Screen brightness adjusting method

Abstract

The invention discloses a screen brightness adjusting method, the adjusting method is applied to a screen of an LED layer, the LED layer is divided into a plurality of LED blocks, and the adjusting method comprises the following steps: S1, obtaining hardware configuration parameters of the screen; s2, based on the maximum power value and the total number of the blocks, calculating the theoretical maximum number of the blocks which can be driven by the LED layer under the constraint of the maximum power; s3, current ambient light parameters are collected in real time; s4, dynamically generating a target window value through a pre-trained brightness compensation model according to the ambient light parameters and the theoretical maximum block number; and S5, generating a corresponding driving control parameter according to the target window value, and controlling a screen to display. By combining hardware power constraint modeling, ambient light intelligent perception, display content self-adaptive identification and closed-loop power consumption control, the problems that in the prior art, complex ambient light adaptability is poor, screen hardware specification compatibility is insufficient, and over-drive and non-over-drive screen management is not unified are effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of screen display control, in particular to a screen brightness adjusting method. BACKGROUND

[0002] At present, the screens of most electronic devices adopt LED backlight structure, and the LED layer thereof is usually divided into multiple independent LED blocks, each of which can be driven and controlled individually to realize local dimming and improve display contrast and energy efficiency. In the prior art, screen brightness adjustment is mostly dependent on the illumination information obtained by an ambient light sensor, and the overall backlight brightness or the partition driving strategy is adjusted to adapt to the ambient light changes. However, such a method often lacks sufficient adaptability when dealing with complex ambient light conditions, such as color temperature changes and different display content types, and it is difficult to achieve optimal brightness and color performance under the maximum power constraint of the screen.

[0003] In addition, the existing brightness adjustment scheme usually does not fully consider the differences in screen hardware specifications, such as different sizes, resolutions and power characteristics, which have significant differences in driving strategies. In particular, for screens that support overdrive functions, they can drive LED blocks at a high current in a short time to achieve higher brightness and contrast, but also bring challenges to power consumption control and heat management. Non-overdrive screens are limited by driving capability and are difficult to provide sufficient visual compensation under high ambient light. SUMMARY

[0004] The present application aims to provide a screen brightness adjusting method to solve the problems raised in the background.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solution: a screen brightness adjusting method applied to a screen with an LED layer, the LED layer being divided into multiple LED blocks, the adjusting method comprising the following steps:

[0006] S1: obtaining hardware configuration parameters of the screen, the hardware configuration parameters including a maximum power value of the screen, a total number of blocks of the LED blocks, and physical size information of each LED block;

[0007] S2: based on the maximum power value and the total number of blocks, calculating a theoretical maximum number of blocks that the LED layer can be driven under the maximum power constraint;

[0008] S3: real-time collecting current ambient light parameters, the ambient light parameters including ambient light illumination and color temperature;

[0009] S4: according to the ambient light parameters and the theoretical maximum number of blocks, dynamically generating a target window value through a pre-trained brightness compensation model, the target window value being used to indicate the range of LED blocks required to be driven to offset the influence of ambient light and achieve target display brightness;

[0010] S5: generating a corresponding driving control parameter according to the target window value, and controlling the screen to display.

[0011] Preferably, the screen brightness adjustment method applying the target window value dynamically generated by the pre-trained brightness compensation model comprises the following steps:

[0012] S11: inputting the ambient light intensity, the ambient light color temperature, and the theoretical maximum number of blocks as input feature vectors into the trained neural network model;

[0013] S12: obtaining the output of the neural network model, the output including the brightness compensation coefficient and the color temperature compensation coefficient required to reach the preset brightness target;

[0014] S13: correcting the theoretical maximum number of blocks according to the brightness compensation coefficient and the color temperature compensation coefficient, and calculating the final target window value.

[0015] Preferably, the training method of the neural network model comprises the following steps:

[0016] S21: driving the screen to display at a plurality of different test window values under a plurality of known ambient light conditions;

[0017] S22: using a luminometer to collect actual measured brightness values and color temperature values of the screen under each test window value and ambient light condition;

[0018] S23: performing supervised learning training on the neural network by taking the ambient light condition and the test window value as input and taking the corresponding measured brightness value and color temperature value as expected output until the output error is lower than a preset threshold.

[0019] Preferably, the method between calculating the theoretical maximum number of blocks and generating the target window value comprises the following steps:

[0020] S31: identifying the content type of the current screen display content;

[0021] S32: selecting a target strategy from a plurality of preset brightness adjustment strategies according to the content type;

[0022] S33: generating the target window value according to the ambient light parameter, the theoretical maximum number of blocks, and the target strategy.

[0023] Preferably, the identification of the content type of the current screen display content comprises scene analysis on the current frame or a plurality of continuous frame image data, if text or graphical UI elements are identified as the main part of the image, the content type is determined as "text mode"; if natural scenes or video content are identified as the main part of the image, the content type is determined as "media mode".

[0024] Preferably, when the target strategy is "text mode", the driving range corresponding to the generated target window value is concentrated in the central area of ​​the screen, and the driving control parameters are configured to improve display contrast.

[0025] When the target strategy is "media mode", the driving range corresponding to the generated target window value covers the entire screen area, and the driving control parameters are configured to improve color saturation.

[0026] Preferably, obtaining the hardware configuration parameters of the screen includes reading the pre-programmed hardware configuration information from the memory built into the screen driver chip; controlling the screen to display a full white image; measuring the voltage and current values ​​of the LED blocks; and calculating the maximum power value.

[0027] Preferably, the method for generating corresponding drive control parameters based on the target window value includes the following steps:

[0028] S41: Determine the set of target LED blocks to be driven based on the target window value;

[0029] S42: For each block in the target LED block set, assign a different pulse width modulation duty cycle according to whether the block is located in the center region or the edge region of the set;

[0030] Specifically, a first pulse width modulation duty cycle is allocated to the LED blocks in the central region, and a second pulse width modulation duty cycle is allocated to the LED blocks in the edge region. The first pulse width modulation duty cycle is greater than the second pulse width modulation duty cycle.

[0031] Preferably, the method further includes monitoring the total operating current of the LED layer in real time during the driving process; if the total operating current exceeds the current threshold corresponding to the maximum power value, the pulse width modulation duty cycle of the LED block in the edge region is dynamically reduced so that the total power does not exceed the maximum power value.

[0032] Preferably, the adjustment method is performed by an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor is configured to execute the computer program to implement the screen brightness adjustment method steps.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1.The present application converts the abstract power constraint into the quantifiable upper limit of the spatial driving range by obtaining the maximum power value of the screen, the total number of LED blocks, and the hardware configuration parameters such as physical size, and calculating the theoretical maximum block number based on this, which is compatible with overdriven and non-overdriven screens, allowing overdriven screens to exert the performance advantage of instantaneous high brightness within the safe range, and providing a driving efficiency optimization framework for non-overdriven screens, ensuring that the power consumption does not exceed the rated value under any driving state, solving the problem of inaccurate power consumption control caused by screen specification differences.

[0035] 2.The present application synchronously collects ambient light intensity and color temperature parameters, overcomes the defect of traditional schemes that only consider brightness and ignore the influence of color temperature, outputs brightness compensation coefficients and color temperature compensation coefficients through a neural network model, and cooperatively corrects the driving parameters to ensure the color authenticity and visual consistency of the displayed content in different color temperature environments.

[0036] 3.The present application allocates different pulse width modulation duty cycles according to the position of the LED block in the target window, ensures the visual focus to be clear in the center area with high brightness, reduces the overall power consumption in the edge area with low brightness, and realizes intelligent allocation of visual resources under limited power budget. BRIEF DESCRIPTION OF DRAWINGS

[0037] Fig. 1 The flowchart of the screen brightness adjustment method of the present application.

[0038] Fig. 2 The flowchart of the neural network training of the present application. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0040] Please refer to Figs. 1-2 The present application provides a technical solution: the embodiments of the present application provide a screen brightness adjustment method, the screen includes an LED layer, the LED layer is divided into a plurality of LED blocks, and the adjustment method includes the following steps:

[0041] S1: first, obtain the hardware configuration parameters of the screen, the hardware configuration parameters include the maximum power value of the screen, the total number of blocks of the LED blocks, and the physical size information of each LED block.

[0042] Obtaining the hardware configuration parameters of the screen, which comprises reading the pre-burned hardware configuration information from the memory built-in the screen driving chip, and controlling the screen to display a full white picture, and calculating the maximum power value of the screen by measuring the voltage and current values of each LED block.

[0043] Specifically, in step S1, the maximum power value is calculated by reading the pre-burned hardware configuration information from the memory built-in the screen driving chip, and controlling the screen to display a full white picture to measure the block voltage and current. This acquisition method takes into account the preset parameters and actual measurement verification, which is beneficial to the accuracy and reliability of the power reference, and provides a reliable basis for subsequent power allocation.

[0044] S2: Based on the maximum power value and the total number of blocks, the theoretical maximum number of blocks that can be driven by the LED layer under the maximum power constraint is calculated.

[0045] In step S2, the calculation of the theoretical maximum number of blocks converts the system total power constraint into the upper limit of the number of drivable blocks, establishing a mapping model from the power domain to the spatial driving range, and providing a unified driving capability quantization index for screens of different sizes and resolutions.

[0046] S3: Real-time acquisition of current ambient light parameters, including ambient light intensity and color temperature.

[0047] In step S3, the synchronous acquisition of ambient light intensity and color temperature overcomes the limitations of traditional methods that only consider brightness and ignore the influence of color temperature, providing an input basis for subsequent brightness and color temperature compensation.

[0048] S4: According to the ambient light parameters and the theoretical maximum number of blocks, a pre-trained brightness compensation model is used to dynamically generate a target window value, which is used to indicate the range of LED blocks that need to be driven to offset the influence of ambient light and achieve the target display brightness.

[0049] Next, according to the ambient light parameters, the theoretical maximum number of blocks, and the selected target strategy, a pre-trained brightness compensation model is used to dynamically generate the final target window value. This process specifically includes:

[0050] S11: The ambient light intensity, ambient light color temperature, and theoretical maximum number of blocks are input as input feature vectors into a trained neural network model.

[0051] S12: Obtain the output of the neural network model, which includes the brightness compensation coefficient and the color temperature compensation coefficient required to achieve the preset brightness target.

[0052] S13: Modify the theoretical maximum number of blocks according to the brightness compensation coefficient and the color temperature compensation coefficient, and calculate the final target window value.

[0053] The neural network model is trained by the following method:

[0054] S21: driving the screen to display at a plurality of different test window values under a plurality of known ambient light conditions;

[0055] S22: using a luminometer to collect actual measured brightness values and color temperature values of the screen under each test window value and ambient light condition;

[0056] S23: performing supervised learning training on the neural network with the ambient light condition and the test window value as input and the corresponding measured brightness value and color temperature value as expected output until the output error is lower than a preset threshold.

[0057] After the theoretical maximum block number is calculated, the method for generating the target window value includes the following steps:

[0058] S31: identifying the content type of the current screen display content;

[0059] S32: selecting a target strategy from a plurality of preset brightness adjustment strategies according to the content type;

[0060] S33: generating a target window value according to the ambient light parameter, the theoretical maximum block number and the target strategy.

[0061] In step S4, the pre-trained brightness compensation model takes the ambient light intensity, color temperature and theoretical maximum block number as input, outputs brightness compensation coefficients and color temperature compensation coefficients through the neural network, and corrects the theoretical maximum block number to generate the final target window value. The model is trained by a large amount of test data under known ambient light conditions, and can accurately predict the best driving range and color compensation required to offset the ambient light interference, so that the display content can be clear and the color can be real under different ambient light conditions.

[0062] S5: finally generating corresponding driving control parameters according to the target window value to control the screen to display.

[0063] The above scheme introduces the theoretical maximum block number as a system-level power constraint reference, and dynamically calculates the LED driving range that meets the hardware power limit and is self-adaptive to environmental light changes and display content requirements by combining real-time environmental light parameters and artificial intelligence models. This design effectively overcomes the problems of insufficient brightness and color performance and inaccurate power control caused by screen specification differences such as overdrive and non-overdrive screens, complex changes in ambient light and different content types in the prior art, and significantly improves the consistency and adaptability of visual experience under the premise of ensuring that the screen does not exceed the maximum power.

[0064] Furthermore, to improve content adaptability, the type of currently displayed content is identified before generating the target window value. If text or graphical UI is identified as the main content, "text mode" is selected. When the target strategy is "text mode", the driving range corresponding to the generated target window value is concentrated in the central area of ​​the screen, and the driving control parameters are configured to improve display contrast to ensure text readability. If natural scenes or video content are identified as the main content, "media mode" is enabled. When the target strategy is "media mode", the driving range corresponding to the generated target window value covers the entire screen area, and the driving control parameters are configured to improve color saturation to optimize the visual experience. This content awareness mechanism closely integrates the brightness adjustment strategy with the actual content viewed by the user, improving energy efficiency and user experience.

[0065] During the drive control parameter generation stage, the set of LED blocks to be driven is determined based on the target window value. For each block in the target LED block set, a different pulse width modulation duty cycle is assigned according to whether the block is located in the central region or the edge region of the set. Specifically, a first pulse width modulation duty cycle is assigned to LED blocks in the central region, and a second pulse width modulation duty cycle is assigned to LED blocks in the edge region. The first pulse width modulation duty cycle is greater than the second pulse width modulation duty cycle. This gradient driving method effectively controls the overall power consumption while maintaining the brightness of the visual focus area.

[0066] In addition, the total operating current of the LED layer is monitored in real time during the driving process. If it exceeds the threshold corresponding to the maximum power, the PWM duty cycle of the edge area block is dynamically reduced so that the total power of the system never exceeds the maximum allowable value. This closed-loop control mechanism enhances the robustness and safety of the system and prevents overheating or hardware damage caused by overdrive.

[0067] It should be noted that, regardless of whether it is an overdriven or non-overdriven screen, its maximum power value is less than the total power when all LED blocks are working at maximum driving parameters simultaneously. This solution ensures that the overall power consumption of the screen does not exceed the rated maximum power under any driving state by calculating the theoretical maximum number of blocks and the dynamic target window value. This not only ensures hardware safety, but also provides a unified and adaptive management framework for overdriven screens to give full play to their performance advantages and for non-overdriven screens to improve driving efficiency.

[0068] This application provides a screen brightness adjustment method, which is executed by an electronic device. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to execute the computer program to implement the steps of the screen brightness adjustment method.

[0069] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. A screen brightness adjustment method, applied to a screen with an LED layer, wherein the LED layer is divided into multiple LED blocks, characterized in that: The adjustment method includes the following steps: S1: Obtain the screen's hardware configuration parameters, including the screen's maximum power value, the total number of LED blocks, and the physical size information of each LED block; S2: Based on the maximum power value and the total number of blocks, calculate the theoretical maximum number of blocks that the LED layer can be driven under the maximum power constraint; S3: Real-time acquisition of current ambient light parameters, including ambient illuminance and color temperature; S4: Based on the ambient light parameters and the theoretical maximum number of blocks, a target window value is dynamically generated through a pre-trained brightness compensation model. The target window value is used to indicate the range of LED blocks that need to be driven to offset the influence of ambient light and achieve the target display brightness. S5: Generate corresponding drive control parameters based on the target window value, and control the screen to display.

2. The screen brightness adjustment method according to claim 1, characterized in that: The method of dynamically generating target window values ​​using a pre-trained brightness compensation model for screen brightness adjustment includes the following steps: S11: The ambient light intensity, ambient light color temperature, and theoretical maximum number of blocks are used as input feature vectors and input into the trained neural network model. S12: Obtain the output of the neural network model, including the brightness compensation coefficient and color temperature compensation coefficient required to achieve the preset brightness target; S13: Based on the brightness compensation coefficient and color temperature compensation coefficient, the theoretical maximum number of blocks is corrected, and the final target window value is calculated.

3. The screen brightness adjustment method according to claim 2, characterized in that: The training method for the neural network model includes the following steps: S21: Under various known ambient light conditions, drive the screen to display with multiple different test window values; S22: Use a photometer to collect the actual measured brightness and color temperature values ​​of the screen under various test window conditions and ambient light conditions; S23: Using ambient light conditions and test window values ​​as inputs, and the corresponding measured brightness and color temperature values ​​as the desired outputs, supervise the neural network for training until its output error is lower than a preset threshold.

4. The screen brightness adjustment method according to claim 1, characterized in that: The method for calculating the theoretical maximum number of blocks and the target window size includes the following steps: S31: Identify the content type of the content currently displayed on the screen; S32: Select the target strategy from multiple preset brightness adjustment strategies based on the content type; S33: Generate the target window value based on ambient light parameters, the theoretical maximum number of blocks, and the target strategy.

5. A screen brightness adjustment method according to claim 4, characterized in that: The identification of the content type of the currently displayed content includes scene analysis of the current frame or multiple consecutive frames of image data. If the image is identified as mainly composed of text or graphic UI elements, the content type is determined to be "text mode"; if the image is identified as mainly composed of natural scenes or video content, the content type is determined to be "media mode".

6. The screen brightness adjustment method according to claim 5, characterized in that: When the target strategy is "text mode", the driving range corresponding to the generated target window value is concentrated in the central area of ​​the screen, and the driving control parameters are configured to improve display contrast. When the target strategy is "media mode", the driving range corresponding to the generated target window value covers the entire screen area, and the driving control parameters are configured to improve color saturation.

7. The screen brightness adjustment method according to claim 1, characterized in that: The process of obtaining the hardware configuration parameters of the screen includes reading the pre-programmed hardware configuration information from the memory built into the screen driver chip; controlling the screen to display a full white image; measuring the voltage and current values ​​of the LED blocks; and calculating the maximum power value.

8. The screen brightness adjustment method according to claim 1, characterized in that: The method for generating corresponding drive control parameters based on the target window value includes the following steps: S41: Determine the set of target LED blocks to be driven based on the target window value; S42: For each block in the target LED block set, assign a different pulse width modulation duty cycle according to whether the block is located in the center region or the edge region of the set; Specifically, a first pulse width modulation duty cycle is allocated to the LED blocks in the central region, and a second pulse width modulation duty cycle is allocated to the LED blocks in the edge region. The first pulse width modulation duty cycle is greater than the second pulse width modulation duty cycle.

9. A screen brightness adjustment method according to claim 8, characterized in that: The method also includes real-time monitoring of the total operating current of the LED layer during the driving process; if the total operating current exceeds the current threshold corresponding to the maximum power value, the pulse width modulation duty cycle of the LED block in the edge region is dynamically reduced so that the total power does not exceed the maximum power value.

10. A screen brightness adjustment method according to claim 1, characterized in that: The adjustment method is performed by an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor is configured to execute the computer program to implement the screen brightness adjustment method steps as described in any one of claims 1-9.

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