A backlight drive control method and system based on Local Dimming algorithm

Abstract

The invention discloses a backlight driving control method and system based on a Local Dimming algorithm, and relates to the field of display technology. The method comprises the following steps: determining the position of a moving object in a current frame image and a next frame image, and a boundary area of ​​the moving object; for a region image only containing the boundary area and the moving object, dividing a backlight module where a highlight region block of the current frame and the next frame region image is located into a plurality of independent control regions; for the current frame region image and the next frame region image, calculating a target brightness difference of the same control region, and sending a brightness control instruction to a control unit of the corresponding control region in advance in combination with a delayed response time; traversing each pixel point in a dark region and a highlight region in the current frame region image, and performing linear transformation on pixel points whose grayscale values ​​are lower than a dark threshold or whose grayscale values ​​are higher than a highlight threshold, so as to improve the image tailing phenomenon and avoid grayscale loss.

Description

Technical Field

[0001] The present invention relates to the field of display technology, and in particular to a backlight driving control method and system based on a Local Dimming algorithm. Background Art

[0002] With the continuous development of display technology, users have higher and higher requirements for the image quality of display devices, especially in terms of contrast, black performance and color details. The basic principle of the Local Dimming algorithm is to divide the backlight source (usually LED) into multiple independently controlled areas or blocks, and each block can independently adjust the brightness according to the needs of the displayed content. This technology can reduce the brightness in areas where deep black needs to be displayed, and increase the brightness in areas where bright details need to be displayed, thereby achieving better visual effects. The specific implementation steps include image analysis, regional brightness control, backlight adjustment and smooth transition.

[0003] In a Chinese invention application with application publication number CN105405412A, a backlight drive control method and system are disclosed, which are applied to a display terminal with a liquid crystal display screen. The display terminal includes an MCU and a backlight source. The backlight source includes a plurality of light strips formed by LED lights and a plurality of driver ICs. Each driver IC controls one or more light strips. The method includes the following steps: when the MCU receives an electrical signal from each LED light, demodulating the electrical signal from each LED light to obtain a brightness value of each LED light; comparing the brightness values ​​of each LED light in each driver IC to obtain a maximum brightness value of the LED light in each driver IC; dividing the maximum brightness value of the LED light in each driver IC into a plurality of brightness intervals, determining a current value corresponding to each brightness interval, and controlling the brightness of the LED light in the driver IC according to the current value.

[0004] The above application improves the energy saving effect of Local Dimming drive and the contrast of screen display. However, the following deficiencies still exist in combination with the existing technology:

[0005] (1) In existing display technologies, Local Dimming technology controls the brightness of multiple LED lights in the backlight module and dynamically adjusts according to the brightness changes of the image content to improve contrast and reduce power consumption. However, when processing fast-moving scenes, such as a meteor passing quickly in the dark, due to the limited response speed of the backlight lamp beads, there is often a delay between the moving object and the brightness changes of the backlight area, resulting in a tailing phenomenon in the picture, affecting the clarity and smoothness of viewing;

[0006] (2) In order to improve the tailing phenomenon, when adjusting the brightness, the problem of grayscale loss is often encountered, which affects the layering and detail presentation of the image. The traditional global backlight adjustment method cannot flexibly adjust the backlight brightness according to the content of the picture, resulting in the picture being either too dark and losing the white grayscale, or too bright and losing the black grayscale. Summary of the invention

[0007] 1. Technical issues to be resolved

[0008] In view of the shortcomings of the prior art, the present invention provides a backlight drive control method and system based on the Local Dimming algorithm, which detects regional images containing boundary areas and moving objects, optimizes the control strategy of the highlight area blocks of the current frame and the next frame regional images, adjusts the dark areas and highlight areas in the current frame regional images, realizes rapid response of backlight lamp bead brightness changes, improves picture tailing phenomenon, avoids grayscale loss, and enhances picture contrast and detail expression.

[0009] (II) Technical solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: a backlight drive control method based on Local Dimming algorithm, comprising the following steps:

[0011] Receive video data from a video source, extract continuous frame images, determine the position of the moving object in the current frame image and the next frame image, and the boundary area of ​​the moving object;

[0012] For a regional image containing only a boundary area and a moving object, obtain a highlight region block of the current frame and the next frame regional image, divide the backlight module where the highlight region block of the current frame and the next frame regional image is located into a plurality of independent control partitions, and assign an independent control unit to each control partition;

[0013] Obtain the target brightness value of each control partition of the current frame area image and the next frame area image, calculate the target brightness difference of the same control partition for the current frame area image and the next frame area image, obtain the delayed response time, and send a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time;

[0014] Traverse each pixel in the dark area and highlight area of ​​the current frame area image, obtain the gray value of each pixel, and perform linear transformation on the pixels whose gray value is lower than the dark threshold or higher than the highlight threshold.

[0015] Furthermore, the process of determining the position of the moving object and the boundary area of ​​the moving object includes:

[0016] Grayscale the current frame image, use the edge detection algorithm to extract the feature area from the current frame image, use the optical flow method to calculate the displacement of the feature area between the current frame and the previous frame, and obtain the motion vector;

[0017] A motion threshold is set in advance, and the area whose motion vector exceeds the motion threshold is identified as a motion area, otherwise, it is identified as a static area, and morphological operations are performed on the identified motion area to extract the contour of the moving object and determine the position of the moving object in the current frame image;

[0018] According to the outline of the moving object, an area within a preset distance from the outline of the moving object is used as a boundary area, and the boundary area is located outside the moving object.

[0019] Furthermore, the process of obtaining the highlighted area blocks of the current frame and the next frame area image includes:

[0020] Calculate the global average gray value of all pixel gray values ​​in the regional image, traverse each gray level, and for each gray level, divide the image into two parts: a set of pixels A whose gray value is less than the current gray level and a set of pixels B whose gray value is greater than or equal to the current gray level;

[0021] Calculate the average grayscale value of sets A and B respectively, and calculate the inter-class variance. The inter-class variance is the weighted sum of the squares of the differences between the average grayscale values ​​of sets A and B and the global average grayscale value, and the weight is the ratio of the number of pixels in sets A and B to the total number of pixels in the regional image.

[0022] The gray level with the largest inter-class variance is taken as the global threshold, the offset percentage is set, and the low and high thresholds are calculated. The low threshold = global threshold - (maximum brightness value of the regional image * offset percentage), and the high threshold = global threshold + (maximum brightness value of the regional image * offset percentage).

[0023] Furthermore, the calculation formula of the between-class variance is as follows:

[0024]

[0025] in, Indicates the gray level is T The between-class variance of , They represent the ratio of the number of pixels in sets A and B to the total number of pixels in the regional image, , Represent the average grayscale value of sets A and B respectively, μ Represents the global average gray value.

[0026] Furthermore, traverse each pixel in the boundary area and the moving object, obtain the brightness value of each pixel, and for each pixel, compare the brightness value of the current pixel with the low threshold and the high threshold:

[0027] If the brightness value of the current pixel is less than the low threshold, the pixel belongs to the dark area;

[0028] If the brightness value of the current pixel is greater than the high threshold, the pixel belongs to the highlight area;

[0029] Otherwise, the pixel belongs to the transition area;

[0030] Adjacent pixels belonging to the highlight area are connected into a continuous area to form a highlight area block.

[0031] Furthermore, for each control partition, all pixels inside the current control partition are traversed, the brightness values ​​of the pixels in the highlight area are counted, and the average brightness value of the pixels in the highlight area is calculated, and the average brightness value is used as the target brightness value of the current control partition.

[0032] Furthermore, according to the brightness change of the lamp beads in the backlight module, the delayed response time required from sending the brightness control instruction to the completion of the actual brightness change is determined: delayed response time = actual brightness change time - brightness control instruction sending time.

[0033] Furthermore, a dark threshold is preset, and a linear transformation is performed on pixels whose grayscale values ​​are lower than the dark threshold. The calculation formula is as follows:

[0034]

[0035] in, f(x) represents the linear transformation function, x represents the original grayscale value, a and b Represents the transformation parameter, which is used to adjust the gray value of the pixel. D represents the dark threshold, , .

[0036] Furthermore, a highlight threshold is pre-set, and a linear transformation is performed on pixels whose grayscale values ​​are higher than the highlight threshold. The calculation formula is as follows:

[0037]

[0038] in, f(x) represents the linear transformation function, x represents the original grayscale value, c and d Represents the transformation parameter, which is used to adjust the gray value of the pixel. Htrepresents the bright threshold, , .

[0039] A backlight drive control system based on Local Dimming algorithm, comprising:

[0040] A motion detection module receives video data from a video source, extracts consecutive frame images, determines the position of a moving object in a current frame image and a next frame image, and a boundary area of ​​the moving object;

[0041] A control partition module, for a region image containing only a boundary region and a moving object, obtains a highlight region block of the region image of the current frame and the next frame, divides the backlight module where the highlight region block of the region image of the current frame and the next frame is located into a plurality of independent control partitions, and allocates an independent control unit to each control partition;

[0042] The brightness control module obtains the target brightness value of each control partition of the current frame area image and the next frame area image, calculates the target brightness difference of the same control partition for the current frame area image and the next frame area image, obtains the delayed response time, and sends a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time;

[0043] The grayscale adjustment module traverses each pixel in the dark area and the highlight area in the current frame area image, obtains the grayscale value of each pixel, and performs linear transformation on the pixel whose grayscale value is lower than the dark threshold or higher than the highlight threshold.

[0044] (III) Beneficial effects

[0045] The present invention provides a backlight drive control method and system based on Local Dimming algorithm, which has the following beneficial effects:

[0046] (1) Through grayscale conversion, edge detection, optical flow method to calculate motion vectors and morphological operations, the moving objects in the image can be accurately identified and their contours can be extracted. By determining the boundary area of ​​the moving object and obtaining its brightness data, the brightness change of the backlight module can be controlled more accurately.

[0047] (2) Since the highlight area blocks are controlled independently, they can respond more quickly to changes in the brightness of these areas. Especially when processing fast-moving scenes, by adjusting the position of the moving object in the next frame of the image and pre-adjusting the backlight brightness, the delay between the moving object and the brightness change of the backlight area caused by the limited response speed of the backlight bead brightness change can be significantly reduced, thereby effectively eliminating the picture tailing phenomenon and improving viewing clarity and smoothness.

[0048] (3) By calculating and sending brightness control instructions in advance, the response time required for backlight lamp brightness changes is effectively reduced. This predictive control strategy enables the backlight module to adapt to changes in image brightness more quickly, especially when processing fast-motion scenes, significantly reducing the delay between moving objects and changes in backlight brightness.

[0049] (4) By traversing each pixel in the dark area of ​​the current frame area image and performing linear transformation on the pixels whose grayscale values ​​are lower than the dark threshold, the grayscale level in the dark area can be effectively increased, and more detail information in the dark area can be retained, avoiding loss or blurring of details in dark scenes, thereby improving the layering and clarity of the overall picture; in the highlight area, by traversing each pixel and performing linear transformation on the pixels whose grayscale values ​​are higher than the highlight threshold, the grayscale level in the highlight area can be optimized, ensuring that there is a clear distinction between the brightest grayscale levels in the highlight area, avoiding over-fusion, and improving the contrast and color expression of the picture. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 Schematic diagram of a backlight driving control method based on Local Dimming algorithm of the present invention;

[0051] Figure 2 It is a schematic diagram of a backlight driving control system based on the Local Dimming algorithm of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] See also Figure 1 The present invention provides a backlight driving control method based on Local Dimming algorithm, comprising the following steps:

[0054] Step 1: Receive video data from a video source, extract continuous frame images, determine the position of the moving object in the current frame image and the next frame image, and the boundary area of ​​the moving object;

[0055] The step 1 includes the following contents:

[0056] Step 101: receiving video data from a video source, extracting continuous frame images, graying the current frame image, extracting a feature region from the current frame image using an edge detection algorithm, and calculating the displacement of the feature region between the current frame and the previous frame using an optical flow method to obtain a motion vector;

[0057] Use a video decoder to decode the video data stream into a continuous frame image sequence, and grayscale the current frame image, that is, convert the color image into a grayscale image to reduce the amount of data to be processed while retaining enough image information for subsequent processing. Common methods for grayscale conversion include weighted average method or other algorithms, such as the conversion formula from RGB to grayscale: Gray=0.299*R+0.587*G+0.114*B;

[0058] Use edge detection algorithms (such as Canny edge detector, Sobel operator, etc.) on grayscale images. Edge detection algorithms are used to identify edge information in images. The purpose of edge detection is to find areas in the image where brightness changes dramatically. These areas are often the boundaries of objects.

[0059] For example, the Sobel operator is a gradient-based algorithm that calculates the horizontal and vertical gradient values ​​of an image and combines them to obtain edge strength. It detects edges by using the phenomenon that the weighted difference in grayscale between the upper and lower and left and right neighboring points of a pixel reaches an extreme value at the edge.

[0060] Use optical flow methods (such as the Lucas-Kanade method) to calculate the displacement of the feature area between the current frame and the previous frame. The optical flow method is a motion estimation method based on image processing. It infers the motion of an object by analyzing the changes in pixel values ​​in consecutive frame images. The optical flow method estimates motion based on the temporal changes and spatial proximity of pixels or feature points, thereby obtaining the motion vector of each feature point.

[0061] Step 102: pre-set a motion threshold, identify the area where the motion vector exceeds the motion threshold as a motion area, otherwise, identify it as a static area, perform morphological operations on the identified motion area, extract the contour of the moving object, determine the position of the moving object in the current frame image, and similarly obtain the position of the moving object in the next frame image;

[0062] According to the requirements of the application scenario and experimental results, a reasonable motion threshold is pre-set. The motion threshold is used to distinguish between moving areas and static areas. It is usually set based on the modulus of the motion vector (i.e., the displacement size);

[0063] Morphological operation is an important technology in the field of image processing, including dilation, erosion, opening and closing operations. The application of morphological operation in image processing includes but is not limited to: noise elimination: removing small noise points in the image through operations such as erosion and opening operations; boundary extraction: extracting boundary information in the image using operations such as morphological gradient; area filling: filling small holes or cracks in the image through operations such as closing operations; connected component extraction: extracting connected areas in the image using morphological operations; image segmentation: combining morphological operations with other image processing techniques to achieve accurate image segmentation;

[0064] Step 103: according to the outline of the moving object, a region within a preset distance from the outline of the moving object is taken as a boundary region, and the boundary region is located outside the moving object;

[0065] It should be noted that the setting of the preset distance depends on the width or pixel range of the smear effect. Generally speaking, the pixel range ranges from a few pixels to dozens of pixels. For example, on a display device with a high resolution and a high refresh rate, the smear phenomenon may be relatively mild and the affected range may be relatively small due to the denser pixels and faster update speed. On the contrary, on a device with a low resolution and a low refresh rate, the smear phenomenon may be more obvious and the affected range may be larger.

[0066] When using, combine the contents of step 101 to step 103:

[0067] Through steps such as grayscale conversion, edge detection, optical flow method to calculate motion vectors, and morphological operations, the moving objects in the image can be accurately identified and their contours can be extracted. By determining the boundary area of ​​the moving object and obtaining its brightness data, the brightness change of the backlight module can be more accurately controlled.

[0068] Step 2: For the regional image containing only the boundary area and the moving object, obtain the highlight area blocks of the current frame and the next frame regional image, divide the backlight module where the highlight area blocks of the current frame and the next frame regional image are located into several independent control partitions, and assign an independent control unit to each control partition;

[0069] The step 2 includes the following contents:

[0070] Step 201: for a region image that only contains a boundary region and a moving object, a global grayscale histogram of the region image is calculated, wherein the horizontal and vertical axes of the histogram represent grayscale levels (for an 8-bit image, usually 0-255), and the vertical axis represents the number of pixels that appear in the image at each grayscale level;

[0071] Step 202: Calculate the global average grayscale value of all pixel grayscale values ​​in the regional image, traverse each grayscale level from 0 to 255, and for each grayscale level, divide the image into two parts: a pixel set A whose grayscale value is less than the current grayscale level and a pixel set B whose grayscale value is greater than or equal to the current grayscale level. The calculation formula of the global average grayscale value is as follows:

[0072]

[0073] in, μ represents the global average gray value, S Indicates the total number of pixels in the region image, L Indicates the number of gray levels (for 8-bit images, the number of gray levels is 256), S[T] Indicates grayscale T The number of pixels;

[0074] Step 203: Calculate the average grayscale values ​​of sets A and B respectively, and calculate the inter-class variance. The inter-class variance is the weighted sum of the squares of the differences between the average grayscale values ​​of sets A and B and the global average grayscale value. The weight is the ratio of the number of pixels in sets A and B to the total number of pixels in the regional image. The calculation formula of the inter-class variance is as follows:

[0075]

[0076] in, Indicates the gray level is T The between-class variance of , They represent the ratio of the number of pixels in sets A and B to the total number of pixels in the regional image, , Represent the average grayscale value of sets A and B respectively, μ Represents the global average gray value;

[0077] Step 204: taking the gray level with the largest inter-class variance as the global threshold, selecting 5% as the offset percentage, and calculating the low and high thresholds, where the low threshold = global threshold - (maximum brightness value of the regional image * offset percentage), and the high threshold = global threshold + (maximum brightness value of the regional image * offset percentage);

[0078] Step 205: traverse each pixel in the boundary area and the moving object, obtain the brightness value of each pixel, and for each pixel, compare the brightness value of the current pixel with the low threshold and the high threshold:

[0079] If the brightness value of the current pixel is less than the low threshold, the pixel belongs to the dark area;

[0080] If the brightness value of the current pixel is greater than the high threshold, the pixel belongs to the highlight area;

[0081] Otherwise, the pixel belongs to the transition area;

[0082] Step 206: Connect adjacent pixels belonging to the highlight area into a continuous area to form a highlight area block, obtain the highlight area blocks of the current frame and the next frame area image, divide the backlight module where the highlight area blocks of the current frame and the next frame area image are located into a plurality of independent control partitions, and allocate an independent control unit (such as an LED driver, a PWM controller, etc.) to each partition so as to adjust the brightness and switch state of each partition;

[0083] It should be noted that when calculating the low and high thresholds, a global threshold and offset percentage are introduced. The global threshold is obtained by maximizing the inter-class variance, which helps to ensure that the threshold setting can adapt to images of different brightness and contrast. The introduction of the offset percentage further refines the division of highlights and dark areas, making the threshold adjustment more flexible and dynamic, and able to adapt to changes in different brightness in the image.

[0084] When used, combine the contents of step 201 to step 206:

[0085] Since the highlight area blocks are controlled independently, they can respond more quickly to changes in the brightness of these areas. Especially when processing fast-motion scenes, by adjusting the position of the moving object in the next frame of the image and pre-adjusting the backlight brightness, the delay between the moving object and the brightness changes of the backlight area caused by the limited response speed of the backlight beads can be significantly reduced, thereby effectively eliminating the picture tailing phenomenon and improving viewing clarity and smoothness.

[0086] Step 3: Obtain the target brightness value of each control partition of the current frame area image and the next frame area image, calculate the target brightness difference of the same control partition for the current frame area image and the next frame area image, obtain the delayed response time, and send a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time;

[0087] The step three includes the following contents:

[0088] Step 301: For each control partition, traverse all pixels in the current control partition, count the brightness values ​​of the pixels in the highlight area, and calculate the average brightness value of the pixels in the highlight area. The average brightness value is used as the target brightness value of the current control partition. The calculation formula is as follows:

[0089]

[0090] in, represents the average brightness value of the i-th control partition, P(i,j)represents the brightness of the jth pixel in the highlight area and transition area of ​​the i-th control partition, and N represents the number of pixels in the highlight area and transition area of ​​the control partition;

[0091] Step 302: Obtain the target brightness value of each control partition of the current frame region image and the next frame region image, and calculate the target brightness difference of the same control partition for the current frame region image and the next frame region image: target brightness difference = target brightness value of the control partition of the next frame region image - target brightness value of the control partition of the current frame region image;

[0092] Step 303: according to the brightness change of the lamp beads in the backlight module, determine the delayed response time required from sending the brightness control instruction to the completion of the actual brightness change: delayed response time = actual brightness change time - brightness control instruction sending time;

[0093] Step 304: Send a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time; for example, when the delayed response time is 10 milliseconds (ms) and the display time of the current frame is 33.33ms, send a brightness control instruction to the control unit of the corresponding control partition 10ms before the current frame starts to be displayed, and the brightness adjustment value is the target brightness difference;

[0094] When used, combine the contents of step 301 to step 304:

[0095] By calculating and sending brightness control instructions in advance, the response time required for backlight lamp brightness changes is effectively reduced. This predictive control strategy enables the backlight module to adapt to changes in image brightness more quickly, especially when dealing with fast-moving scenes, significantly reducing the delay between moving objects and changes in backlight brightness.

[0096] Step 4: Traverse each pixel in the dark area and highlight area of ​​the current frame area image, obtain the grayscale value of each pixel, and perform linear transformation on the pixels whose grayscale value is lower than the dark threshold or higher than the highlight threshold.

[0097] The step 4 includes the following contents:

[0098] Step 401: traverse each pixel in the dark area of ​​the current frame area image, obtain the gray value of each pixel, pre-set the dark threshold, perform linear transformation on the pixels with gray values ​​lower than the dark threshold, increase the gray level, and thus retain more details. The calculation formula is as follows:

[0099]

[0100] in, f(x) represents the linear transformation function, x represents the original grayscale value,a and b Represents the transformation parameter, which is used to adjust the gray value of the pixel. D represents the dark threshold, , ;

[0101] Step 402: traverse each pixel in the highlight area of ​​the current frame area image, obtain the grayscale value of each pixel, pre-set the highlight threshold, perform linear transformation on the pixels with grayscale values ​​higher than the highlight threshold, and optimize the grayscale levels of the highlight area to ensure that there is a clear distinction between the brightest grayscale levels without excessive fusion. The calculation formula is as follows:

[0102]

[0103] in, f(x) represents the linear transformation function, x represents the original grayscale value, c and d Represents the transformation parameter, which is used to adjust the gray value of the pixel. Ht represents the bright threshold, , ;

[0104] It should be noted that the dark threshold is used to distinguish which pixels are too dark and need to be processed. For example, the dark threshold can be set to a lower grayscale value, such as 10. The highlight threshold is used to distinguish which pixels are too bright and need to be processed. For example, the highlight threshold can be set to a higher grayscale value, such as 240.

[0105] Transformation parameters a and b are set based on specific needs and scenarios. Usually, the value of a should be greater than 1 to increase the grayscale value and improve the brightness, and the value of b can be a constant to improve the grayscale level as a whole. Similarly, transformation parameters c and d are set based on specific needs and scenarios. Usually, the value of c should be less than 1 to reduce the grayscale value and reduce the brightness, and the value of d can be a negative number to reduce the grayscale level as a whole. However, it should be noted that the grayscale value after transformation should still remain within the valid range (0 to 255).

[0106] When used, combine the contents of step 401 to step 402:

[0107] By traversing each pixel in the dark area of ​​the current frame area image and performing linear transformation on the pixels whose grayscale values ​​are lower than the dark threshold, the grayscale level of the dark area can be effectively increased, more detail information in the dark area can be retained, and the loss or blurring of details in dark scenes can be avoided, thus improving the layering and clarity of the overall picture.

[0108] In the highlight area, by traversing each pixel and performing linear transformation on the pixels whose grayscale values ​​are higher than the highlight threshold, the grayscale levels in the highlight area can be optimized, ensuring that there is a clear distinction between the brightest grayscale levels in the highlight area, avoiding over-fusion, and improving the contrast and color expression of the picture.

[0109] See also Figure 2 The present invention also provides a backlight driving control system based on the Local Dimming algorithm, comprising: a motion detection module, a control partition module, a brightness control module and a grayscale adjustment module; wherein,

[0110] A motion detection module receives video data from a video source, extracts consecutive frame images, determines the position of a moving object in a current frame image and a next frame image, and a boundary area of ​​the moving object;

[0111] A control partition module, for a region image containing only a boundary region and a moving object, obtains a highlight region block of the region image of the current frame and the next frame, divides the backlight module where the highlight region block of the region image of the current frame and the next frame is located into a plurality of independent control partitions, and allocates an independent control unit to each control partition;

[0112] The brightness control module obtains the target brightness value of each control partition of the current frame area image and the next frame area image, calculates the target brightness difference of the same control partition for the current frame area image and the next frame area image, obtains the delayed response time, and sends a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time;

[0113] The grayscale adjustment module traverses each pixel in the dark area and the highlight area in the current frame area image, obtains the grayscale value of each pixel, and performs linear transformation on the pixel whose grayscale value is lower than the dark threshold or higher than the highlight threshold.

[0114] In the application, the several formulas involved are all calculated by removing dimensions and taking their numerical values. The formula is a formula of the most recent real situation obtained by collecting a large amount of data and performing software simulation. The coefficients in the formula are set by technicians in this field according to actual conditions.

[0115] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in combination with electronic hardware, computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0116] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A backlight driving control method based on Local Dimming algorithm, characterized in that: The following steps are involved: Receive video data from a video source, extract continuous frame images, determine the position of the moving object in the current frame image and the next frame image, and the boundary area of ​​the moving object; For a regional image containing only a boundary area and a moving object, obtain a highlight region block of the current frame and the next frame regional image, divide the backlight module where the highlight region block of the current frame and the next frame regional image is located into a plurality of independent control partitions, and assign an independent control unit to each control partition; Obtain the target brightness value of each control partition of the current frame area image and the next frame area image, calculate the target brightness difference of the same control partition for the current frame area image and the next frame area image, obtain the delayed response time, and send a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time; Traverse each pixel in the dark area and highlight area of ​​the current frame area image, obtain the gray value of each pixel, and perform linear transformation on the pixels whose gray value is lower than the dark threshold or higher than the highlight threshold, including: The dark threshold is set in advance, and the pixels with grayscale values ​​lower than the dark threshold are linearly transformed. The calculation formula is as follows: in, f(x) represents the linear transformation function, x represents the original grayscale value, a and b Represents the transformation parameter, which is used to adjust the gray value of the pixel. D represents the dark threshold, , ; The highlight threshold is set in advance, and the pixels with grayscale values ​​higher than the highlight threshold are linearly transformed. The calculation formula is as follows: in, f(x) represents the linear transformation function, x represents the original grayscale value, c and d Represents the transformation parameter, which is used to adjust the gray value of the pixel. Ht represents the bright threshold, , .

2. The backlight driving control method based on Local Dimming algorithm according to claim 1, characterized in that: The process of determining the position of a moving object and the boundary area of ​​the moving object includes: Grayscale the current frame image, use the edge detection algorithm to extract the feature area from the current frame image, use the optical flow method to calculate the displacement of the feature area between the current frame and the previous frame, and obtain the motion vector; A motion threshold is set in advance, and the area whose motion vector exceeds the motion threshold is identified as a motion area, otherwise, it is identified as a static area, and morphological operations are performed on the identified motion area to extract the contour of the moving object and determine the position of the moving object in the current frame image; According to the outline of the moving object, an area within a preset distance from the outline of the moving object is used as a boundary area, and the boundary area is located outside the moving object.

3. The backlight driving control method based on Local Dimming algorithm according to claim 1, characterized in that: The process of obtaining the highlighted area blocks of the current frame and the next frame area image includes: Calculate the global average gray value of all pixel gray values ​​in the regional image, traverse each gray level, and for each gray level, divide the image into two parts: a set of pixels A whose gray value is less than the current gray level and a set of pixels B whose gray value is greater than or equal to the current gray level; Calculate the average grayscale value of sets A and B respectively, and calculate the inter-class variance. The inter-class variance is the weighted sum of the squares of the differences between the average grayscale values ​​of sets A and B and the global average grayscale value, and the weight is the ratio of the number of pixels in sets A and B to the total number of pixels in the regional image. The gray level with the largest inter-class variance is taken as the global threshold, the offset percentage is set, and the low threshold and high threshold are calculated. The low threshold = global threshold - (regional image maximum brightness value offset percentage), and the high threshold = global threshold + (regional image maximum brightness value * offset percentage).

4. The backlight driving control method based on Local Dimming algorithm according to claim 3, characterized in that: The calculation formula for between-class variance is as follows: in, Indicates the gray level is T The between-class variance of , They represent the ratio of the number of pixels in sets A and B to the total number of pixels in the regional image, , Represent the average grayscale value of sets A and B respectively, μ Represents the global average gray value.

5. The backlight driving control method based on Local Dimming algorithm according to claim 3, characterized in that: Traverse each pixel in the boundary area and the moving object, obtain the brightness value of each pixel, and for each pixel, compare the brightness value of the current pixel with the low threshold and the high threshold: If the brightness value of the current pixel is less than the low threshold, the pixel belongs to the dark area; If the brightness value of the current pixel is greater than the high threshold, the pixel belongs to the highlight area; Otherwise, the pixel belongs to the transition area; Adjacent pixels belonging to the highlight area are connected into a continuous area to form a highlight area block.

6. The backlight driving control method based on Local Dimming algorithm according to claim 1, characterized in that: For each control partition, traverse all pixels inside the current control partition, count the brightness values ​​of the pixels in the highlight area, and calculate the average brightness value of the pixels in the highlight area, and use the average brightness value as the target brightness value of the current control partition.

7. The backlight driving control method based on Local Dimming algorithm according to claim 1, characterized in that: According to the brightness change of the lamp beads in the backlight module, determine the delayed response time required from sending the brightness control command to the actual brightness change: delayed response time = actual brightness change time - brightness control command sending time.

8. A backlight drive control system based on Local Dimming algorithm, used to implement the method according to any one of claims 1 to 7, characterized in that: include: A motion detection module receives video data from a video source, extracts consecutive frame images, determines the position of a moving object in a current frame image and a next frame image, and a boundary area of ​​the moving object; A control partition module, for a region image containing only a boundary region and a moving object, obtains a highlight region block of the region image of the current frame and the next frame, divides the backlight module where the highlight region block of the region image of the current frame and the next frame is located into a plurality of independent control partitions, and allocates an independent control unit to each control partition; The brightness control module obtains the target brightness value of each control partition of the current frame area image and the next frame area image, calculates the target brightness difference of the same control partition for the current frame area image and the next frame area image, obtains the delayed response time, and sends a brightness control instruction to the control unit of the corresponding control partition in advance according to the target brightness difference and the delayed response time; The grayscale adjustment module traverses each pixel in the dark area and the highlight area of ​​the current frame area image, obtains the grayscale value of each pixel, and performs linear transformation on the pixel whose grayscale value is lower than the dark threshold or higher than the highlight threshold, including: The dark threshold is set in advance, and the pixels with grayscale values ​​lower than the dark threshold are linearly transformed. The calculation formula is as follows: in, f(x) represents the linear transformation function, x represents the original grayscale value, a and b Represents the transformation parameter, which is used to adjust the gray value of the pixel. D represents the dark threshold, , ; The highlight threshold is set in advance, and the pixels with grayscale values ​​higher than the highlight threshold are linearly transformed. The calculation formula is as follows: in, f(x) represents the linear transformation function, x represents the original grayscale value, c and d Represents the transformation parameter, which is used to adjust the gray value of the pixel. Ht represents the bright threshold, , .

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