Image correction method, device and storage medium

Abstract

This application discloses an image correction method, apparatus, and storage medium. The method includes: acquiring a first influence parameter of an image to be displayed, wherein the first influence parameter measures the brightness of the image; determining a first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio adjusts the brightness of the image to be displayed; adjusting the image to be displayed based at least on the first adjustment ratio to obtain an adjusted target display image; and correcting the target display image based on correction coefficients, wherein the correction coefficients ensure that, after correction, the target brightness achieved by the display is the average brightness of the display, and the target color gamut achieved by the display is the maximum color gamut supported by more than a predetermined proportion of LEDs in the display. This application solves the technical problem of excessive brightness and color gamut loss and poor user experience caused by directly correcting the screen based on a set of correction coefficients without processing the image content in related technologies.

Description

Technical Field

[0001] This application relates to the field of image processing, and more specifically, to an image correction method, apparatus, and storage medium. Background Technology

[0002] With the development of LED display technology, LED displays are now widely used in various fields due to their advantages such as low cost, low power consumption, high visibility, and flexible assembly. At the same time, as the application of LED displays becomes more widespread, people's requirements for their display quality are also increasing. Therefore, how to improve the display quality of LED displays has become a research hotspot in this field.

[0003] One of the more challenging issues currently facing LED displays is the significant variation among individual LEDs. During calibration, it's crucial to ensure that the selected target matches the performance of all LEDs, which inevitably results in substantial sacrifices in brightness and color gamut. Figure 1 The diagram shows the architecture of a luminance and chromaticity correction technology in related technologies. This luminance and chromaticity correction technology can be applied to PWM-driven LED screens. Each pixel (generally containing three sub-pixels: RGB) stores a set of correction coefficients. Since the LED screen is two-dimensional, it can be called two-dimensional correction. The main idea is to select a certain luminance layer as the correction layer, and then acquire RGB optical data (such as luminance Y or spectral tristimulus values ​​XYZ) through acquisition devices (industrial cameras, digital cameras, etc.). Then, by setting a common target, the correction purpose is achieved.

[0004] A significant drawback of this luminance and color correction technology is that it can only set a single target, which needs to be achievable by nearly all pixels (generally over 98%) of the entire LED screen. However, due to manufacturing processes, the differences between individual LEDs in an LED screen are substantial. For example, if the maximum brightness difference between LEDs can reach 30%, then the target brightness for correction would be 0.7, resulting in a 30% brightness loss. When the LED screen brightness is low, a 30% brightness loss is acceptable. However, with the development of HDR, LED screen brightness is increasing, making a 30% brightness loss increasingly unacceptable. For example, an 800-nit screen with a 30% brightness loss would have a corrected brightness of 560 nits, which is acceptable to users. However, a 3000-nit screen with a 30% brightness loss would only have a corrected brightness of 2100 nits. Clearly, this significant brightness change is unacceptable to users. In other words, this technology suffers from the problem of excessive brightness and color gamut loss due to relying on only one set of correction coefficients, resulting in a poor user experience.

[0005] There is currently no effective solution to the above problems. Summary of the Invention

[0006] This application provides an image correction method, apparatus, and storage medium to at least solve the technical problem of excessive loss of brightness and color gamut and poor user experience caused by directly correcting the screen based on a set of correction coefficients without processing the image content in related technologies.

[0007] According to one aspect of the embodiments of this application, an image correction method is provided, comprising: obtaining a first influence parameter of an image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; determining a first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; adjusting the image to be displayed based at least on the first adjustment ratio to obtain an adjusted target display image; obtaining a correction coefficient, and correcting the target display image based on the correction coefficient.

[0008] Optionally, obtaining the first influence parameter of the image to be displayed includes: obtaining the grayscale value of each pixel in the image to be displayed; determining the first average value corresponding to the image to be displayed based on the average value of the data set composed of the grayscale values ​​of each pixel; and determining the first average value as the first influence parameter.

[0009] Optionally, adjusting the image to be displayed is based at least on a first adjustment ratio, including: acquiring a second influence parameter of the image to be displayed, wherein the second influence parameter is used to measure the brightness of the image to be displayed; determining a second adjustment ratio corresponding to the second influence parameter, wherein the second adjustment ratio is used to adjust the brightness of the image to be displayed; adjusting the image to be displayed according to the first adjustment ratio and the second adjustment ratio; or acquiring a third influence parameter of the image to be displayed, wherein the third influence parameter is used to measure the saturation of the image to be displayed; determining a third adjustment ratio corresponding to the third influence parameter, wherein the third adjustment ratio is used to adjust the saturation of the image to be displayed; and adjusting the image to be displayed according to the third adjustment ratio and the first adjustment ratio.

[0010] Optionally, obtaining a second influence parameter of the image to be displayed includes: obtaining the grayscale value of each pixel in the image to be displayed; determining a first standard deviation of the image to be displayed based on the standard deviation of the data set composed of the grayscale values ​​of each pixel, and determining the first standard deviation as the second influence parameter.

[0011] Optionally, obtaining a third influence parameter of the image to be displayed includes: obtaining the saturation of each pixel in the image to be displayed; determining a second average value corresponding to the image to be displayed based on the average value of the data set composed of the saturation of each pixel; and determining the second average value as the third influence parameter.

[0012] Optionally, determining the first adjustment ratio corresponding to the first influencing parameter includes: obtaining a first mapping relationship between the first influencing parameter and the first adjustment ratio, and determining the first adjustment ratio corresponding to the first influencing parameter based on the first mapping relationship; determining the second adjustment ratio corresponding to the second influencing parameter includes: obtaining a second mapping relationship between the second influencing parameter and the second adjustment ratio, and determining the second adjustment ratio corresponding to the second influencing parameter based on the second mapping relationship; determining the third adjustment ratio corresponding to the third influencing parameter includes: obtaining a third mapping relationship between the third influencing parameter and the third adjustment ratio, and determining the third adjustment ratio corresponding to the third influencing parameter based on the third mapping relationship.

[0013] Optionally, the image to be displayed includes: an RGB format image to be displayed; adjusting the image to be displayed based at least on a first adjustment ratio to obtain an adjusted target display image, including: converting the RGB format image to be displayed into HSV format; adjusting the HSV format image to be displayed based at least on a first adjustment ratio to obtain an adjusted HSV format target display image; and converting the HSV format target display image into an RGB format target display image.

[0014] Optionally, correcting the target display image based on correction coefficients includes: correcting the target display image in RGB format based on correction coefficients.

[0015] Optionally, the correction coefficient is used to ensure that, after calibration, the target brightness of the display is the average brightness of the display, and the target color gamut of the display is the maximum color gamut that can be supported by more than a predetermined proportion of LEDs in the display.

[0016] According to another aspect of the embodiments of this application, an image correction apparatus is also provided, comprising: an acquisition module, configured to acquire a first influence parameter of an image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; a determination module, configured to determine a first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; an adjustment module, configured to adjust the image to be displayed at least based on the first adjustment ratio to obtain an adjusted target display image; and a correction module, configured to acquire a correction coefficient and correct the target display image based on the correction coefficient.

[0017] Optionally, the correction coefficient is used to ensure that, after calibration, the target brightness of the display is the average brightness of the display, and the target color gamut of the display is the maximum color gamut that can be supported by more than a predetermined proportion of LEDs in the display.

[0018] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein, when the program is running, it controls the device where the non-volatile storage medium is located to execute any image correction method.

[0019] According to another aspect of the embodiments of this application, a processor is also provided, which is used to run a program, wherein the program executes any image correction method during runtime.

[0020] In this embodiment, the brightness and / or saturation of the image to be displayed are controlled by obtaining a first influence parameter of the image to be displayed; determining a first adjustment ratio corresponding to the first influence parameter; and adjusting the image to be displayed based at least on the first adjustment ratio to obtain an adjusted target display image; and correcting the target display image based on a correction coefficient. This achieves the purpose of determining the display parameters to be displayed based on the content of the image to be displayed and automatically adjusting the display parameters of the image to be displayed. This achieves the technical effect of dynamically adjusting the display parameters of the image to be displayed based on the content of the image to be displayed and correcting the dynamically adjusted image to be displayed based on a correction coefficient. This solves the technical problem of excessive loss of brightness and color gamut and poor user experience caused by directly correcting the screen based on a set of correction coefficients without processing the image content in related technologies. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0022] Figure 1 This is a schematic diagram of the architecture of a luminance and chromaticity correction technique in related technologies;

[0023] Figure 2 This is a schematic flowchart of an optional image correction method according to an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of an optional luminance and chromaticity correction architecture according to an embodiment of this application;

[0025] Figure 4 This is a schematic diagram of an optional first mapping relationship curve according to an embodiment of this application;

[0026] Figure 5 This is a schematic diagram of an optional second mapping relationship curve according to an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of an optional third mapping relationship curve according to an embodiment of this application;

[0028] Figure 7 This is a schematic diagram of the structure of an optional image correction device implemented according to this application. Detailed Implementation

[0029] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] To facilitate better understanding of the related embodiments of this application by those skilled in the art, the following are the explanations of some technical terms or partial nouns that may be involved in the related embodiments of this application:

[0032] LED: Chinese name is light emitting diode (English full name: Light Emitting Diode).

[0033] PWM: Pulse Width Modulation, (English full name: Pulse Width Modulation).

[0034] CIE: International Lighting Association

[0035] HSV: Hue (hue), Saturation (saturation), Value (brightness); among them, hue (phase): is the basic attribute of color, which is the usual color name, such as red, yellow, etc.; saturation: refers to the purity of color, the higher the purity, the purer the color, and it gradually becomes gray when it is low, and can take 0-100%.

[0036] High Dynamic Range (HDR) image: A High-Dynamic Range (HDR) image can provide more dynamic range and image details compared to ordinary images.

[0037] According to an embodiment of this application, an image correction method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0038] Figure 2 This is an image correction method according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0039] Step S102: Obtain the first influence parameter of the image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed;

[0040] Step S104: Determine the first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed;

[0041] Step S106: Adjust the image to be displayed based at least on the first adjustment ratio to obtain the adjusted target display image;

[0042] Step S108: Obtain the correction coefficients and correct the target display image based on the correction coefficients.

[0043] It should be noted that the correction coefficient is used to ensure that the target brightness of the display screen after calibration is the average brightness of the display screen, and the target color gamut of the display screen is the maximum color gamut that can be supported by more than a predetermined proportion of LEDs in the display screen.

[0044] In this image correction method, a first influence parameter of the image to be displayed is obtained, wherein the first influence parameter is used to measure the brightness of the image to be displayed; a first adjustment ratio corresponding to the first influence parameter is determined, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; the image to be displayed is adjusted at least based on the first adjustment ratio to obtain the adjusted target display image; the target display image is corrected based on a correction coefficient, wherein the correction coefficient is used to ensure that the target brightness achieved by the display after correction is the average brightness of the display, and the target color gamut achieved by the display is the maximum color gamut that can be supported by more than a predetermined proportion of LEDs in the display. This achieves the purpose of determining the display parameters to be displayed based on the content of the image to be displayed and automatically adjusting the display parameters of the image to be displayed, thereby realizing the technical effect of dynamically adjusting the display parameters of the image to be displayed based on the content of the image to be displayed and correcting the dynamically adjusted image to be displayed based on the correction coefficient. This solves the technical problem of excessive loss of brightness and color gamut and poor user experience caused by correcting the screen based on only one set of correction coefficients in related technologies.

[0045] It should be noted that the above display parameters include, but are not limited to, brightness and saturation. It should also be noted that the larger the color gamut, the higher the saturation.

[0046] This application sets a set of correction coefficients to meet the requirements of no loss in brightness and color gamut, then analyzes the image content based on the image content, and then controls the image content to achieve the purpose of uniform display.

[0047] The working principle of this application is to calibrate the LED screen by setting a calibration target that does not lose brightness and color gamut. This is because it is not that LED screens cannot be calibrated uniformly. Generally, the problem of poor calibration only exists in the case of high brightness or high saturation display. This application makes full use of this characteristic and then automatically analyzes the image content to determine whether the user is more concerned about screen uniformity or display effect (e.g., high brightness, more vivid colors (wider color gamut)). Then, it automatically controls the range of image content displayed to achieve a balance between uniformity and brightness and color gamut without loss.

[0048] The idea behind this invention is to set the goal of no loss in brightness and no loss in color gamut. During the image display process, by analyzing the image content, if the image is a natural image (low brightness, low saturation, and high information content), no control needs to be made on the image content; if the image content is a single grayscale or a single color displayed on the entire screen (low information content), then the image content is controlled within a smaller range (such as display brightness and display color gamut) to achieve uniform display.

[0049] Figure 3 This is a schematic diagram of an optional luminance and chromaticity correction architecture of this application, such as... Figure 3 As shown, from Figure 3 As can be seen, this architecture is not significantly different from luminance and chromaticity correction in related technologies. The collected data is the same as in related technologies; therefore, there is no issue of increased data collection leading to decreased collection efficiency. The main improvements lie in the computation unit during the data acquisition phase and the display phase. Specifically, the computation unit outputs a set of correction coefficients, which can be the coefficients generated by a two-dimensional correction. The correction calculation formula can be written as:

[0050] C(i,j)=f(R) XYZ (i, j), G XYZ (i, j), B XYZ (i, j), Target);

[0051] Where R XYZ (i, j) represents the optical information of the current red light point collected by the acquisition device, which may be the pure brightness Y. R It could also be luminance / chromaticity information under the CIE standard. G XYZ (i, j) represents the optical information of the current green light spot collected by the acquisition device, which may be the pure brightness Y. G It could also be luminance / chromaticity information under the CIE standard. B XYZ (i, j) represents the optical information of the current blue light spot collected by the acquisition device, which may be the pure brightness Y. B It could also be luminance / chromaticity information under the CIE standard. Target represents the correction target, which is typically a three-dimensional matrix.

[0052] A general method for calculating colorimetric correction coefficients:

[0053]

[0054] The Target is set to a target value that does not result in any loss of brightness or color gamut. The simplest implementation is to set the target value to the average of all points.

[0055] During the display phase, image content analysis primarily analyzes the image's mean and saturation, or other analytical data. This data is mainly used to measure whether the human eye perceives uniformity, brightness, or saturation more readily when the image is displayed. For example, when displaying an image where the entire screen is at a certain grayscale level, the human eye is more likely to perceive non-uniformity. However, when displaying natural scene images, the human eye's perception of uniformity is reduced, and people tend to prefer scenes with higher saturation and more vibrant colors. The input is an image, and the output is brightness adjustment parameters and saturation adjustment parameters P.

[0056] P = f1(R, G, B) (3)

[0057] The image content control section automatically adjusts the brightness and saturation of the image to be displayed based on the image mean and image saturation.

[0058]

[0059] Compensation and Correction:

[0060]

[0061] in This indicates the input signal. This refers to the image signal after image content control. This represents the compensated data signal. A represents the result of image analysis. C represents the interpolation result of the correction coefficients.

[0062] Optionally, obtaining the first influence parameter of the image to be displayed includes: obtaining the grayscale value of each pixel in the image to be displayed; determining the first average value corresponding to the image to be displayed based on the average value of the data set composed of the grayscale values ​​of each pixel; and determining the first average value as the first influence parameter. It should be noted that the average value of the data set composed of the grayscale values ​​of each pixel is used as the first average value corresponding to the image to be displayed.

[0063] In some optional embodiments of this application, the image to be displayed is adjusted based at least on a first adjustment ratio, which can be achieved through the following steps: obtaining a second adjustment ratio corresponding to a second influence parameter, wherein the second adjustment ratio is used to adjust the brightness of the image to be displayed; adjusting the image to be displayed according to the first adjustment ratio and the second adjustment ratio, specifically, determining the product of the first adjustment ratio and the second adjustment ratio; and adjusting the image to be displayed based on the product.

[0064] In some optional embodiments of this application, the image to be displayed is adjusted at least based on a first adjustment ratio, including: obtaining a third influence parameter of the image to be displayed, wherein the third influence parameter is used to measure the saturation of the image to be displayed; determining a third adjustment ratio corresponding to the third influence parameter; and then adjusting the image to be displayed according to the third adjustment ratio and the first adjustment ratio. It can be understood that when adjusting the image to be displayed based on the third adjustment ratio and the first adjustment ratio, the brightness and saturation of the image to be displayed are adjusted respectively.

[0065] Optionally, the second influence parameter of the image to be displayed can be determined as follows: obtain the gray value of each pixel in the image to be displayed, determine the first standard deviation of the image to be displayed based on the standard deviation of the data set composed of the gray values ​​of each pixel, and use the first standard deviation as the second influence parameter. It should be noted that the standard deviation of the data set composed of the gray values ​​of each pixel can be used as the first standard deviation of the image to be displayed.

[0066] Optionally, the third influence parameter of the image to be displayed can be obtained in the following way: obtain the saturation of each pixel in the image to be displayed, and determine the second average value of the image to be displayed based on the average value of the data set composed of the saturation of each pixel; determine the second average value as the third influence parameter. It should be noted that the average value of the data set composed of the saturation of each pixel can be used as the second average value of the image to be displayed.

[0067] In some optional embodiments of this application, determining the first adjustment ratio corresponding to the first influencing parameter can be achieved by: obtaining a first mapping relationship between the first influencing parameter and the first adjustment ratio, and determining the first adjustment ratio corresponding to the first influencing parameter based on the first mapping relationship; determining the second adjustment ratio corresponding to the second influencing parameter can be achieved by: obtaining a second mapping relationship between the second influencing parameter and the second adjustment ratio, and determining the second adjustment ratio corresponding to the second influencing parameter based on the second mapping relationship; determining the third adjustment ratio corresponding to the third influencing parameter can be achieved by: obtaining a third mapping relationship between the third influencing parameter and the third adjustment ratio, and determining the third adjustment ratio corresponding to the third influencing parameter based on the third mapping relationship. It should be noted that the aforementioned first, second, and third mapping relationships can be functional relationships or graphical curves.

[0068] For example, suppose the brightness emitted by four LEDs at 255 grayscale is 67 nits, 80 nits, 100 nits, and 125 nits, respectively.

[0069] According to traditional calibration methods, the standard calibration target would be set to 67 nits. Therefore, the calibration coefficients would be 1.0, 0.8375, 0.67, and 0.536. That is, all calibration coefficients are less than 1.0, meaning all LEDs can display the same calibration target. For example, a 255-level grayscale can display 67 nits; a 128-level grayscale can display 33.5 nits.

[0070] If the calibration target is set to 100 nits, then the calibration compensation coefficients are: 1.5, 1.25, 1.0, and 0.8. Intuitively, it might seem that a calibration coefficient greater than 1 would be insufficient to achieve the calibration target for some LEDs. For example, the first LED's maximum brightness is only 67 nits, making it impossible to display 100 nits. However, the actual brightness requirement for a 128-grayscale display is 50 nits, which all LEDs can achieve. Therefore, using this calibration coefficient, the screen can still be calibrated very uniformly across the 128-grayscale.

[0071] Setting the target brightness to 100 nits (as in the example) without loss, during image display, by analyzing the image content, in some optional embodiments of this application, if the image is a natural image, the image content can be left uncontrolled, i.e., the image display parameters can be left unadjusted. For example, brightness and saturation can be left unadjusted. If the image content is a single grayscale or color displayed across the entire screen, then by controlling the image content within a smaller brightness range (e.g., display brightness less than 67), uniformity can be achieved. The advantage of this is that brightness is not lost after correction. When displaying natural images, the human eye is not sensitive to uniformity, so a certain degree of uniformity can be sacrificed.

[0072] Specifically, the average image brightness (APL) can be calculated first (i.e., the first influence parameter), and then the brightness control ratio (LRatio1) can be obtained by looking up a table. Figure 4 This is a schematic diagram of an optional first mapping relationship in this application, wherein the first mapping relationship is a curve graph, the horizontal axis is the average image brightness APL (i.e., the first influence parameter), and the vertical axis is the brightness control ratio (i.e., the first adjustment ratio). Optionally, APL can be expressed by the formula APL = AVG(MAX(R, G, B)).

[0073] Then, the information content of the image can be calculated, and the information content can be used to distinguish whether the image is a natural image or a grayscale image. The information content can be calculated by calculating the standard deviation (STD) of the image grayscale (i.e., the second influence parameter), and then normalizing the STD. Figure 5 This is a schematic diagram of an optional second mapping relationship in this application. The second mapping relationship is a curve graph, where the horizontal axis represents the standard deviation of image grayscale (i.e., the second influencing parameter), and the vertical axis represents the grayscale control ratio (i.e., the second adjustment ratio). The curve is shown below. Figure 5 As shown, the grayscale control ratio Lratio2 (the second adjustment ratio) is obtained. Finally, the brightness control ratio Ratio for the image is Ratio = LRatio1 * LRatio2 (that is, the product of the first adjustment ratio and the second adjustment ratio is determined). After adjustment based on this brightness control ratio Ratio, the brightness-adjusted image can be corrected based on the correction coefficient.

[0074] For example, some customers are concerned about excessive loss of color gamut after correction. This solution can automatically adjust the display brightness and saturation of the displayed content to achieve the best display effect. The correction target value can still be calculated based on no loss of brightness and no loss of color gamut.

[0075]

[0076] Correction factor calculation:

[0077]

[0078] Image content analysis, analyzing image brightness and saturation:

[0079] The image brightness calculation process involves first calculating the image brightness mean (APL) (i.e., the first influencing parameter), and then... Figure 4 The curve shown yields the brightness control LRatio1 (i.e., the first adjustment ratio), where APL can be expressed by the following formula:

[0080] APL = AVG(MAX(R, G, B));

[0081] Then, saturation calculation is performed, which calculates the average saturation value (Savg) of all pixels (i.e., the third influencing parameter). Figure 6 This is a schematic diagram of an optional third mapping relationship in this application, wherein the third mapping relationship is a curve graph, the horizontal axis of which is the saturation mean Savg (i.e., the third influencing parameter), and the vertical axis is the saturation control SRatio (i.e., the third adjustment ratio), and then through, as shown in... Figure 6 The curve shown yields the saturation control SRatio (i.e., the third adjustment ratio), where Savg and Sat are calculated using the following formulas:

[0082] Savg = AVG(Sat(R, G, B));

[0083]

[0084] Then, the brightness and saturation of the image to be displayed are adjusted based on the first adjustment ratio and the third adjustment ratio respectively to obtain the adjusted brightness and saturation. Finally, the adjusted display image is corrected based on the set correction coefficient.

[0085] In some embodiments of this application, the image to be displayed may include an RGB format image. Therefore, adjusting the image to be displayed based at least on a first adjustment ratio to obtain an adjusted target display image includes: converting the RGB format image to be displayed into HSV format; adjusting the HSV format image to be displayed based at least on a first adjustment ratio to obtain an adjusted HSV format target display image; and converting the HSV format target display image into an RGB format target display image. It is understood that correcting the target display image based on a correction coefficient includes: correcting the RGB format target display image based on a correction coefficient.

[0086] Specifically, the image RGB signal can first be converted to an HSV signal. Then, the V signal is adjusted using LRatio to obtain Vo, and the S signal is adjusted using SRatio to obtain So. Finally, the adjusted H SoVo is converted to RaGaBa. RGB2HSV and HSV2RGB are standard conversions between RGB and HSV.

[0087] HSV = RGB2HSV(R, G, B)

[0088] Vo=V*LRatio

[0089] So = S * SRatio

[0090] R a G a B a =HSV2RGB(H, So, Vo)

[0091] Finally, perform corrections:

[0092]

[0093] The above steps enable automatic control of image content. When the image mean is high, the image brightness is too high, and the LED screen cannot achieve uniformity. Therefore, the brightness coefficient needs to be reduced to ensure the brightness uniformity of the display screen. When the image saturation is high, it indicates that the image is more vibrant. In such scenarios, the human eye prefers more vibrant images. Therefore, adjusting the saturation parameter closer to 1.0 will result in a more vibrant image.

[0094] Figure 7 This application provides an optional image correction device, such as... Figure 7 As shown, the device includes:

[0095] The acquisition module 40 is used to acquire the first influence parameter of the image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed;

[0096] The determining module 42 is used to determine the first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed;

[0097] Adjustment module 44 is used to adjust the image to be displayed based at least on a first adjustment ratio to obtain the adjusted target display image;

[0098] The correction module 46 is used to obtain correction coefficients and correct the target display image based on the correction coefficients.

[0099] It should be noted that the correction coefficient is used to ensure that the target brightness of the display screen after calibration is the average brightness of the display screen, and the target color gamut of the display screen is the maximum color gamut that can be supported by more than a predetermined proportion of LEDs in the display screen.

[0100] In this image correction device, the acquisition module 40 is used to acquire a first influence parameter of the image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; the determination module 42 is used to determine a first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; the adjustment module 44 is used to adjust the image to be displayed based at least on the first adjustment ratio to obtain the adjusted target display image; and the correction module 46 is used to correct the target display image based on a correction coefficient, wherein the correction coefficient is used so that after the display screen is corrected, the target brightness achieved by the display screen is the average brightness of the display screen, and the target color gamut achieved by the display screen is the maximum color gamut that can be supported by more than a predetermined proportion of LED beads in the display screen. This achieves the purpose of determining the display parameters to be displayed based on the content of the image to be displayed and automatically adjusting the display parameters of the image to be displayed, thereby realizing the technical effect of dynamically adjusting the display parameters of the image to be displayed based on the content of the image to be displayed and correcting the dynamically adjusted image to be displayed based on the correction coefficient. This solves the technical problem of excessive loss of brightness and color gamut and poor user experience caused by directly correcting the screen based on a set of correction coefficients without processing the image content in related technologies.

[0101] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein, when the program is running, it controls the device where the non-volatile storage medium is located to execute any image correction method.

[0102] Specifically, the aforementioned storage medium is used to store program instructions that perform the following functions: obtaining a first influence parameter of an image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; determining a first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; adjusting the image to be displayed based at least on the first adjustment ratio to obtain an adjusted target display image; obtaining a correction coefficient, and correcting the target display image based on the correction coefficient.

[0103] According to another aspect of the embodiments of this application, a processor is also provided, which is used to run a program, wherein the program executes any image correction method during runtime.

[0104] Specifically, the processor is used to call program instructions in memory to perform the following functions: obtain a first influence parameter of the image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; determine a first adjustment ratio corresponding to the first influence parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; adjust the image to be displayed based at least on the first adjustment ratio to obtain the adjusted target display image; obtain a correction coefficient, and correct the target display image based on the correction coefficient.

[0105] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0106] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0108] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0109] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0110] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0111] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of correcting an image, characterized by, include: Obtain a first influence parameter of the image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; Determine a first adjustment ratio corresponding to the first influencing parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; The image to be displayed is adjusted based at least on the first adjustment ratio to obtain the adjusted target display image; Obtain correction coefficients, and correct the target display image based on the correction coefficients. The correction coefficients are used to ensure that the target brightness of the LED display screen after correction is the average brightness of the display screen, and the target color gamut of the display screen is the maximum color gamut that can be supported by more than a predetermined proportion of LED beads in the display screen. Wherein, adjusting the image to be displayed based at least on the first adjustment ratio includes: Obtain a second influence parameter of the image to be displayed, wherein the second influence parameter is used to measure the brightness of the image to be displayed; Determine the second adjustment ratio corresponding to the second influencing parameter, wherein the second adjustment ratio is used to adjust the brightness of the image to be displayed; The image to be displayed is adjusted according to the product of the first adjustment ratio and the second adjustment ratio; or Obtain the third influence parameter of the image to be displayed, wherein the third influence parameter is used to measure the saturation of the image to be displayed; Determine the third adjustment ratio corresponding to the third influencing parameter, wherein the third adjustment ratio is used to adjust the saturation level of the image to be displayed; The image to be displayed is adjusted according to the third adjustment ratio and the first adjustment ratio.

2. The method of claim 1, wherein, Obtain the first impact parameters of the image to be displayed, including: Obtain the grayscale value of each pixel in the image to be displayed; The first average value corresponding to the image to be displayed is determined based on the average value of the data set composed of the gray values ​​of each pixel. The first average value is determined as the first influencing parameter.

3. The method according to claim 1, characterized in that, Obtaining the second influence parameter of the image to be displayed includes: Obtain the grayscale value of each pixel in the image to be displayed; The first standard deviation of the image to be displayed is determined based on the standard deviation of the data set composed of the gray values ​​of each pixel. The first standard deviation is determined as the second influence parameter.

4. The method of claim 1, wherein, Obtaining the third influence parameter of the image to be displayed includes: Obtain the saturation of each pixel in the image to be displayed; The second average value corresponding to the image to be displayed is determined based on the average value of the data set composed of the saturation of each pixel. The second average value is determined as the third influencing parameter.

5. The method according to claim 1, characterized in that, Determining the first adjustment ratio corresponding to the first influence parameter includes: obtaining a first mapping relationship between the first influence parameter and the first adjustment ratio, and determining the first adjustment ratio corresponding to the first influence parameter based on the first mapping relationship; Determining the second adjustment ratio corresponding to the second influence parameter includes: obtaining a second mapping relationship between the second influence parameter and the second adjustment ratio, and determining the second adjustment ratio corresponding to the second influence parameter based on the second mapping relationship; Determining the third adjustment ratio corresponding to the third influencing parameter includes: obtaining a third mapping relationship between the third influencing parameter and the third adjustment ratio, and determining the third adjustment ratio corresponding to the third influencing parameter based on the third mapping relationship.

6. The method of claim 1, wherein, The image to be displayed includes: an RGB format image to be displayed, wherein the image to be displayed is adjusted based at least on the first adjustment ratio to obtain an adjusted target display image, including: Convert the RGB format image to be displayed into HSV format; The HSV format image to be displayed is adjusted based at least on the first adjustment ratio to obtain the adjusted target display image in the HSV format; The target display image in HSV format is converted into the target display image in RGB format.

7. An image correction device characterized by comprising: include: An acquisition module is used to acquire a first influence parameter of the image to be displayed, wherein the first influence parameter is used to measure the brightness of the image to be displayed; A determining module is used to determine a first adjustment ratio corresponding to the first influencing parameter, wherein the first adjustment ratio is used to adjust the brightness of the image to be displayed; An adjustment module is used to adjust the image to be displayed based at least on the first adjustment ratio to obtain an adjusted target display image; A correction module is used to obtain correction coefficients and correct the target display image based on the correction coefficients. The correction coefficients are used so that after the LED display screen is corrected, the target brightness achieved by the display screen is the average brightness of the display screen, and the target color gamut achieved by the display screen is the maximum color gamut that can be supported by more than a predetermined proportion of LED beads in the display screen. Wherein, adjusting the image to be displayed based at least on the first adjustment ratio includes: Obtain a second influence parameter of the image to be displayed, wherein the second influence parameter is used to measure the brightness of the image to be displayed; Determine the second adjustment ratio corresponding to the second influencing parameter, wherein the second adjustment ratio is used to adjust the brightness of the image to be displayed; The image to be displayed is adjusted according to the product of the first adjustment ratio and the second adjustment ratio; or Obtain the third influence parameter of the image to be displayed, wherein the third influence parameter is used to measure the saturation of the image to be displayed; Determine the third adjustment ratio corresponding to the third influence parameter, wherein the third adjustment ratio is used to adjust the saturation level of the image to be displayed; The image to be displayed is adjusted according to the third adjustment ratio and the first adjustment ratio.

8. A non-volatile storage medium, comprising: The non-volatile storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the non-volatile storage medium to perform the image correction method according to any one of claims 1 to 6.

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