagram of the compensation interval divided according to the display brightness value in the optimization method of this embodiment;

[0029] Figure 3 This is a schematic diagram showing the brightness comparison before and after optimization using a grayscale optimization method according to an embodiment of the present disclosure. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] Figure 1 This is a flowchart of a grayscale optimization method according to an embodiment of the present disclosure. Display is achieved through multiple pixels, and the data for each pixel includes, for example, a display brightness value (DBV) and a grayscale value for the pixel, such as... Figure 1 As shown, the grayscale optimization method includes the following steps:

[0032] In step S10, the display brightness value and grayscale value of the pixel are input;

[0033] In step S20, it is determined whether the display brightness value of the pixel is less than or equal to the brightness compensation threshold. Specifically, the range of the display brightness value DBV is, for example, 0 to 255. The larger the value of the display brightness value DBV, the brighter the corresponding display screen. The brightness compensation threshold is, for example, 64. That is, when the display brightness value DBV is less than or equal to 64, it is determined that the brightness of the display screen is low and the display brightness value needs to be optimized and compensated.

[0034] In step S30, when the display brightness value is less than or equal to the brightness compensation threshold, it is determined whether the grayscale value of the pixel is less than or equal to the grayscale threshold. Specifically, the grayscale value of the pixel is compared with the grayscale threshold. When the grayscale value of the pixel is less than or equal to the grayscale threshold, it is determined that the grayscale value is low and optimization compensation is required.

[0035] In step S40, when the grayscale value of a pixel is less than or equal to a grayscale threshold, the initial pixel data of the pixel is converted from the RGB color space to the YUV color space according to the first conversion function. Specifically, for an OLED display device, based on the light-emitting characteristics of its red, green, and blue sub-pixels, a first conversion function is defined to convert the RGB color space to the YUV color space, and then the initial pixel data in the RGB color space is converted to the YUV color space through the first conversion function.

[0036] The first transformation function is as follows:

[0037] Y = 0.32R + 0.56G + 0.125B + 0.25

[0038] U = -0.1825R - 0.31G + 0.5B + ​​128

[0039] V = 0.5R - 0.4325G - 0.062B + 128

[0040] Where Y is the luminance component in the YUV color space, representing the image grayscale; U and V are the chrominance components in the YUV color space, representing the color saturation; R is the grayscale value of the red subpixel in the initial pixel data; G is the grayscale value of the green subpixel in the initial pixel data; and B is the grayscale value of the blue subpixel in the initial pixel data.

[0041] Furthermore, the parameters in the first conversion function are specifically optimized and adjusted according to the light emission characteristics of each color sub-pixel in the OLED display device. The first conversion function can convert the initial pixel data of the RGB color space into the YUV color space.

[0042] Taking smart wearable devices as an example, the input RGB data (initial pixel data) of an OLED display device has a color depth of 8 bits, meaning the grayscale range is adjustable from 0 to 255, which can represent approximately 16.7 million different colors. Since the human eye is more sensitive to brightness information than chromaticity information, the low grayscale (grayscale value less than or equal to 64) display details directly output from the initial pixel data are usually imperceptible to the human eye. The YUV color space is more convenient for adjusting brightness information independently compared to the RGB color space. Therefore, step S30 converts the initial pixel data from the RGB color space to the YUV color space for subsequent optimization.

[0043] In step S50, the initial brightness in the YUV color space is compensated to obtain compensated YUV color space data. Specifically, the brightness compensation has multiple compensation intervals, such as a first compensation interval, a second compensation interval, and a third compensation interval. Different compensation functions are selected to perform different degrees of brightness compensation on the YUV color space based on the compensation interval in which the displayed brightness value falls. This includes:

[0044] The initial luminance Y in the YUV color space is substituted into the compensation function to obtain the compensated luminance Y′. Then, the compensated luminance Y′ is combined with the chromaticity components U and V in the original second pixel data to form the compensated YUV color space (Y′, U, V). Specifically, the compensation function can be a quadratic function, including:

[0045] Y′=aY 2 +bY+c;

[0046] Where Y is the initial brightness; Y′ is the compensated brightness; and a, b, and c are the compensation coefficients, which can be obtained, for example, by plotting a compensation curve using data from multiple selected points and performing quadratic curve fitting.

[0047] Furthermore, the compensation can also include more compensation intervals, each with a different compensation function.

[0048] In step S60, the compensated YUV color space is converted to the RGB color space to obtain compensated pixel data. Depending on the display device, taking an OLED display device as an example, since it still needs pixel data in the RGB color space for output, the compensated YUV color space is converted to compensated pixel data in the RGB color space through the second conversion function.

[0049] The second transformation function is as follows:

[0050] R′=Y′-0.079U+1.327V-r_offset

[0051] G'=Y'-0.327U-0.748V+g_offset

[0052] B'=Y'+1.748U+0.027V-b_offset

[0053] Where R′ is the grayscale value of the red subpixel in the compensated pixel data, G′ is the grayscale value of the green subpixel in the compensated pixel data, B′ is the grayscale value of the blue subpixel in the compensated pixel data, Y′ is the compensated luminance in the compensated YUV color space, U and V are the chromaticity components in the compensated YUV color space, r_offset is the color offset compensation for the red subpixel data, g_offset is the color offset compensation for the green subpixel data, and b_offset is the color offset compensation for the blue subpixel data, to ensure that the optimized image display color is not distorted.

[0054] In step S41, if the display brightness value DBV of a pixel is greater than the brightness compensation threshold or the grayscale value of a pixel is greater than the grayscale threshold, then no optimization compensation is performed on the initial pixel data, and the initial pixel data is maintained.

[0055] In step S70, pixel data is output; wherein, depending on whether optimization is required, compensated pixel data or initial pixel data is output as the final pixel data so that the display device displays the corresponding image.

[0056] The aforementioned grayscale optimization method uses grayscale brightness optimization in conjunction with the display brightness value (DBV). It requires no additional instructions from the display terminal's main control chip and can automatically determine the grayscale optimization on / off state and the selection of optimization curves. It provides precise and automatic optimization for low display brightness scenarios, effectively avoiding color distortion caused by overcompensation in high display brightness scenarios, while also saving power. This optimization method supports flexible adjustment of RGB pixel data across multiple nodes, allowing for the simultaneous setting of multiple brightness adjustment curves to optimize different grayscale ranges. This meets the optimization needs of different grayscale pixel data, enabling effective display of low-grayscale gradient details in complex images without affecting high-grayscale color display. It adaptively optimizes display devices for all-weather or nighttime display scenarios. Furthermore, this method determines the need for brightness component adjustment on a pixel-by-pixel basis, identifying dark detail pixels in complex color images and precisely controlling the low-grayscale brightness component, avoiding overcompensation of high-grayscale pixel data that does not require optimization.

[0057] Figure 2 This is a schematic diagram of the compensation interval divided according to the display brightness value in the optimization method of this embodiment; for Figure 1In step S50, the multiple compensation intervals are divided, for example, according to the display brightness value DBV. The range of the display brightness value DBV is, for example, 0 to 255. For example, display brightness values ​​DBV of 20, 32, and 64 are selected as the division nodes for the compensation intervals. The display brightness value DBV of 0 to 20 is divided into the first compensation interval. At this time, the screen brightness is low, and the grayscale screen is almost indistinguishable to the human eye, requiring a large degree of compensation. The display brightness value DBV of 21 to 32 is divided into the second compensation interval. At this time, the screen is slightly brighter, and the grayscale screen is slightly distinguishable to the human eye, requiring a medium degree of compensation. The display brightness value DBV of 33 to 64 is divided into the third compensation interval. At this time, the grayscale screen is basically distinguishable to the human eye, requiring only a light degree of compensation. As for the display brightness value DBV of 65 to 255, the grayscale screen can be displayed normally, and no compensation is required. The original data output can be used.

[0058] For the same grayscale image, when the Display Brightness Value (DBV) is large, the overall brightness of the OLED display is high, and it can usually display grayscale image data normally. Therefore, no additional optimization adjustment is needed, and the original data output can be used. When the DBV is small, the overall brightness of the OLED display is low, and the brightness of details in the dark areas of the image will be even lower. Since the human eye is more sensitive to brightness information than chromaticity information, the human eye usually cannot obtain information such as gradient details in low grayscale images from the display image corresponding to the original data output. For the low DBV portion, it can be addressed through methods such as... Figure 3 The three optimization curves shown are designed to achieve different brightness zones with different compensation.

[0059] Figure 3 This is a schematic diagram comparing the brightness before and after optimization according to a grayscale optimization method of this disclosure, specifically a schematic diagram of the adjustment of the initial brightness Y and the compensated brightness Y′ in step S50. As shown by the solid line, before compensation, the output value Y_out of the brightness component Y is equal to the input value Y_in. As shown by the dashed line, after compensation, the input value Y_in(Y) of the brightness component Y is adjusted to the output value Y_out(Y′).

[0060] Specifically, this brightness compensation supports custom grayscale brightness compensation nodes to adjust low grayscale pixel data. For example, a single compensation curve can select 1 to 16 nodes. First, the grayscale positions corresponding to the 16 nodes are determined by customization. Taking the first compensation interval as an example, 16 low grayscale nodes with Y_in values ​​of 2, 4, 6, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 50, 56, and 64 are selected. Then, the node Y_out after compensation is defined based on the characteristics of the human eye. A quadratic curve fitting is performed on the curve formed by the coordinates of the grayscale nodes to obtain the compensation function for the compensation interval, thereby adjusting the brightness components within the compensation interval.

[0061] The compensation function for the first compensation interval is, for example, a quadratic function, including:

[0062] Y′=aY 2 +bY+c;

[0063] Where Y represents the initial brightness (Y_in), Y′ represents the compensated brightness (Y_out), and a, b, and c are the compensation coefficients, which can be obtained, for example, by performing quadratic curve fitting on the compensation curve plotted from multiple selected node data. Similarly, the compensation functions for the second and third compensation intervals can be determined in a similar manner to achieve compensation for the corresponding brightness components. When Y_in is greater than a certain value, i.e., greater than the brightness compensation threshold, the brightness of the corresponding image no longer needs to be compensated.

[0064] The embodiments of this disclosure can be implemented by software, hardware, firmware, or a combination thereof. For example, the optimization method of the embodiments of this disclosure can be implemented by a driver chip of a display device, or by any other computing device having the above-described discrimination, conversion, and compensation capabilities.

[0065] In summary, the grayscale optimization method, display device, and electronic device provided by this invention, by linking grayscale brightness optimization with the display brightness value (DBV), can automatically determine the grayscale optimization switch and select the optimization curve without the need for additional instructions from the terminal main control chip. It provides precise and automatic optimization for low DBV scenarios, effectively avoiding color distortion caused by overcompensation in high DBV scenarios, while also saving power.

[0066] Furthermore, the optimization method provided by this invention can adjust pixel data for different grayscale levels individually, effectively improving the display effect of low grayscale detail changes in the image while maintaining color accuracy in the optimized image. Moreover, the low grayscale brightness optimization supports flexible adjustment of RGB pixel data across multiple nodes, allowing for the simultaneous setting of multiple brightness adjustment curves to optimize different grayscale ranges, meeting the optimization needs of different grayscale pixel data, and achieving effective display of low grayscale gradient details in complex images without affecting the color display of high grayscale levels. This invention can adaptively optimize the application of OLED display devices in scenarios such as all-weather or nighttime displays.

[0067] The above description is merely an exemplary embodiment of the present invention and is not intended to limit the scope of protection of the present invention, which is determined by the appended claims.

Claims

1. A grayscale optimization method, comprising: Input the display brightness and grayscale values ​​of the pixels; Determine whether the display brightness value of a pixel is less than or equal to the brightness compensation threshold; When the display brightness value is less than or equal to the brightness compensation threshold, determine whether the grayscale value of the pixel is less than or equal to the grayscale threshold. When the grayscale value is less than or equal to the grayscale threshold, the initial pixel data of the pixel is converted from the RGB color space to the YUV color space according to the threshold range of the display brightness value to perform brightness compensation, so that the brightness after compensation is greater than the brightness before compensation and the optimized screen display color is not distorted.

2. The grayscale optimization method according to claim 1 further includes: If the display brightness value of a pixel is greater than the brightness compensation threshold or the grayscale value of a pixel is greater than the grayscale threshold, then no brightness compensation will be performed on the pixel.

3. The grayscale optimization method according to claim 1, wherein, The brightness compensation includes multiple compensation intervals, each with a different compensation function. Different degrees of brightness compensation are applied to the YUV color space based on the different compensation functions.

4. The grayscale optimization method according to claim 3, wherein, The compensation function is a quadratic function, which is obtained by curve fitting at multiple points within the compensation interval.

5. The grayscale optimization method according to claim 1, wherein, Converting the initial pixel data of a pixel from the RGB color space to the YUV color space includes: converting the initial pixel data of a pixel from the RGB color space to the YUV color space according to a first conversion function, wherein the first conversion function includes: Where Y is the luminance component in the converted YUV color space, representing the image grayscale; U and V are the chrominance components in the converted YUV color space, representing the color saturation; R is the grayscale value of the red subpixel in the initial pixel data; G is the grayscale value of the green subpixel in the initial pixel data; and B is the grayscale value of the blue subpixel in the initial pixel data.

6. The grayscale optimization method according to claim 1 further includes: The brightness-compensated YUV color space is converted to the RGB color space to obtain the compensated pixel data.

7. The grayscale optimization method according to claim 6, wherein, Converting the brightness-compensated YUV color space to the RGB color space includes: converting the brightness-compensated YUV color space to the RGB color space according to a second conversion function, wherein the second conversion function further includes color offset compensation for the RGB color space.

8. The grayscale optimization method according to claim 7, wherein the second transformation function comprises: Where R´ is the grayscale value of the red sub-pixel in the compensated pixel data, G´ is the grayscale value of the green sub-pixel in the compensated pixel data, B´ is the grayscale value of the blue sub-pixel in the compensated pixel data, Y´ is the compensated brightness after brightness compensation, U and V are the chromaticity components after brightness compensation, r_offset is the color shift compensation for the grayscale value of the red sub-pixel, g_offset is the color shift compensation for the grayscale value of the green sub-pixel, and b_offset is the color shift compensation for the grayscale value of the blue sub-pixel.

9. A display device, comprising: A driver chip that performs the grayscale optimization method as described in any one of claims 1-8.

10. An electronic device, comprising: Storage medium, which stores executable program instructions; The processor, by invoking the program instructions, is capable of executing the grayscale optimization method as described in any one of claims 1 to 8.

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