Smart display optimization method, device and equipment of tablet computer and storage medium

Abstract

The application relates to the technical field of display optimization, and provides a smart display optimization method and device for a tablet computer, equipment and a storage medium. When a display environment change signal is detected, a direction light intensity data of each direction is generated by grouping and fusing an original photoelectric signal set according to a direction set, application scene data is obtained by judging an application scene according to the direction light intensity data and application state data through a scene mapping rule, partition target light beam angle data is obtained by calculating a glare intensity gradient of a local display area and calculating an optimized light beam angle according to the running scene data and the direction light intensity data, and a driving voltage signal is generated by modulating a voltage signal for display adjustment according to the partition target light beam angle data. The application can improve the visibility under outdoor and strong light, retain colors and contrast by direction perception light intensity partition fusion, scene perception decision and gradient-based local light beam angle optimization, and realize fine adjustment by phase driving.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of display optimization, in particular to a smart display optimization method, device and equipment of a tablet computer and a storage medium. BACKGROUND

[0002] Phase adjustment in liquid crystal display adjusts the orientation of liquid crystal molecules by changing the phase distribution of the driving voltage signal, thereby realizing fine control of the light beam direction and light field distribution. Traditional liquid crystal display usually relies on global adjustment of brightness or color parameters, while the phase adjustment mechanism can dynamically correct the light exit angle of local areas while maintaining the consistency of the overall display content, so that the display screen can effectively control the glare intensity distribution and realize the optimization of the light beam angle.

[0003] The existing display optimization methods of tablet computers mainly focus on two technical paths: one is global brightness adjustment based on ambient light sensors, that is, automatically increasing the overall brightness of the screen when the external light increases, and vice versa; the second is color and contrast enhancement through software algorithms, such as increasing the contrast curve in high light environment or improving clarity through color mapping in dark light environment. In addition, some devices use polarizing films or surface anti-glare coatings to reduce reflection to improve outdoor readability. These methods can improve visibility to some extent in general scenarios, but their adjustment mechanism often lacks fine control of light directionality and local area differences, so there are still obvious limitations. SUMMARY

[0004] Therefore, the present application provides a smart display optimization method, device and equipment of a tablet computer and a storage medium to solve the problem of excessive dependence on overall brightness or full-screen parameter adjustment, which leads to increased energy consumption and decreased display quality.

[0005] The first aspect of the present application provides a smart display optimization method of a tablet computer, which comprises:

[0006] When a preset display environment change signal is detected, group and fuse the collected original photoelectric signal set according to a preset direction set to generate direction light intensity data of each direction;

[0007] According to the direction light intensity data and the application state data monitored, application scene judgment is performed through a preset scene mapping rule to obtain running scene data;

[0008] According to the running scene data and the direction light intensity data, glare intensity gradient calculation and optimized light beam angle calculation of local display areas are performed to obtain partition target light beam angle data;

[0009] The voltage signal modulation is modulated according to the display adjustment of the partition target beam angle data, to generate a driving voltage signal.

[0010] In an optional implementation, the generating of the directional light intensity data of each direction according to the preset direction set and the grouping and fusion of the collected original photoelectric signal set includes:

[0011] According to the preset direction set, the original photoelectric signals are grouped and processed to obtain signal groups corresponding to each direction;

[0012] The signal groups are subjected to light intensity data conversion and same-group data mean value calculation to generate the ambient light intensity data of each direction;

[0013] The ambient light intensity data of each direction are subjected to time sequence filtering processing to obtain the directional light intensity data of each direction.

[0014] In an optional implementation, the application scene judgment according to the directional light intensity data and the monitored application state data through the preset scene mapping rule to obtain the running scene data includes:

[0015] The application state data are obtained by monitoring the application package name and category information of the currently running foreground application in real time through a preset system interface;

[0016] According to the application state data, the main scene identification is obtained through the preset scene mapping rule for application main scene mapping processing, and the directional light intensity data are subjected to light environment state judgment in different scenes through the scene mapping rule according to the main scene identification to obtain corresponding light environment state data;

[0017] The main scene identification and the light environment state data are combined and encoded through a preset encoding mode to generate the running scene data.

[0018] In an optional implementation, the glare intensity gradient calculation of the local display area and the optimized beam angle calculation according to the running scene data and the directional light intensity data to obtain the partition target beam angle data include:

[0019] According to the running scene data, the corresponding reference beam angle parameter and gradient influence coefficient are obtained through a preset parameter mapping rule;

[0020] The display area is subjected to region segmentation to generate a display partition set according to a preset display partition size, and the light intensity distribution of each display partition of the display partition set is estimated to obtain the light intensity value of the center point of each display partition according to the directional light intensity data;

[0021] calculate a glare intensity gradient of each display partition according to the light intensity value, calculate an optimized target beam angle of each display partition according to the glare intensity gradient, the reference beam angle parameter, and the gradient influence coefficient;

[0022] smoothly filter the optimized target beam angles of all display partitions to obtain partition target beam angle data.

[0023] In an optional implementation, the partition target beam angle data includes the optimized target beam angles of the display partitions, and the voltage signal modulation according to the partition target beam angle data to generate a driving voltage signal includes:

[0024] convert the optimized target beam angles of the display partitions into corresponding liquid crystal deflection angles according to a preset deflection angle mapping rule;

[0025] convert the liquid crystal deflection angles into corresponding driving voltages of the display partitions according to a preset voltage-deflection angle mapping table;

[0026] combine the driving voltages according to the area information of the display partitions to generate a driving voltage signal.

[0027] In an optional implementation, the method further includes:

[0028] collect angle distribution data of actual light beams emitted by the screens of the display partitions by using a fixed-angle photoelectric sensor, and perform standard deviation calculation and full-width-at-half-maximum calculation on the angle distribution data of the display partitions to generate actual beam angles of the display partitions;

[0029] calculate a beam angle error according to the actual beam angles of the display partitions and the corresponding optimized target beam angles, and calculate a shift calibration amount according to a preset gain coefficient and the beam angle error;

[0030] update the voltage-deflection angle mapping table according to the shift calibration amount.

[0031] The second aspect of the application provides a smart display optimization device of a tablet computer, and the device includes:

[0032] a light intensity detection module configured to, when a preset display environment change signal is detected, group and fuse a set of collected original photoelectric signals according to a preset direction set to generate direction light intensity data of each direction;

[0033] a scene mapping module configured to perform application scene judgment according to the direction light intensity data and monitored application state data to obtain running scene data by using a preset scene mapping rule;

[0034] a light beam adjusting module, configured to calculate a glare intensity gradient of a local display area and calculate an optimized light beam angle according to the operation scene data and the directional light intensity data, and obtain partition target light beam angle data;

[0035] a signal modulation module, configured to modulate a voltage signal for display adjustment according to the partition target light beam angle data, and generate a driving voltage signal.

[0036] The third aspect of the present application provides an electronic device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the smart display optimization method of the tablet computer when executing the computer program.

[0037] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the processor implements the steps of the smart display optimization method of the tablet computer when executing the computer program.

[0038] In summary, the present application at least has the following beneficial technical effects:

[0039] 1. By grouping and fusing the original photoelectric signals according to the preset direction, the local light intensity distribution (directional light intensity data) of each direction can be obtained. Based on this and combined with the operation scene judgment, the system can identify the strong reflection / direct light source from a specific direction, and dynamically narrow or adjust the light beam angle of the affected display partition, thereby reducing the influence of the incident direct light on the user's visual content (highlight overflow, reflection glare) in the area.

[0040] 2. Using the directional light intensity and the monitored application state (for example: reading, video, game, video call, demonstration) to determine the operation scene means that the display optimization is not simply adjusted according to the ambient light full screen, but is differentiated according to the current application demand - for example, when playing a video, the local high dynamic range is preferentially retained; when reading a text, the readability of the text area is preferentially guaranteed rather than the overall brightness.

[0041] 3. By adjusting the light beam angle and output intensity only for the affected partition or key display area, rather than improving the overall panel brightness, the overall backlight or driving energy consumption can be reduced while ensuring the perceived visibility. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor.

[0043] Figure 1 is a flow chart of a smart display optimization method of a tablet computer provided by an embodiment of the present application;

[0044] Figure 2 is a function module diagram of a smart display optimization device of a tablet computer provided by an embodiment of the present application;

[0045] Figure 3 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0047] As shown in Figure 1 is a flow chart of a smart display optimization method of a tablet computer provided by an embodiment of the present application. The smart display optimization method of a tablet computer provided by the embodiment of the present application includes the following steps.

[0048] Step S1, when a preset display environment change signal is detected, grouping and fusing the collected original photoelectric signal set according to a preset direction set to generate direction light intensity data of each direction.

[0049] It should be understood that the display environment change signal is a trigger condition for starting the smart display optimization process of the present application, and is not a single indicator. Instead, it is a logical judgment result composed of two types of physical events: one is the posture mutation signal output by the built-in accelerometer of the device, and the other is the ambient light intensity mutation signal detected by the photoelectric sensor. When the accelerometer detects that the device posture changes significantly (such as horizontal-vertical screen switching or picking up and putting down action), a digital interrupt signal will be generated; at the same time, each photoelectric sensor will continuously monitor the ambient light intensity with a period of 100 milliseconds, and if any sensor detects that the light intensity changes by more than 50 lux threshold, an analog level jump signal will be generated. The embodiment of the present application polls these two signals through a special hardware interface, and once any condition is met, it is determined that the display environment has changed, and the subsequent data acquisition and processing process is triggered. By continuously monitoring the display environment change signal, it is ensured that the system only starts the high-energy-consuming calculation process when the environment actually changes, thereby optimizing the overall power consumption on the premise of ensuring real-time response.

[0050] After obtaining the ambient light change signal, the original photoelectric signals are synchronously collected from the eight wide-angle photoelectric sensors embedded in the tablet frame. The sensors are symmetrically distributed on the four sides of the device (two on each side), and their physical positions are predefined as four main direction sets: front, back, left, and right. The grouping processing process merges the sensor signals belonging to the same direction into the same signal group according to the preset spatial mapping relationship. For example, the two sensors located at the top of the device are classified into the "front" signal group, and the two sensors on the right side are classified into the "right" signal group. This grouping strategy is based on the principle of spatial continuity of optical perception, and by aggregating multiple sensor readings in the same direction, it provides redundant information for subsequent data fusion, thereby improving the robustness of direction light intensity estimation. For example, when the user holds the tablet horizontally, the left hand may partially block the left sensor, but through the compensation of the data from the other sensor in the group, an accurate left ambient light intensity estimate can still be obtained.

[0051] Subsequently, light intensity data conversion and group data mean calculation are performed for each signal group. The original photoelectric signal is an analog voltage value (range 0-3.3V) output by the sensor, which is first quantized to a digital signal (range 0-4095) by a 12-bit analog-to-digital converter, and then converted to an absolute light intensity value in lux units using a factory-precalibrated linear conversion coefficient. The conversion formula is: V =k×D V +b, where k and b are the slope and intercept parameters calibrated for each sensor individually to eliminate individual differences between sensors. D V is the original photoelectric signal in the signal group. After conversion, the arithmetic mean of the two light intensity values in the same signal group is calculated to generate the ambient light intensity data representing the direction. This mean calculation process can effectively suppress single-point measurement errors, such as when a sensor is temporarily disturbed (e.g., by a finger briefly blocking it), the normal reading of the other sensor in the group can balance it out, resulting in a more reliable direction light intensity estimate. For example, in a reading scenario, if the left side of the tablet is close to a desk lamp light source, the readings of the two sensors in the left signal group may be 500 lux and 520 lux, respectively. After mean calculation, 510 lux is output as the light intensity representation of the left direction, which reflects the strong light characteristics on the left side and smooths the small differences between the sensors.

[0052] Finally, the ambient light intensity data in each direction is time-series filtered. Since the ambient light has high-frequency fluctuations (such as flickering caused by fluorescent light, tree leaves swaying), directly using the instantaneous sampling value may cause the display parameters to frequently jump. The system uses a weighted moving average filtering algorithm to smooth the light intensity data. In the embodiments of the application, the latest sampling value is given a weight of 70%, and the historical filtered value is given a weight of 30%. This can quickly track the real change trend of the light intensity, and effectively suppress short-term fluctuation interference. The direction light intensity data output after filtering has time stability, avoiding frequent adjustment of screen brightness caused by small fluctuations in light. For example, when a user uses a tablet in a moving vehicle, the alternating appearance of tree shadows and direct sunlight outside the window will cause rapid changes in light intensity. Time-series filtering can eliminate this high-frequency oscillation, ensuring that the generated direction light intensity data reflects the overall trend of the lighting environment rather than instantaneous disturbances, providing a stable input basis for subsequent scene judgment.

[0053] Step S2, according to the direction light intensity data and the application state data monitored, the application scene is judged by the preset scene mapping rule, and the running scene data is obtained.

[0054] Among them, the real-time acquisition of application state data is to continuously monitor the digital identity information of the current foreground running application through the application programming interface provided by the operating system. The application state data is essentially a structured data object, including the application package name and the predefined category label. For example, when the application with the package name "com.amazon.kindle" is detected to be in an active state, the system will map it to the "e-book reading" category. This direct way of obtaining application state replaces computationally intensive visual behavior analysis, and reliably determines the user's current core use intention with a delay of less than 10 milliseconds by accessing the process management interface of the operating system. By establishing a deterministic basis for user scene judgment, for example, when a video conference application is detected in the foreground, the system can predict in advance that the user needs to maintain facial light uniformity, providing a basis for decision-making for subsequent optical adjustment.

[0055] After obtaining the application state data, the system performs application main scene mapping processing, which relies on the scene mapping rule database pre-stored in the device firmware. The scene mapping rule is a two-dimensional lookup table structure, the first dimension maps the application package name or category to the main scene identifier, and the second dimension defines the judgment logic of the light environment state under different main scenes. The main scene identifier adopts enumeration coding form, using 1 byte length to store the basic scene type, for example, 0x01 represents reading scene, 0x02 represents video playing scene, and 0x03 represents video conference scene. According to the determined main scene identifier, the system activates the corresponding light environment judgment rule to analyze the directional light intensity data: for the reading scene, the rule requires to detect whether the maximum light intensity exceeds 500 lux to judge whether there is strong light interference; for the video playing scene, the rule identifies the backlight interference condition by calculating whether the ratio of the front light intensity to the rear light intensity is lower than 0.3. This scene-based judgment mechanism ensures that the optical optimization strategy is targeted, for example, in the video conference scene, the system will preferentially ensure the light beam uniformity in the center area of the screen to avoid local overexposure or shadow on the faces of the participants.

[0056] After completing the light environment state judgment, the system combines the main scene identifier and the light environment state data to synthesize the running scene data by a combination coding method. The coding process adopts bit field operation technology to divide the 1 byte length running scene data into two fields of high 4 bits and low 4 bits: the high 4 bits store the main scene identifier code, and the low 4 bits store the light environment state code. For example, running scene data 0x13 represents that the main scene is reading (0x1) and the light environment is in strong light state (0x3), and 0x22 represents that the main scene is video playing (0x2) and backlight interference is detected (0x2). This coding scheme not only reduces data transmission bandwidth, but more importantly, establishes a standardized scene description specification, enabling subsequent processing modules to quickly parse scene features through simple bit operations. The running scene data, as the decision hub of the entire intelligent display system, connects the environment perception and optical execution two subsystems, for example, when the system detects scene data coded as 0x13, it automatically triggers a high glare suppression mode, using a narrower light beam angle configuration to improve the readability of the screen in strong light.

[0057] Through multi-level rule mapping and state coding, the original application state and light intensity data are converted into refined scene decision instructions. This rule-based judgment architecture reduces the computing energy consumption by 90% compared with the neural network scheme, while ensuring the predictability of system behavior through explicit decision logic. The running scene data, as a structured decision output, provides control parameters with both semantic clarity and processing efficiency for subsequent light beam angle optimization.

[0058] In step S3, the glare intensity gradient calculation and optimized light beam angle calculation of the local display area are performed according to the running scene data and the directional light intensity data, and the partition target light beam angle data is obtained.

[0059] To obtain the core parameters of optical adjustment by analyzing the running scene data, first, the main scene identifier stored in the running scene data with the high 4 bits is taken as an index to retrieve the corresponding reference beam angle parameter and gradient influence coefficient from the preset parameter database. Among them, the reference beam angle parameter represents the recommended beam divergence angle of the scene under standard environment, for example, the reading scene corresponds to a reference value of 65°, ensuring that the text display has the best contrast and readability; the video playing scene corresponds to a reference value of 110°, providing a wider viewing angle range. The gradient influence coefficient is a symbolic parameter, a positive coefficient indicating that the beam angle needs to be contracted in the high gradient area to suppress glare, and a negative coefficient indicating that the beam angle needs to be expanded to enhance the viewing angle inclusiveness. Through parameterized design, the system can adapt to the optical needs of different scenes. When the running scene data indicates the video conference mode, the system will automatically select the 85° reference beam angle and the negative influence coefficient to prioritize the consistency of the light on the faces of the participants under different viewing angles.

[0060] After obtaining the basic parameters, the system divides the display area into a 16x16 grid of display partitions according to the preset physical partition size, with each partition corresponding to an independent control unit of the backlight module. Since the directional light intensity data only provides macroscopic lighting information in four directions, it is necessary to estimate the light intensity value of the center point of each display partition through a bilinear interpolation algorithm. This algorithm takes the light intensity data in the front, back, left, and right directions as boundary conditions and calculates the light intensity estimate of any point inside the grid based on the coordinate weighting principle, establishing a mapping model from discrete directional data to continuous two-dimensional light intensity distribution. For example, when the left directional light intensity is 500 lux and the right directional light intensity is 200 lux, the system will automatically generate a gradually decaying light intensity distribution field from left to right. This spatial interpolation enables the limited directional sensors to deduce the lighting conditions of the entire screen, providing a data basis for local glare detection.

[0061] Based on the light intensity distribution field, the system calculates the glare intensity gradient of each display partition to quantify the risk of local glare. The glare intensity gradient is calculated by the Sobel operator, which obtains the light intensity change rate (i.e., the glare intensity gradient) in the X and Y directions through convolution operation. The higher the gradient value of the glare intensity gradient, the more intense the light intensity change in that area, and the greater the possibility of glare interference. Combined with the reference beam angle parameter and the gradient influence coefficient, the system dynamically calculates the optimal target beam angle of each partition, where the core algorithm is: . Wherein, is the reference beam angle parameter, is the gradient influence coefficient, is the gradient of the glare intensity. The gradient influence is ensured to be smoothly limited in the range of [-1, 1] by the hyperbolic tangent function tanh, avoiding visual discomfort caused by parameter mutation. When the user reads outdoors under direct sunlight, the left side of the screen may have a high gradient area due to strong light irradiation, and the positive gradient influence coefficient will automatically shrink the beam angle of this area to below 60°, resisting environmental light interference by concentrating light energy.

[0062] Finally, Gaussian smoothing filtering is performed on the optimized target beam angle of all partitions, using a 5x5 convolution kernel to eliminate angle mutations between adjacent partitions. The filtering process ensures that the beam angle changes continuously in space, avoiding visible partition boundary effects. The generated partition target beam angle data forms a 16x16 matrix structure, which not only retains the targeted optimization of high glare areas, but also ensures the visual consistency of the overall display effect, providing accurate spatial control parameters for subsequent phase modulation. Through the gradient-aware adaptive algorithm, the precise conversion from macroscopic scene judgment to microscopic pixel-level optical regulation is realized, enabling the display system to intelligently cope with complex light environment challenges.

[0063] Step S4, modulating the voltage signal according to the partition target beam angle data to generate a driving voltage signal.

[0064] It should be understood that the technical solution of step S4 of the embodiments of the present application relies on the hardware architecture of the polarization modulation liquid crystal cell and the birefringent film group, which is integrated between the backlight unit and the liquid crystal panel of the tablet display module. The core hardware includes a layered transparent ITO electrode array and a liquid crystal material layer, where the ITO electrode is patterned and etched according to the screen partition to form a 16x16 independent controllable conductive area, each electrode partition is accurately aligned with the backlight optical partition; the liquid crystal layer uses negative nematic material, whose molecular orientation rotates under voltage control, thereby changing the polarization state of the transmitted light. The birefringent film group is attached to the light-emitting side of the liquid crystal layer, using a DBEF film with a thickness of 50-100 microns, whose optical anisotropy causes path deflection of light with different polarization directions.

[0065] The deflection angle mapping rule adopted by the embodiments of the present application is used to convert the target beam angle data of each display partition into a physical control parameter of liquid crystal molecules. Among them, the partition target beam angle data is a matrix containing 256 optimized angle values, and each value represents the beam divergence angle (i.e., the optimized target beam angle) that the corresponding display partition needs to achieve. The deflection angle mapping rule is an optical conversion model preset in the system firmware, which establishes a mathematical relationship between the "optimized target beam angle - light path deflection angle - liquid crystal deflection angle". The rule first converts the target beam angle into the required light path deflection angle according to the principle of geometric optics, and then calculates the liquid crystal molecule deflection angle (i.e., the liquid crystal deflection angle) required to achieve the light path deflection based on the birefringence physical effect. Among them, the birefringence physical effect can be expressed as β = arcsin(n e ×sinθ - n o ). β is the light path deflection angle, which is used to represent the included angle between the actual exit direction of the light after passing through the birefringent film group and the original light path, and β directly determines the divergence angle of the screen beam of this partition. The larger β is, the more significant the beam deflection is, and the narrower the exit beam angle (the light is more concentrated); the smaller or no deflection β is, the wider the beam angle (the light is more dispersed). θ is the liquid crystal deflection angle, which is used to represent the angle of rotation of the liquid crystal molecules from the initial parallel arrangement direction after the voltage is applied. The realization of the liquid crystal deflection angle θ is precisely controlled by changing the voltage applied to the ITO electrode. The higher the voltage, the larger the liquid crystal deflection angle θ is generally (depending on the type of liquid crystal). The liquid crystal deflection angle θ directly modulates the polarization direction of the incident light. After the polarized light after rotation enters the birefringent film, its propagation path will change. e n o is the core parameter for describing the optical anisotropy of birefringent materials (such as DBEF) (i.e., the inherent physical property of the material, which is determined by the chemical composition and microstructure of the birefringent film itself). e (Extraordinary light refractive index): For light whose polarization direction is parallel to the optical principal axis of the material, the refractive index corresponding to the propagation speed. The light in this direction will be deflected. o (Odinary light refractive index): For light whose polarization direction is perpendicular to the optical principal axis of the material, the refractive index corresponding to the propagation speed. The light in this direction does not deflect. (n e -n o ) is called birefringence, which determines the deflection ability of the material to polarized light. The larger the difference is, the stronger the control ability of the light direction is. For example, when the optimized target beam angle of a certain partition is 65°, the mapping rule calculates that the liquid crystal deflection angle of the corresponding region needs to be 38° through internal calculation, and this conversion process ensures that the optical target can be accurately converted into executable physical control instructions.

[0066] After obtaining the target value of the liquid crystal deflection angle, the system converts it into a driving voltage through a voltage-deflection angle mapping table. The voltage-deflection angle mapping table is a key parameter table established during the factory calibration stage, which records the correspondence between the liquid crystal deflection angle and the driving voltage. This relationship is determined by the electro-optic properties of the liquid crystal material, which has nonlinear characteristics. The mapping table is stored in a lookup table structure, with the deflection angle as the index value and the driving voltage. The system can obtain the accurate driving voltage value by querying the table according to the target deflection angle. For example, to achieve a 38° liquid crystal deflection angle, the corresponding driving voltage is 4.2V, which will cause the liquid crystal molecules to produce an accurate angle deflection. The mapping relationship between voltage and deflection angle will drift with temperature changes, so the mapping table includes temperature compensation parameters to ensure control accuracy at different environmental temperatures. The voltage-deflection angle mapping table is stored in the device's non-volatile memory, with each partition independently storing voltage-angle data for 10 calibration points. Linear interpolation is used to calculate intermediate values to ensure control accuracy.

[0067] The generation of the driving voltage signal is completed by a partition display driving chip, which contains 256 independently programmable voltage output channels. Each channel generates an AC driving signal in the range of 0.5-12V according to the assigned voltage value (i.e., the driving voltage), with a frequency of 1kHz to avoid liquid crystal polarization effects. The voltage signal is transmitted to the ITO electrode of the corresponding partition through row and column leads, forming a spatial electric field distribution to control the orientation of liquid crystal molecules. Specifically, the driving voltage is combined to generate a driving voltage signal according to the area information of the display partition. The area information of the display partition refers to the physical position coordinates of each partition on the screen. The system arranges the 256 independent driving voltage values in a matrix structure according to these coordinates. This voltage matrix is transmitted to the control circuit of the screen backplane through the display driving interface, and each voltage value is applied to the corresponding transparent ITO electrode of the partition. The driving voltage signal is in the form of an AC square wave, with a voltage range of 0.5V to 12V and a frequency above 1kHz to avoid liquid crystal material polarization. For example, in a reading scenario, the edge area of the screen may receive a 6.5V driving voltage, while the center area receives a 3.0V voltage. This partition voltage difference causes the liquid crystals in different areas to produce different deflection angles, ultimately achieving differential beam control effects through the birefringent film.

[0068] It should be understood that the optical modulation effect is based on the principle of polarization path control: the non-polarized light emitted by the backlight source first becomes linearly polarized light through the lower polarizer, and when the polarized light penetrates the liquid crystal layer, the polarization direction is modulated by the voltage-controlled molecular orientation, and the rotated polarized light enters the birefringent film group to be path deflected, and the deflection angle is determined by the polarization direction. This hardware architecture realizes pixel-level beam angle regulation while maintaining the thin design of the display module, with an increase in the overall optical stack thickness of less than 0.3 mm, fully meeting the integration requirements of tablet computers. The response time of the driving voltage signal is controlled within 20 milliseconds, ensuring that the display effect adapts to environmental changes in real time and provides users with a stable visual experience.

[0069] To realize feedback calibration, the method further activates the photoelectric sensor array hidden in the screen periphery by inserting a full-white test picture during the video blanking period. The photoelectric sensors with fixed angles are distributed in an embedded structure inside the display screen frame, containing 12 photoelectric diodes with different orientations, whose pointing angles cover the range of -75° to +75° and are uniformly distributed with an interval of 7.5°. When the system triggers the calibration period, the backlight module outputs a white picture with full brightness for 5 milliseconds, and the photoelectric sensor array synchronously collects light intensity data at each angle at a sampling rate of 100 kHz. This synchronous sampling mechanism ensures that the measurement data accurately reflects the light beam distribution characteristics at a specific time, for example, when measuring the central partition of the screen, the 12 sensors will simultaneously record the light intensity values at 0°, ±7.5°, ±15°, etc. different directions, forming a complete angle and light intensity distribution curve (i.e., angle distribution data).

[0070] After obtaining the angle distribution data, the system performs standard deviation calculation and full-width-at-half-maximum analysis to process the angle distribution data of each partition. The standard deviation calculation uses the classic formula where is the sensor angle, μ is the light beam center direction, is the corresponding angle light intensity value. This calculation process quantifies the dispersion degree of the light beam distribution, and the larger the σ value, the more divergent the light beam. The full-width-at-half-maximum calculation determines the actual beam angle by finding the angle width corresponding to the position of 50% of the maximum light intensity on the light intensity distribution curve. For example, when σ=15° is measured, the system calculates the actual beam angle as 35.3°, which is compared with the target beam angle to evaluate the execution precision of the optical system.

[0071] Based on the actual beam angle measurement value, the system calculates the beam angle error and generates the offset calibration quantity. The beam angle error is the difference between the optimized target beam angle and the actual beam angle. The offset calibration quantity used in the embodiments of the present application is calculated by a PID controller, and its mathematical expression is where , , Kp, Ki, Kd are proportional, integral, derivative gain coefficients respectively. The proportional term should respond to current error, the integral term accumulates historical error, and the derivative term predicts error trend, the combination of the three ensures the accuracy and stability of the calibration quantity. When a persistent positive error of +3° is detected in the left partition of the screen, the integral term will gradually increase the calibration quantity, systematically correcting the voltage bias of this region.

[0072] The final stage updates the voltage-deflection angle mapping table according to the offset calibration quantity. The voltage-deflection angle mapping table is a two-dimensional lookup table stored in the device's non-volatile memory, recording the mapping relationship between phase values and driving voltages. The calibration update adopts a global offset strategy, increasing all voltage values in the mapping table by the offset calibration quantity obtained above. This global calibration method is based on the assumption that the optical system error is consistent overall, for example, when the temperature rises and the response sensitivity of the liquid crystal material decreases, the entire mapping table needs to be uniformly increased in driving voltage to compensate for performance drift. The updated mapping table will take effect immediately and be used continuously until the next calibration cycle detects a new system error. The entire feedback calibration process is controlled through a closed-loop of measurement-computation-update, ensuring that the display system can maintain accurate optical performance under various environmental conditions, solving the long-term stability problems such as temperature drift and aging attenuation.

[0073] The application is applied to the technical field of display optimization. When a display environment change signal is detected, the original set of photoelectric signals is grouped and fused according to the direction set to generate directional light intensity data of each direction. Application scene data is obtained by judging the application scene according to the directional light intensity data and application state data. The gradient calculation of glare intensity and the calculation of the target beam angle of the partition are performed according to the running scene data and the directional light intensity data to obtain the partition target beam angle data. The driving voltage signal is generated by modulating the voltage signal of display adjustment according to the partition target beam angle data. The application can improve the visibility in outdoor and strong light, retain color and contrast, reduce energy consumption and eye fatigue, and improve user experience through directional perception light intensity partition fusion, scene perception decision, and gradient-based local beam angle optimization, and fine adjustment through phase driving.

[0074] As shown in Figure 2 , it is a functional module diagram of the smart display optimization device of the tablet computer provided by the embodiment of the application.

[0075] In some embodiments, the smart display optimization device 2 of the tablet computer can include a plurality of function modules composed of computer program segments. The computer programs of each program segment in the smart display optimization device 2 of the tablet computer can be stored in the memory of the server and executed by at least one processor to perform the functions of the smart display optimization method of the tablet computer (see Figure 1 Description) for details.

[0076] In this embodiment, the smart display optimization device 2 of the tablet computer can be divided into a plurality of functional modules according to the functions performed by the device. The functional modules can include a light intensity detection module 21, a scene mapping module 22, a light beam adjustment module 23, a signal modulation module 24, and a feedback adjustment module 25. The module referred to in the present application refers to a series of computer program segments that can be executed by at least one processor and can complete a fixed function, which are stored in a memory. In this embodiment, the functions of the modules will be described in detail in subsequent embodiments.

[0077] The light intensity detection module 21 is configured to, when a preset display environment change signal is detected, group and fuse the collected original photoelectric signal set according to a preset direction set to generate directional light intensity data of each direction.

[0078] In an optional implementation, the light intensity detection module 21 is specifically configured to:

[0079] grouping and processing the collected original photoelectric signals according to the preset direction set to obtain a signal group corresponding to each direction;

[0080] performing light intensity data conversion and same-group data mean calculation on the signal group to generate environmental light intensity data of each direction;

[0081] performing time sequence filtering processing on the environmental light intensity data of each direction to obtain directional light intensity data of each direction.

[0082] The scene mapping module 22 is configured to perform application scene judgment according to the directional light intensity data and the monitored application state data through a preset scene mapping rule to obtain running scene data.

[0083] In an optional implementation, the scene mapping module 22 is specifically configured to:

[0084] monitoring application package names and category information of currently running foreground applications in real time through a preset system interface to obtain application state data;

[0085] performing main scene mapping processing on the application state data through a preset scene mapping rule to obtain a main scene identifier, and performing light environment state judgment on the directional light intensity data through the scene mapping rule according to the main scene identifier to obtain corresponding light environment state data;

[0086] combining and encoding the main scene identifier and the light environment state data through a preset encoding mode to generate running scene data.

[0087] The light beam adjusting module 23 is configured to calculate a glare intensity gradient of a local display area and calculate an optimized light beam angle according to the operation scene data and the directional light intensity data, and obtain partition target light beam angle data.

[0088] In an optional embodiment, the light beam adjusting module 23 is specifically configured to:

[0089] The reference light beam angle parameter and the gradient influence coefficient corresponding to the operation scene data are obtained according to a preset parameter mapping rule;

[0090] The display area is regionally divided to generate a display partition set according to a preset display partition size, and the light intensity distribution of each display partition of the display partition set is estimated according to the directional light intensity data, and the light intensity value of the center point of each display partition is obtained;

[0091] The glare intensity gradient of each display partition is calculated according to the light intensity value, and the optimized target light beam angle of each display partition is calculated according to the glare intensity gradient, the reference light beam angle parameter and the gradient influence coefficient;

[0092] The optimized target light beam angles of all display partitions are smoothed and filtered to obtain the partition target light beam angle data.

[0093] The signal modulation module 24 is configured to modulate a voltage signal for display adjustment according to the partition target light beam angle data, and generate a driving voltage signal.

[0094] In an optional embodiment, the signal modulation module 24 is specifically configured to:

[0095] The optimized target light beam angle of each display partition is converted into a corresponding liquid crystal deflection angle according to a preset deflection angle mapping rule;

[0096] The liquid crystal deflection angle is converted into a corresponding driving voltage of each display partition according to a preset voltage and deflection angle mapping table;

[0097] The driving voltage is combined according to the area information of the display partition to generate a driving voltage signal.

[0098] In an optional embodiment, the smart display optimization device 2 of the tablet computer further comprises a feedback adjusting module 25, and the feedback adjusting module 25 is specifically configured to:

[0099] The angle distribution data of the actual outgoing light beam of each display partition screen is collected by a fixed-angle photoelectric sensor, and the standard deviation and full width at half maximum of the angle distribution data of each display partition are calculated to generate the actual light beam angle of each display partition.

[0100] According to the actual beam angle of each display partition and the corresponding optimized target beam angle, a beam angle error is calculated, and according to a preset gain coefficient and the beam angle error, a shift calibration quantity is calculated;

[0101] According to the shift calibration quantity, the voltage and deflection angle mapping table is updated.

[0102] It should be understood that the various changes and specific embodiments in the method provided by the above embodiments are also applicable to the smart display optimization device of the tablet computer in the present embodiment. Through the foregoing detailed description of the smart display optimization method of the tablet computer, those skilled in the art can clearly understand the implementation method of the smart display optimization device of the tablet computer in the present embodiment. For the sake of brevity of the description, the implementation method of the smart display optimization device of the tablet computer in the present embodiment will not be described in detail here.

[0103] As shown in Figure 3 , it is a structure schematic diagram of an electronic device provided by the embodiment of the present application.

[0104] In the preferred embodiment of the present application, the electronic device 3 can include, but is not limited to, a memory 31, at least one processor 32, and at least one communication bus 33.

[0105] Those skilled in the art should understand that Figure 3 The structure of the electronic device 3 shown is not a limitation of the embodiment of the present application. The electronic device 3 can also include more or less other hardware or software, or different component arrangements.

[0106] In some embodiments, the electronic device 3 is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions. The hardware thereof includes, but is not limited to, a microprocessor, an application specific integrated circuit, a programmable gate array, a digital processor, and an embedded device.

[0107] It should be noted that the electronic device 3 is only an example. Other existing or future electronic products, such as those that can be adapted to the present application, should also be included within the protection scope of the present application and are hereby incorporated by reference.

[0108] In some embodiments, the memory 31 stores a computer program which, when executed by the at least one processor 32, implements all or part of the steps of the method of intelligent display optimization of a tablet computer as described. The memory 31 includes a Read-Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically-Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM), or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other medium of storage of computer-readable program code. Further, the computer-readable storage medium can include a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs required by at least one function, and the like.

[0109] In some embodiments, the at least one processor 32 is a control unit of the electronic device 3, which connects various components of the entire electronic device 3 through various interfaces and lines, and performs various functions of the electronic device 3 and processes data by running or executing programs or modules stored in the memory 31 and calling data stored in the memory 31. For example, the at least one processor 32 implements all or part of the steps of the method of intelligent display optimization of a tablet computer as described in the embodiments of the present application when executing the computer program stored in the memory 31, or implements all or part of the functions of the intelligent display optimization apparatus of a tablet computer. The at least one processor 32 can be composed of integrated circuits, for example, can be composed of a single packaged integrated circuit, or can be composed of multiple packaged integrated circuits with the same function or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips.

[0110] In some embodiments, the at least one communication bus 33 is configured to enable connection communication between the memory 31 and the at least one processor 32. Although not shown, the electronic device 3 can further include a power supply (such as a battery) for powering the various components of the electronic device 3. Preferably, the power supply is logically connected to the at least one processor 32 via a power management device, thereby enabling management of charging, discharging, and power consumption management, etc. by the power management device. The power supply can also include one or more direct current or alternating current power sources, recharging circuits, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 3 can further include a variety of sensors, a Bluetooth module, a Wi-Fi module, and the like, which are not described herein.

[0111] The integrated units in the form of software function modules described above can be stored in a computer readable storage medium. The software function modules described above are stored in a storage medium, and include a plurality of instructions for causing an electronic device (which can be a personal computer, an electronic device, or a network device, etc.) or a processor to execute part of the method described in various embodiments of the present application.

[0112] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other manners. For example, the described apparatus embodiments are merely illustrative. For example, the division of the modules is merely a logical function division. There can be another division manner in actual implementation.

[0113] The modules illustrated as separated components can or can not be physically separated, and the components illustrated as modules can or can not be physical units. They can be located in one place or distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments.

[0114] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, any equivalent changes made on the structure, shape, and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for optimizing the intelligent display of a tablet computer, characterized in that, The method includes: When a preset display environment change signal is detected, the collected raw photoelectric signal set is grouped and fused according to the preset direction set to generate directional light intensity data in each direction; By using preset scene mapping rules, the application scene is determined based on the directional light intensity data and the monitored application status data to obtain the running scene data. Based on the running scenario data, the corresponding reference beam angle parameters and gradient influence coefficients are obtained through preset parameter mapping rules. The display area is divided into regions according to the preset display partition size to generate a display partition set, and the light intensity distribution of each display partition in the display partition set is estimated according to the directional light intensity data to obtain the light intensity value of the center point of each display partition. The glare intensity gradient of each display zone is calculated based on the light intensity value, and the optimized target beam angle of each display zone is calculated based on the glare intensity gradient, the reference beam angle parameter, and the gradient influence coefficient. The optimized target beam angle of all display zones is smoothed and filtered to obtain the zone target beam angle data; The voltage signal is modulated based on the target beam angle data of the partition to generate a driving voltage signal.

2. The intelligent display optimization method for a tablet computer according to claim 1, characterized in that, The step of grouping and fusing the acquired raw photoelectric signal set according to a preset direction set to generate directional light intensity data in each direction includes: Based on a preset direction set, the acquired raw photoelectric signals are grouped and processed to obtain signal groups corresponding to each direction; The light intensity data of the signal group is converted and the mean value of the data in the same group is calculated to generate ambient light intensity data in each direction. The ambient light intensity data in each direction are processed by time-series filtering to obtain the directional light intensity data in each direction.

3. The intelligent display optimization method for a tablet computer according to claim 1, characterized in that, The process of determining the application scenario based on the directional light intensity data and the monitored application status data using preset scene mapping rules, and obtaining the running scenario data, includes: The application status data can be obtained by monitoring the package name and category information of the currently running application in the foreground through a preset system interface in real time. Based on the application status data, the main scene identifier is obtained by performing application main scene mapping processing through preset scene mapping rules, and the light environment status of the directional light intensity data is judged according to the main scene identifier and the scene mapping rules to obtain the corresponding light environment status data. The main scene identifier and the light environment status data are combined and encoded using a preset encoding method to generate running scene data.

4. The intelligent display optimization method for a tablet computer according to claim 1, wherein the partition target beam angle data includes the optimized target beam angle of each display partition; characterized in that, The voltage signal modulation for display adjustment based on the partitioned target beam angle data, generating the driving voltage signal includes: By using a preset deflection angle mapping rule, the optimized target beam angle of each display zone is converted into the corresponding liquid crystal deflection angle; According to the preset voltage and deflection angle mapping table, the liquid crystal deflection angle is converted into the driving voltage corresponding to each display partition; The driving voltages are combined according to the area information of the display partition to generate a driving voltage signal.

5. The intelligent display optimization method for a tablet computer according to claim 4, characterized in that, The method further includes: The actual beam angle of each display zone is generated by collecting the angular distribution data of the emitted beam from each display zone screen using a photoelectric sensor with a fixed angle. The standard deviation and full width at half maximum (FWHM) of the angular distribution data of each display zone are calculated. The beam angle error is calculated based on the actual beam angle of each display zone and the corresponding optimized target beam angle, and the offset calibration amount is calculated based on the preset gain coefficient and the beam angle error. The voltage and deflection angle mapping table is calibrated and updated based on the offset calibration amount.

6. A smart display optimization device for a tablet computer, applied to the smart display optimization method for a tablet computer as described in claim 1, characterized in that, The device includes: The light intensity detection module is used to group and fuse the collected raw photoelectric signal set according to the preset direction set when a preset display environment change signal is detected, and generate directional light intensity data in each direction. The scene mapping module is used to determine the application scene based on the directional light intensity data and the monitored application status data according to the preset scene mapping rules, and obtain the running scene data. The beam adjustment module is used to calculate the glare intensity gradient of the local display area and optimize the beam angle calculation based on the running scene data and the directional light intensity data, so as to obtain the target beam angle data of the partition. The signal modulation module is used to modulate the voltage signal for display adjustment based on the partition target beam angle data, and generate a driving voltage signal.

7. An electronic device, characterized in that, The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the intelligent display optimization method for a tablet computer according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent display optimization method for a tablet computer according to any one of claims 1 to 5.

Images