Local dimming method for eliminating halo

Abstract

The invention provides a local dimming method for eliminating halo, which is applied to the field of liquid crystal display. According to the method, an RGB image is converted into a grey-scale image, then initial local and global backlight values are calculated through a cumulative distribution function method and a high-gray-scale averaging method, then pixel point ratios meeting the three conditions of low pixel values, pixel point flatness and adjacent backlight brightness are counted to quantify the halo risk, and finally the weight is calculated based on the pixel statistical value and the ambient illuminance. And fusing global and local backlight values to eliminate halo. According to the method, the halo area is accurately positioned through Sobel operator detection and neighborhood backlight threshold judgment, the image quality and energy consumption are balanced in combination with the CDF and the high-gray-scale averaging method, adaptive adjustment is achieved by introducing ambient light parameters, halo can be effectively inhibited, and the method is suitable for various LCD devices.

Description

Technical Field

[0001] This invention relates to the field of liquid crystal displays, specifically to a local dimming method for eliminating halos. Background Technology

[0002] Currently, Liquid Crystal Displays (LCDs) generally use ordinary Light Emitting Diodes (LEDs) or even smaller mini-LEDs as backlights. Backlight adjustment technology in LCDs is widely used because it effectively improves image contrast and saves energy. When the displayed image is dark, if the backlight is fully on, light leakage from the liquid crystal can cause excessive brightness in dark scenes, resulting in lower contrast and higher power consumption. Backlight adjustment technology, however, can adjust the backlight brightness in real time according to the content of the displayed image. That is, when displaying a dark scene, the backlight brightness can be appropriately reduced, or even turned off when displaying a completely black image. In this way, backlight adjustment technology can reduce power consumption and improve image contrast.

[0003] Backlight adjustment technology can be divided into three types: global dimming (0D dimming), linear dimming (1D dimming), and local dimming (2D dimming, or local dimming). Global dimming adjusts the backlight uniformly based on the image content. Linear dimming divides the backlight into rows or columns and adjusts their respective backlight values. Local dimming divides the backlight into zones and dynamically adjusts the backlight value of each zone. Compared to global and linear dimming, local dimming adaptively determines the backlight value based on the local content of the displayed image, which can significantly improve display contrast, reduce power consumption, and extend the lifespan of the display device. However, local dimming can produce a halo effect, affecting the visual experience. Summary of the Invention

[0004] The purpose of this invention is to provide a local dimming method for eliminating halos, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a local dimming method for eliminating halos, comprising the following steps: Step 1: Convert RGB image to grayscale image: For the input RGB image, calculate the maximum value of the three sub-pixels (red, green, and blue) to obtain the grayscale image; Step 2, Backlight Value Calculation: Calculate the initial local backlight value and global backlight value based on the input RGB image content; specifically, use the cumulative distribution function method and the high grayscale mean method to calculate the initial local backlight value and global backlight value of the RGB image. Step 3, Pixel Value Statistics: Count the number of pixels in the RGB image that simultaneously meet the three conditions for halo, and then divide by the total number of pixels in the image to obtain the halo pixel ratio value; the three conditions for halo generation are: low pixel value, flat pixels, and brighter adjacent backlight; Step 4: Backlight value adjustment: Combine the global backlight value calculated in step 2 with the local backlight value to eliminate halo effect.

[0006] Preferably, the specific calculation logic for the backlight value is as follows: Assume the number of backlight zones in the input RGB image is Similarly, the input RGB image content is then divided into segments corresponding to the backlight. Each region is analyzed; the probability density function of the grayscale image is calculated for each region, where the integral of the probability density function is the cumulative distribution function. Let the probability density function be... , The grayscale value represents the range of its values. ,function The range of values ​​is Cumulative distribution function , and The grayscale value represents the range of its values. , The range of values ​​is ,when equal to threshold The corresponding gray value at time , This is the backlight value of the backlight area using the cumulative distribution function method, denoted as... ,in ; Integrating the probability density function with respect to gray levels from largest to smallest yields another cumulative distribution function, denoted as . The function expression is ,when equal to threshold The corresponding grayscale value is The grayscale value in the calculation area is not less than this value. The average value of the pixels is used to obtain the backlight value of this area using the high brightness average method, denoted as . ,in ; The backlight value for this area is obtained by weighted averaging the backlight value obtained by the cumulative distribution function threshold method and the backlight value obtained by the high brightness mean method. The specific calculation formula is as follows: ; in, For parameters, .

[0007] Preferably, the three conditions for achieving a halo in step 3 are as follows: Condition 1: Low pixel value; if the grayscale value of a pixel is less than the threshold. ,for example Then condition 1 is satisfied; Condition 2: The pixels are flat. The Sobel operator is used to calculate the gradient magnitude of each pixel. If the gradient magnitude is below a threshold... ,for example Then condition 2 is satisfied; Condition 3: The adjacent backlight is relatively bright, so obtain the backlight area where the pixel is located. Neighborhood backlight value, if The maximum value of the window exceeds a certain threshold of the backlight value of the area it is in. ,for example Then condition 3 is satisfied; The number of pixels that simultaneously meet all three conditions for a halo is counted and accumulated, then divided by the total number of pixels in the image to obtain the halo pixel ratio value, denoted as . .

[0008] Preferably, the specific implementation logic of the backlight value adjustment is as follows: First, calculate the halo weight based on the pixel statistics and ambient light intensity in step 3; then, based on the halo weight, mix the local backlight and global backlight to adjust the local backlight value, specifically: First, based on the halo pixel ratio in step 3... Adjustment weight The calculation is as follows: ; in, , , For parameters; Then, the ambient light sensor acquires the surrounding light conditions of the RGB image displayed on the LCD screen, and outputs an illuminance value reflecting the ambient brightness; the unit of ambient light illuminance is lux, denoted as . Based on ambient light intensity values Adjustment weight The calculation is as follows: ; in, , , For parameters; Multiply the two weights above together to obtain the local backlight adjustment weight: ; Finally, based on the weight adjustment of local backlight, the adjusted backlight value is obtained by mixing the local backlight and global backlight as follows: ; in, These represent the vertical and horizontal index values ​​of the backlight area, respectively.

[0009] Compared with the prior art, the beneficial effects of the present invention are: The local dimming method for eliminating halos proposed in this invention integrates multiple technical steps, including grayscale image conversion, backlight value calculation, pixel statistics, and dynamic weight adjustment. This method not only solves the halos problem in local dimming of liquid crystal displays but also achieves comprehensive optimization of image quality, power consumption, and visual experience. Specific beneficial effects are as follows: 1. Precisely eliminate halos and improve display quality Halo recognition based on multi-condition pixel statistics: By setting three quantization conditions—low pixel value, flat pixel distribution, and brighter adjacent backlight—the ratio of pixels related to halo is accurately calculated, avoiding the fuzzy judgment of halo phenomena by traditional methods. This quantization standard combines local image features with backlight distribution, enabling real-time capture of halo-prone areas (such as the edges of bright objects against a dark background), providing a precise basis for subsequent backlight adjustments. Dynamic fusion of global and local backlight is also implemented.

[0010] When the detected halo pixel ratio exceeds a threshold, the global backlight and local backlight are merged according to the weights calculated by using ambient light intensity and pixel statistics. This method retains the contrast-enhancing effect of local dimming while suppressing light leakage caused by adjacent bright areas through global backlighting, fundamentally eliminating halos and making dark scene details clearer (such as sharper boundaries between dark and bright stars in a starry sky image, without any whitening).

[0011] II. Optimize backlight calculation logic to balance power consumption and image quality. The cumulative distribution function (CDF) combined with the high grayscale averaging method and CDF thresholding: By setting a threshold T1, the grayscale values ​​corresponding to pixels within a region are obtained, ensuring that the backlight value can cover the brightness requirements of most pixels and avoiding power waste caused by excessive brightness. High grayscale averaging method: The average value is calculated only for high grayscale pixels, focusing on preserving the bright details of the image (such as sunset and lights) and preventing distortion in bright areas caused by the overall reduction of backlight.

[0012] The weighted average method reduces backlight power consumption in dark scenes while ensuring that the image quality of high grayscale content is not distorted, solving the problems of high power consumption in the traditional maximum value method and loss of detail in the average value method.

[0013] Intelligent switching between local backlighting and global dimming: When the risk of halo is low, local dimming is the main method to improve contrast; when the risk of halo is high (such as bright objects in dark environments), the proportion of global backlighting is automatically increased to eliminate halo while avoiding the overall darkness of the image caused by excessive adjustment of local backlighting, thus achieving an intelligent balance of "on-demand dimming".

[0014] III. Strong environmental adaptability enhances the user's visual experience. Ambient light intensity linkage adjustment: By acquiring illuminance values ​​through an ambient light sensor, when the ambient light is dim (such as in nighttime scenes), the local backlight weight is automatically reduced to enhance the anti-halo effect of the global backlight, which aligns with the human eye's greater sensitivity to halos in dark environments. When the ambient light is bright, the contrast advantage of local dimming is prioritized to reduce power consumption. This dynamic adjustment ensures that the monitor maintains optimal visual performance under different lighting conditions (such as clearer text display under strong outdoor light and no halo interference in movie scenes under low indoor light).

[0015] Adjustable and versatile design: Key parameters can be flexibly adjusted according to different display hardware (such as the number of mini-LED backlight zones and the light leakage characteristics of the LCD panel) and usage scenarios, making it highly adaptable and applicable to various LCD devices such as TVs, computer monitors, and automotive screens, thus avoiding the limitations of traditional fixed parameter methods.

[0016] IV. Technological Innovation and Industry Application Value Multi-dimensional halo suppression mechanism: Unlike the method of eliminating halo by simply reducing the brightness of the backlight zone, this invention forms a complete technical chain from "halo detection - backlight calculation - weight fusion". For the first time, it combines pixel gradient features, neighborhood backlight distribution and ambient light intensity to build a more comprehensive halo suppression model, providing a new technical path for the optimization of local dimming technology.

[0017] In summary, this invention, through a quantified halo detection standard, an intelligent backlight fusion algorithm, and an environmental adaptive mechanism, efficiently solves the halo problem of local dimming in liquid crystal displays without sacrificing image quality and power consumption, demonstrating significant technological advancement and practical application value. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the cumulative distribution function thresholding method of the present invention; Figure 3 This is a schematic diagram of the high brightness averaging method of the present invention. Detailed Implementation

[0019] 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 embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1-3 This invention provides a technical solution: a local dimming method for eliminating halos, comprising the following steps: Step 1: Convert RGB image to grayscale image: For the input RGB image, calculate the maximum value of the three sub-pixels (red, green, and blue) to obtain the grayscale image; Step 2, Backlight Value Calculation: Calculate the initial local and global backlight values ​​based on the input RGB image content. Specifically, the cumulative distribution function method and the high grayscale mean method are used to calculate the initial local and global backlight values ​​of the RGB image. The specific calculation logic is as follows: Assume the number of backlight zones in the input RGB image is Similarly, the input RGB image content is then divided into segments corresponding to the backlight. Each region is analyzed; the probability density function of the grayscale image is calculated for each region, where the integral of the probability density function is the cumulative distribution function. Let the probability density function be... , The grayscale value represents the range of its values. ,function The range of values ​​is Cumulative distribution function , and The grayscale value represents the range of its values. , The range of values ​​is ,like Figure 2 Example Select threshold ,for example The gray value corresponding to the threshold (Scope) ), This refers to the backlight value of the cumulative distribution function method for this backlight area (range: ), denoted as ,in ; Integrating the probability density function with respect to gray levels from largest to smallest yields another cumulative distribution function, denoted as . The function expression is ,like Figure 3 Example, selecting a threshold ,for example The threshold corresponding to grayscale value (Scope) The calculation area is not less than The average gray value of the pixels , This refers to the average backlight value of the high brightness of this backlight area (range: ), denoted as ,in ; The backlight value for this area is obtained by weighted averaging the backlight value obtained by the cumulative distribution function threshold method and the backlight value obtained by the high brightness mean method. The specific calculation formula is as follows:

[0021] in, For parameters, .

[0022] The above describes how to calculate the regional backlight value. The global backlight value can be calculated using the same method, denoted as... .

[0023] It should be noted that common methods for calculating dynamic backlight values ​​include the maximum value method, the weighted average method, and the Cumulative Distribution Function (CDF) threshold method. To balance image quality and energy efficiency, this invention combines the CDF method with the high grayscale average method to calculate the backlight value. This invention's backlight calculation method effectively reduces energy consumption while maintaining image quality, especially high grayscale quality. The high grayscale average method refers to calculating the average value only for a certain proportion of high grayscale pixels in the image, using this as the backlight value.

[0024] The methods for calculating local backlighting and global backlighting are the same. Local backlighting is calculated based on the image content of a local region, while global backlighting is calculated based on the entire image content.

[0025] Step 3: Pixel Value Statistics: Count and accumulate the number of pixels in the RGB image that simultaneously meet the three conditions for halo effect, then divide by the total number of pixels in the image to obtain the halo pixel ratio. The three conditions for halo effect are: low pixel value, flat pixel distribution, and bright adjacent backlight. The specific details of meeting the three conditions for halo effect are as follows: Condition 1: Low pixel value; if the grayscale value of a pixel is less than the threshold. ,for example Then condition 1 is satisfied; Condition 2: The pixels are flat. The Sobel operator is used to calculate the gradient magnitude of each pixel. If the gradient magnitude is below a threshold... ,for example Then condition 2 is satisfied; Condition 3: The adjacent backlight is relatively bright, so obtain the backlight area where the pixel is located. Neighborhood backlight value, if The maximum value of the window exceeds a certain threshold of the backlight value of the area it is in. ,for example Then condition 3 is satisfied; The number of pixels that simultaneously meet all three conditions for a halo is counted and accumulated, then divided by the total number of pixels in the image to obtain the halo pixel ratio value, denoted as . .

[0026] It should be noted that halo effects are more likely to occur when the background light is bright in the vicinity of flat, dark pixels in an image. Furthermore, halo effects are only perceptible when the ambient light is low. Therefore, based on the conditions for halo occurrence, this invention's method counts the number of pixels that simultaneously meet three conditions: low pixel value, flat pixel, and bright adjacent background light. Based on the number of pixels in the image that meet these conditions, this invention determines whether a halo has occurred. The more pixels that meet the conditions, the more likely a halo effect is to occur. Because global dimming does not produce halos, when a halo occurs and the ambient light is low enough to detect it, this invention's method integrates global dimming and local dimming, mixing the local backlight value with the global backlight value, thus eliminating the halo effect. Step 4: Backlight Value Adjustment: The global backlight value calculated in Step 2 is merged with the local backlight value to eliminate the halo effect. The specific implementation logic is as follows: First, the halo weight is calculated based on the pixel statistics and ambient light intensity in Step 3; then, the local backlight is mixed with the global backlight based on the halo weight to adjust the local backlight value. Specifically: First, based on the halo pixel ratio in step 3... Adjustment weight The calculation is as follows: ; in, , , For parameters; Then, the ambient light sensor acquires the surrounding light conditions of the RGB image displayed on the LCD screen, and outputs an illuminance value reflecting the ambient brightness; the unit of ambient light illuminance is lux, denoted as . Based on ambient light intensity values Adjustment weight The calculation is as follows: ; in, , , For parameters; Multiply the two weights above together to obtain the local backlight adjustment weight: ; Finally, based on the weight adjustment of local backlight, the adjusted backlight value is obtained by mixing the local backlight and global backlight as follows:

[0027] in, These represent the vertical and horizontal index values ​​of the backlight area, respectively.

[0028] This invention discloses a local dimming method for eliminating halos in liquid crystal displays, aiming to address the impact of halos on visual effects in local dimming technology. The method achieves intelligent backlight adjustment through a multi-step technical logic, specifically including: converting an RGB image to a grayscale image; calculating initial local and global backlight values ​​using the cumulative distribution function method and the high grayscale mean method; statistically analyzing the pixel ratio that meets the three conditions of "low pixel value, flat pixel size, and brighter adjacent backlight" to quantify the halos risk; and calculating a hybrid weight based on pixel statistics and ambient light intensity to dynamically fuse global and local backlight values ​​to eliminate halos.

[0029] The core innovation of this invention lies in: combining Sobel operator gradient magnitude detection and flat pixel analysis, The method employs a neighborhood backlight threshold determination to accurately locate halo-prone areas. It uses a weighted calculation of the backlight value using both the CDF threshold method and the high grayscale mean method to balance image quality and energy consumption. Furthermore, it incorporates ambient light parameters to achieve adaptive adjustment under different lighting conditions. Experimental results show that this method effectively suppresses halo phenomena caused by local dimming in LCD displays while ensuring high grayscale image quality remains undistorted. It is applicable to various LCD devices such as televisions and monitors.

[0030] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for local dimming to eliminate halos, characterized in that, Includes the following steps: Step 1: Convert RGB image to grayscale image: For the input RGB image, calculate the maximum value of the three sub-pixels (red, green, and blue) to obtain the grayscale image; Step 2, Backlight Value Calculation: Calculate the initial local backlight value and global backlight value based on the input RGB image content; specifically, use the cumulative distribution function method and the high grayscale mean method to calculate the initial local backlight value and global backlight value of the RGB image. Step 3, Pixel Value Statistics: Count the number of pixels in the RGB image that simultaneously meet the three conditions for halo, and then divide by the total number of pixels in the image to obtain the halo pixel ratio value; the three conditions for halo generation are: low pixel value, flat pixels, and brighter adjacent backlight; Step 4: Backlight value adjustment: Combine the global backlight value calculated in step 2 with the local backlight value to eliminate halo effect.

2. The local dimming method for eliminating halos according to claim 1, characterized in that, The specific calculation logic for the backlight value is as follows: Assume the number of backlight zones in the input RGB image is Similarly, the input RGB image content is then divided into segments corresponding to the backlight. Each region is analyzed; the probability density function of the grayscale image is calculated for each region, where the integral of the probability density function is the cumulative distribution function. Let the probability density function be... , The grayscale value represents the range of its values. ,function The range of values ​​is Cumulative distribution function , and The grayscale value represents the range of its values. , The range of values ​​is ,when equal to threshold The corresponding gray value at time , This is the backlight value of the backlight area using the cumulative distribution function method, denoted as... ,in ; Integrating the probability density function with respect to gray levels from largest to smallest yields another cumulative distribution function, denoted as . The function expression is ,when equal to threshold The corresponding grayscale value is The grayscale value in the calculation area is not less than this value. The average value of the pixels is used to obtain the backlight value of this area using the high brightness average method, denoted as . ,in ; The backlight value for this area is obtained by weighted averaging the backlight value obtained by the cumulative distribution function threshold method and the backlight value obtained by the high brightness mean method. The specific calculation formula is as follows: ； in, For parameters, .

3. The local dimming method for eliminating halos according to claim 1, characterized in that, The specific details of satisfying the three conditions for the halo in step 3 are as follows: Condition 1: Low pixel value; if the grayscale value of a pixel is less than the threshold. Then condition 1 is satisfied; Condition 2: The pixels are flat. The Sobel operator is used to calculate the gradient magnitude of each pixel. If the gradient magnitude is below a threshold... Then condition 2 is satisfied; Condition 3: The adjacent backlight is relatively bright, so obtain the backlight area where the pixel is located. Neighborhood backlight value, if The maximum value of the window exceeds a certain threshold of the backlight value of the area it is in. Then condition 3 is satisfied; The number of pixels that simultaneously meet all three conditions for a halo is counted and accumulated, then divided by the total number of pixels in the image to obtain the halo pixel ratio value, denoted as . .

4. The local dimming method for eliminating halos according to claim 1, characterized in that: The specific implementation logic for adjusting the backlight value is as follows: First, calculate the halo weight based on the pixel statistics and ambient light intensity in step 3; then, based on the halo weight, mix the local backlight with the global backlight to adjust the local backlight value. Specifically: First, based on the halo pixel ratio in step 3... Adjustment weight The calculation is as follows: ； in, , , For parameters; Then, the ambient light sensor acquires the surrounding light conditions of the RGB image displayed on the LCD screen, and outputs an illuminance value reflecting the ambient brightness; the unit of ambient light illuminance is lux, denoted as . Based on ambient light intensity values Adjustment weight The calculation is as follows: ； in, , , For parameters; Multiply the two weights above together to obtain the local backlight adjustment weight: ； Finally, based on the weight adjustment of local backlight, the adjusted backlight value is obtained by mixing the local backlight and global backlight as follows: ； in, These represent the vertical and horizontal index values ​​of the backlight area, respectively.

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