An OLED display brightness and contrast combined adjustment system based on artificial intelligence

Abstract

The application relates to the technical field of regulation and control, and discloses an OLED display brightness-contrast combined regulation system based on artificial intelligence. The system collects OLED display brightness data and contrast data under the condition that the brightness is unchanged to construct a sample set, and pre-processes the OLED display brightness data collected in the sample set; meanwhile, a brightness regulation relationship model is established based on the pre-processed OLED display brightness data; meanwhile, a contrast-brightness combined regulation model is established based on the established brightness regulation relationship model and a contrast regulation algorithm; after the contrast-brightness combined regulation model is established, the contrast-brightness combined regulation model is optimized through a genetic algorithm, and the OLED display brightness-contrast combined regulation is realized based on the optimized contrast-brightness combined regulation model, so that the intelligence and efficiency of the OLED display brightness-contrast combined regulation are ensured.

Description

Technical Field

[0001] The present invention relates to the field of regulation and control technology, and in particular to an artificial intelligence-based OLED display brightness and contrast combination regulation system. Background Art

[0002] With the continuous advancement of science and technology, a wide variety of electronic products have been manufactured and widely used in various fields of civil, medical, and social life. As a key component of most electronic products, displays are also constantly upgraded. Brightness and contrast adjustment are key factors in determining the effectiveness of displays. However, existing displays often only have fixed brightness and contrast settings, which cannot meet user expectations.

[0003] Existing technologies, such as Chinese patent application CN106707861A, collect the light intensity of the surrounding environment through a light intensity collection unit, convert the collected light intensity into a corresponding electrical signal value, and compare the electrical signal value with the previous stored electrical signal value. If the change in the electrical signal values ​​of the two exceeds a set threshold, the electrical signal value is stored, and an interrupt signal is generated and sent to a central processing control unit. When the central processing control unit receives the interrupt signal, it reads the stored electrical signal value and controls the power management unit to output a corresponding power supply voltage to the display unit according to the electrical signal value; the display unit controls the display brightness of the display screen according to the received power supply voltage, which only realizes brightness adjustment and does not take into account the contrast adjustment of the display screen, which has great limitations. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In response to the shortcomings of the existing technology, the present invention provides an artificial intelligence-based OLED display brightness and contrast combination adjustment system, which has the advantages of intelligence and high efficiency, and solves the problem that the brightness and contrast adjustment of existing displays can often only be achieved with fixed adjustment.

[0006] (2) Technical solution

[0007] In order to solve the technical problem that the brightness and contrast of the conventional display can only be adjusted in a fixed manner, the present invention provides the following technical solutions:

[0008] The present invention discloses an artificial intelligence-based brightness and contrast combination adjustment method for an OLED display, which specifically includes the following steps:

[0009] S1. Collecting brightness data of the OLED display and contrast data when the brightness remains unchanged, and constructing a sample set based on the collected brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0010] The OLED display brightness data includes: user input brightness data and display brightness data;

[0011] The user inputs brightness data in the range of [0%, 100%], and the display brightness data is represented by the brightness quantization of the three colors R, G, and B, and the brightness quantization range of the three colors R, G, and B is [0, 255];

[0012] S2. Preprocessing the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establishing a brightness adjustment relationship model;

[0013] S3. Based on the established brightness adjustment relationship model and contrast adjustment algorithm, establish a contrast and brightness combination adjustment model;

[0014] S4. Based on the collected OLED display brightness data and the contrast data when the brightness remains unchanged, the contrast and brightness combination adjustment model is processed by a genetic algorithm to obtain an optimal contrast and brightness combination adjustment model;

[0015] S5. Combining and adjusting the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combination adjustment model;

[0016] The combined adjustment of the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combined adjustment model includes:

[0017] By inputting the user input brightness data into the obtained optimal contrast and brightness combination adjustment model, the optimal contrast and brightness combination adjustment model adjusts the display brightness and contrast based on the user input brightness data.

[0018] The present invention constructs a sample set by collecting brightness data of an OLED display and contrast data under a condition where the brightness remains unchanged, preprocesses the brightness data of the OLED display collected in the sample set, and establishes a brightness adjustment relationship model based on the preprocessed brightness data of the OLED display. At the same time, a contrast and brightness combination adjustment model is established based on the established brightness adjustment relationship model and a contrast adjustment algorithm. After the contrast and brightness combination adjustment model is established, the established contrast and brightness combination adjustment model is optimized by a genetic algorithm, and brightness and contrast combination adjustment of the OLED display is implemented based on the optimized contrast and brightness combination adjustment model, thereby ensuring the intelligence and efficiency of the brightness and contrast combination adjustment of the OLED display.

[0019] Preferably, the preprocessing of the OLED display brightness data collected from the sample set to obtain the preprocessed OLED display brightness data and establishing a brightness adjustment relationship model comprises the following steps:

[0020] S21, filtering the OLED display brightness data in the sample set to obtain filtered OLED display brightness data;

[0021] Setting a one-to-one correspondence between the user input brightness data and the display brightness data in the OLED display brightness data; when the user input brightness data or the display brightness data in the OLED display brightness data is missing, deleting the missing user input brightness data or the display brightness data, and deleting the user input brightness data or the display brightness data corresponding to the missing data to achieve filtering; the remaining OLED display brightness data in the sample set is the filtered OLED display brightness data;

[0022] S22 , sorting the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model.

[0023] Preferably, the step of arranging the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model comprises the following steps:

[0024] Arrange the filtered OLED display brightness data in descending order, and determine the grayscale level of the current OLED display based on the number of bits of the current processor. When the processor is 8 bits, the grayscale level of the corresponding OLED display is 2 to the power of 8, which is 256 levels of grayscale;

[0025] For a 64-level grayscale OLED display, the number of bits required to convert the brightness of each color in the display brightness data into binary brightness data is 6 bits;

[0026] The brightness adjustment algorithm formula is as follows:

[0027] Y=K×X

[0028] Where Y is the output 6-bit binary brightness data, which represents the desired brightness value after adjustment; X is the input 6-bit binary brightness data; and K is the user input brightness data.

[0029] A brightness adjustment relationship model is constructed based on the brightness adjustment algorithm. The brightness adjustment relationship model formula is as follows:

[0030] L=L min +(L max -L min )×(Y / 255)2

[0031] Wherein, L represents the actual achieved brightness value after adjustment, L max represents the maximum brightness, L min represents the minimum brightness.

[0032] The present application filters the OLED display brightness data collected in the sample set through data cleaning, and establishes a brightness adjustment relationship model based on the filtered data according to a brightness adjustment algorithm, thereby ensuring the accuracy of OLED display brightness adjustment.

[0033] Preferably, the contrast and brightness combined adjustment model is established based on the established brightness adjustment relationship model and the contrast adjustment algorithm, and includes the following steps:

[0034] For a 64-level grayscale OLED display, the contrast adjustment algorithm formula is as follows:

[0035] D=64(X÷64) γ

[0036] Wherein, X is the input 6-bit binary brightness data, D is the output 6-bit binary brightness data, represents the expected contrast value after adjustment, the contrast value represents the ratio of the maximum brightness to the minimum brightness of the OLED display, and γ is the contrast adjustment variable.

[0037] The contrast and brightness combined adjustment model is as follows:

[0038] Q=K(L÷64) γ

[0039] Wherein, Q is the output 6-bit binary brightness data after contrast and brightness combined adjustment, represents the expected combined adjustment value of contrast and brightness after adjustment, K is the user input brightness data, γ is the contrast adjustment variable, and L represents the actual achieved brightness value after adjustment.

[0040] The present application establishes the contrast and brightness combined adjustment model through the established brightness adjustment relationship model and the contrast adjustment algorithm, thereby ensuring the reliability of the contrast and brightness combined adjustment model.

[0041] Preferably, the contrast and brightness combined adjustment model is processed by a genetic algorithm based on the collected OLED display brightness data and the contrast data under the condition that the brightness is unchanged, and includes the following steps:

[0042] S41, randomly select the pre-processed OLED display brightness data and contrast data, select N processed brightness data and contrast data and sequentially number them to obtain chromosome coding, and the chromosome coding set is:

[0043] {1(225,225,225,400:1),2(200,200,225,400:1),...,N(255,255,255,600:1)}

[0044] Among them, 1 represents the chromosome code of the brightness data and contrast data after processing numbered 1, N represents the chromosome code of the brightness data and contrast data after processing numbered N, 225, 225, 225 represent the brightness quantization values ​​of R, G, and B respectively, 400:1 represents the contrast value at the current brightness, 200, 200, 225 represent the brightness quantization values ​​of R, G, and B respectively, 255, 255, 255 represent the brightness quantization values ​​of R, G, and B respectively, and 600:1 represents the contrast value at the current brightness;

[0045] S42, initializing the population;

[0046] S43, establishing a fitness function;

[0047] S44, genetic operator selection operation;

[0048] S45, chromosome crossover operation;

[0049] S46, iteratively executing steps S42-S45 until the contrast adjustment variable converges, and outputting the optimal individual under each brightness group;

[0050] The converged contrast adjustment variable is used as the contrast adjustment variable in the calculation of the current contrast and brightness combination adjustment model, thereby obtaining the optimal contrast and brightness combination adjustment model.

[0051] Preferably, the population initialization comprises the following steps:

[0052] Select 4 chromosome codes from the N processed brightness data and contrast data to generate an initial population;

[0053] Sort the data in the generated initial population by number;

[0054] By setting the initial value of the contrast adjustment variable in the contrast and brightness combination adjustment model, the data in the sorted initial population is adjusted based on the contrast and brightness combination adjustment model with the set initial value of the contrast adjustment variable to obtain the data after contrast and brightness combination adjustment.

[0055] Preferably, the establishing of the fitness function comprises the following steps:

[0056] During the process of adjusting the data in the sorted initial population by the contrast and brightness combination adjustment model, when the user is satisfied with the brightness of the OLED display after the current contrast and brightness combination adjustment, the fitness value of the contrast and brightness combination adjustment is determined by the user touching the OLED display;

[0057] When the contrast and brightness combination adjustment model is adjusting the data in the sorted initial population, if the user does not touch the OLED display to determine the fitness value after the contrast and brightness combination adjustment, a new population is generated and processed by the genetic algorithm;

[0058] Recording the fitness value after the determined contrast and brightness combination is adjusted, and setting the fitness value after the determined contrast and brightness combination is adjusted as a genetic operator;

[0059] Constructing a fitness function based on the determined fitness value after adjusting the contrast and brightness combination;

[0060] The fitness function is set as follows:

[0061]

[0062] Among them, Fix(i) represents the fitness of the contrast and brightness of the i-th group in the initialization population, Q i Represents the contrast and brightness combination adjustment value of the i-th contrast and brightness group of the initialized population in the fitness function.

[0063] Preferably, the genetic operator selection operation comprises the following steps:

[0064] By randomly selecting the genetic operator in a roulette wheel manner, the probability of each contrast and brightness group being selected is proportional to the fitness, and the contrast and brightness with the highest fitness are selected;

[0065] The probability formula for the genetic operator to be selected is as follows:

[0066]

[0067] Where I represents the population size, Fix(i) represents the fitness of the i-th contrast and brightness group in the initialization population, and p(i) represents the probability that the i-th contrast and brightness group in the initialization population is selected.

[0068] Preferably, the chromosome crossover operation comprises the following steps:

[0069] The chromosome codes of the selected genetic operators are copied to generate offspring populations, the chromosome codes in the generated offspring populations are randomly paired, and crossover points are randomly selected. The genetic operators in the generated offspring populations are cross-propagated by sequential crossover to generate a new pair of chromosome codes.

[0070] The newly generated chromosome codes are also used as data to participate in the iteration.

[0071] The present invention uses a genetic algorithm to optimize the established contrast and brightness combination adjustment model by performing chromosome encoding, population initialization, fitness function establishment, and genetic operator selection and crossover operations on brightness data, contrast data under the condition of constant brightness, and the established contrast and brightness combination adjustment model, thereby ensuring the accuracy and reliability of the brightness and contrast combination adjustment method for OLED displays.

[0072] The present invention discloses an artificial intelligence-based OLED display brightness and contrast combination adjustment system, comprising: a data collection module, a database, a brightness and contrast combination adjustment module, an adjustment optimization module, and a display module;

[0073] The data collection module is used to collect brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0074] The database is used to store the brightness data of the OLED display and the contrast data when the brightness remains unchanged collected by the data collection module;

[0075] The brightness and contrast combination adjustment module is used to establish a contrast and brightness combination adjustment model through a brightness adjustment algorithm and a contrast adjustment algorithm;

[0076] The adjustment optimization module is used to optimize the established contrast and brightness combination adjustment model through a genetic algorithm;

[0077] The display module is used to display the brightness data and contrast data adjusted by the contrast and brightness combination adjustment model.

[0078] (3) Beneficial effects

[0079] Compared with the prior art, the present invention provides an artificial intelligence-based OLED display brightness and contrast combination adjustment system, which has the following beneficial effects:

[0080] 1. The application constructs a sample set by collecting OLED display brightness data and contrast data under the condition that the brightness is unchanged, pre-processes the OLED display brightness data collected in the sample set, establishes a brightness adjustment relationship model based on the pre-processed OLED display brightness data, establishes a contrast and brightness combined adjustment model based on the established brightness adjustment relationship model and a contrast adjustment algorithm, optimizes the established contrast and brightness combined adjustment model by using a genetic algorithm after the establishment of the contrast and brightness combined adjustment model, and realizes OLED display brightness and contrast combined adjustment based on the optimized contrast and brightness combined adjustment model, thereby ensuring the intelligence and efficiency of OLED display brightness and contrast combined adjustment.

[0081] 2. The application realizes data cleaning and filtering of the OLED display brightness data collected in the sample set, and establishes a brightness adjustment relationship model based on the filtered data according to a brightness adjustment algorithm, thereby ensuring the accuracy of OLED display brightness adjustment.

[0082] 3. The application realizes the establishment of a contrast and brightness combined adjustment model based on the established brightness adjustment relationship model and a contrast adjustment algorithm, thereby ensuring the reliability of the establishment of the contrast and brightness combined adjustment model.

[0083] 4. The application realizes the optimization of the established contrast and brightness combined adjustment model by using a genetic algorithm, through the operations of chromosome coding, population initialization, establishment of fitness function and genetic operator selection and crossover of the brightness data and contrast data under the condition that the brightness is unchanged and the established contrast and brightness combined adjustment model, thereby ensuring the accuracy and reliability of the OLED display brightness and contrast combined adjustment method. BRIEF DESCRIPTION OF DRAWINGS

[0084] Figure 1 The figure is a flow structure diagram of the OLED display brightness and contrast combined adjustment method of the application.

[0085] Figure 2 The figure is a flow chart of the optimization of the contrast and brightness combined adjustment model of the application. DETAILED DESCRIPTION

[0086] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0087] The present invention discloses an artificial intelligence-based brightness and contrast combination adjustment method for an OLED display, which specifically includes the following steps:

[0088] S1. Collecting brightness data of the OLED display and contrast data when the brightness remains unchanged, and constructing a sample set based on the collected brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0089] The OLED display brightness data includes: user input brightness data and display brightness data;

[0090] The user inputs brightness data in the range of [0%, 100%], and the display brightness data is represented by the brightness quantization of the three colors R, G, and B, and the brightness quantization range of the three colors R, G, and B is [0, 255];

[0091] S2. Preprocessing the OLED display brightness data in the sample set to obtain preprocessed OLED display brightness data and establishing a brightness adjustment relationship model;

[0092] Preprocessing the OLED display brightness data collected from the sample set to obtain the preprocessed OLED display brightness data and establishing a brightness adjustment relationship model includes the following steps:

[0093] S21, filtering the OLED display brightness data collected in the sample set to obtain filtered OLED display brightness data;

[0094] Setting a one-to-one correspondence between the user input brightness data and the display brightness data in the OLED display brightness data; when the user input brightness data or the display brightness data in the OLED display brightness data is missing, deleting the missing user input brightness data or the display brightness data, and deleting the user input brightness data or the display brightness data corresponding to the missing data to achieve filtering; the remaining OLED display brightness data in the sample set is the filtered OLED display brightness data;

[0095] S22, sorting the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model;

[0096] Arrange the filtered OLED display brightness data in descending order, and determine the grayscale level of the current OLED display based on the number of bits of the current processor. When the processor is 8 bits, the grayscale level of the corresponding OLED display is 2 to the power of 8, which is 256 levels of grayscale;

[0097] For a 64-level grayscale OLED display, the number of bits required to convert the brightness of each color in the display brightness data into binary brightness data is 6 bits;

[0098] The brightness adjustment algorithm formula is as follows:

[0099] Y=K×X

[0100] Where Y is the output 6-bit binary brightness data, which represents the desired brightness value after adjustment; X is the input 6-bit binary brightness data; and K is the user input brightness data.

[0101] A brightness adjustment relationship model is constructed based on the brightness adjustment algorithm. The brightness adjustment relationship model formula is as follows:

[0102] L=L min +(L max -L min )×(Y / 255) 2

[0103] Among them, L represents the actual brightness value achieved after adjustment, L max Indicates the maximum brightness, L min Indicates minimum brightness;

[0104] S3. Based on the established brightness adjustment relationship model and contrast adjustment algorithm, establish a contrast and brightness combination adjustment model;

[0105] Based on the established brightness adjustment relationship model and contrast adjustment algorithm, establishing a contrast and brightness combination adjustment model includes the following steps:

[0106] For a 64-level grayscale OLED display, the contrast adjustment algorithm formula is as follows:

[0107] D=64(X÷64) γ

[0108] Where X is the input 6-bit binary brightness data, D is the output 6-bit binary brightness data, which represents the desired contrast value after adjustment. The contrast value represents the ratio of the maximum brightness to the minimum brightness of the OLED display, and γ is the contrast adjustment variable.

[0109] The contrast and brightness combination adjustment model is as follows:

[0110] Q=K(L÷64) γ

[0111] Where Q is the 6-bit binary brightness data output after contrast and brightness combination adjustment, indicating the desired contrast and brightness combination adjustment value after adjustment; K is the user input brightness data; γ is the contrast adjustment variable; and L represents the actual brightness value achieved after adjustment.

[0112] S4, based on the collected OLED display brightness data and contrast data under the condition of constant brightness, the contrast and brightness combination adjustment model is processed by genetic algorithm, and the optimal contrast and brightness combination adjustment model is obtained;

[0113] Based on the collected OLED display brightness data and contrast data under the condition of constant brightness, the contrast and brightness combination adjustment model is processed by genetic algorithm, which includes the following steps:

[0114] S41, randomly select the preprocessed OLED display brightness data and contrast data, select N processed brightness data and contrast data and sequentially number, obtain chromosome code, and the chromosome code set is:

[0115] {1(225,225,225,400:1),2(200,200,225,400:1),...,N(255,255,255,600:1)}

[0116] Wherein, 1 represents the chromosome code of the processed brightness data and contrast data with number 1, N represents the chromosome code of the processed brightness data and contrast data with number N, 225, 225, 225 represent the brightness quantization value of R, G, B three colors respectively, 400:1 represents the contrast value under the current brightness, 200, 200, 225 represent the brightness quantization value of R, G, B three colors respectively, 255, 255, 255 represent the brightness quantization value of R, G, B three colors respectively, 600:1 represents the contrast value under the current brightness;

[0117] S42, population initialization;

[0118] Select 4 chromosome codes from the N processed brightness data and contrast data with completed numbering to generate an initial population;

[0119] Further, sort the data in the generated initial population according to the number;

[0120] Further, by setting the contrast adjustment variable initial value in the contrast and brightness combination adjustment model, the data in the sorted initial population is adjusted based on the contrast and brightness combination adjustment model with the set contrast adjustment variable initial value, to obtain the data after contrast and brightness combination adjustment;

[0121] S43, establish fitness function;

[0122] During the process of adjusting the data in the sorted initial population by the contrast and brightness combination adjustment model, when the user is satisfied with the brightness of the OLED display after the current contrast and brightness combination adjustment, the fitness value of the contrast and brightness combination adjustment is determined by the user touching the OLED display;

[0123] When the contrast and brightness combination adjustment model is cyclically adjusting the data in the sorted initial population, if the user does not touch the OLED display to determine the fitness value after the contrast and brightness combination adjustment, a new population is selected and processed by the genetic algorithm;

[0124] Further, recording the fitness value after the determined contrast and brightness combination adjustment, and setting the fitness value after the determined contrast and brightness combination adjustment as a genetic operator;

[0125] Constructing a fitness function based on the determined fitness value after adjusting the contrast and brightness combination;

[0126] The fitness function is set as follows:

[0127]

[0128] Among them, Fix(i) represents the fitness of the contrast and brightness of the i-th group in the initialization population, Q i Represents the contrast and brightness combination adjustment value of the initialization population i-th group contrast and brightness in the fitness function;

[0129] S44, genetic operator selection operation;

[0130] By randomly selecting the genetic operator in a roulette wheel manner, the probability of each contrast and brightness group being selected is proportional to the fitness, and the contrast and brightness with the highest fitness are selected;

[0131] The probability formula for the genetic operator to be selected is as follows:

[0132]

[0133] Where I represents the population size, Fix(i) represents the fitness of the i-th contrast and brightness group in the initialization population, and p(i) represents the probability that the i-th contrast and brightness group in the initialization population is selected;

[0134] S45, chromosome crossover operation;

[0135] The chromosome codes of the selected genetic operators are copied to generate offspring populations, the chromosome codes in the generated offspring populations are randomly paired, and crossover points are randomly selected. The genetic operators in the generated offspring populations are cross-propagated by sequential crossover to generate a new pair of chromosome codes.

[0136] Furthermore, the generated new chromosome codes are also used as data to participate in the iteration;

[0137] S46, iteratively executing steps S42-S45 until the contrast adjustment variable converges, and outputting the optimal individual under each brightness group;

[0138] Furthermore, the converged contrast adjustment variable is used as the contrast adjustment variable in the calculation of the current contrast and brightness combination adjustment model, thereby obtaining the optimal contrast and brightness combination adjustment model;

[0139] S5. Combining and adjusting the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combination adjustment model;

[0140] The combined adjustment of the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combined adjustment model includes:

[0141] By inputting the user input brightness data into the obtained optimal contrast and brightness combination adjustment model, the optimal contrast and brightness combination adjustment model adjusts the display brightness and contrast based on the user input brightness data;

[0142] The present invention discloses an artificial intelligence-based OLED display brightness and contrast combination adjustment system, comprising: a data collection module, a database, a brightness and contrast combination adjustment module, an adjustment optimization module, and a display module;

[0143] The data collection module is used to collect brightness data of the OLED display and contrast data when the brightness remains unchanged;

[0144] The database is used to store the brightness data of the OLED display and the contrast data when the brightness remains unchanged collected by the data collection module;

[0145] The brightness and contrast combination adjustment module is used to establish a contrast and brightness combination adjustment model through a brightness adjustment algorithm and a contrast adjustment algorithm;

[0146] The adjustment optimization module is used to optimize the established contrast and brightness combination adjustment model through a genetic algorithm;

[0147] The display module is used to display the brightness data and contrast data adjusted by the contrast and brightness combination adjustment model.

[0148] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for adjusting brightness and contrast of an OLED display based on artificial intelligence, characterized in that: The following steps are involved: S1. Collecting brightness data of the OLED display and contrast data when the brightness remains unchanged, and constructing a sample set based on the collected brightness data of the OLED display and contrast data when the brightness remains unchanged; The OLED display brightness data includes: user input brightness data and display brightness data; The user inputs brightness data in the range of [0%, 100%], and the display brightness data is represented by the brightness quantization of the three colors R, G, and B, and the brightness quantization range of the three colors R, G, and B is [0, 255]; S2. Preprocessing the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establishing a brightness adjustment relationship model; S3. Based on the established brightness adjustment relationship model and contrast adjustment algorithm, establish a contrast and brightness combination adjustment model; S4. Based on the collected OLED display brightness data and the contrast data when the brightness remains unchanged, the contrast and brightness combination adjustment model is processed by a genetic algorithm to obtain an optimal contrast and brightness combination adjustment model; S5. Combining and adjusting the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combination adjustment model; The combined adjustment of the brightness and contrast of the OLED display based on the obtained optimal contrast and brightness combined adjustment model includes: By inputting the user input brightness data into the obtained optimal contrast and brightness combination adjustment model, the optimal contrast and brightness combination adjustment model adjusts the display brightness and contrast based on the user input brightness data.

2. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 1, wherein: The preprocessing of the OLED display brightness data in the sample set to obtain the preprocessed OLED display brightness data and establishing a brightness adjustment relationship model comprises the following steps: S21, filtering the OLED display brightness data in the sample set to obtain filtered OLED display brightness data; Setting a one-to-one correspondence between the user input brightness data and the display brightness data in the OLED display brightness data; when the user input brightness data or the display brightness data in the OLED display brightness data is missing, deleting the missing user input brightness data or the display brightness data, and deleting the user input brightness data or the display brightness data corresponding to the missing data to achieve filtering; the remaining OLED display brightness data in the sample set is the filtered OLED display brightness data; S22 , sorting the filtered OLED display brightness data to obtain pre-processed OLED display brightness data and establishing a brightness adjustment relationship model.

3. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 2, wherein: The filtering and collating of the OLED display brightness data to obtain the pre-processed OLED display brightness data and establishing the brightness adjustment relationship model comprises the following steps: Arrange the filtered OLED display brightness data in descending order, and determine the grayscale level of the current OLED display based on the number of bits of the current processor. When the processor is 8 bits, the grayscale level of the corresponding OLED display is 2 to the power of 8, which is 256 levels of grayscale; For a 64-level grayscale OLED display, the number of bits required to convert the brightness of each color in the display brightness data into binary brightness data is 6 bits; The brightness adjustment algorithm formula is as follows: Y=K×X Where Y is the output 6-bit binary brightness data, which represents the desired brightness value after adjustment; X is the input 6-bit binary brightness data; and K is the user input brightness data. A brightness adjustment relationship model is constructed based on the brightness adjustment algorithm. The brightness adjustment relationship model formula is as follows: L=L min +(L max -L min )×(Y / 255) 2 Among them, L represents the actual brightness value achieved after adjustment, L max Indicates the maximum brightness, L min Indicates minimum brightness.

4. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 1, wherein: The step of establishing a contrast and brightness combination adjustment model based on the established brightness adjustment relationship model and contrast adjustment algorithm includes the following steps: For a 64-level grayscale OLED display, the contrast adjustment algorithm formula is as follows: D=64(X÷64) γ Where X is the input 6-bit binary brightness data, D is the output 6-bit binary brightness data, which represents the desired contrast value after adjustment. The contrast value represents the ratio of the maximum brightness to the minimum brightness of the OLED display, and γ is the contrast adjustment variable. The contrast and brightness combination adjustment model is as follows: Q=K(L÷64) γ Where Q is the 6-bit binary brightness data output after contrast and brightness combination adjustment, indicating the desired contrast and brightness combination adjustment value after adjustment. K is the user input brightness data, γ is the contrast adjustment variable, and L represents the actual brightness value achieved after adjustment.

5. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 1, wherein: The method of processing the contrast and brightness combination adjustment model by a genetic algorithm based on the collected OLED display brightness data and the contrast data under the condition of constant brightness includes the following steps: S41. Randomly select the pre-processed brightness data and contrast data of the OLED display, select N processed brightness data and contrast data and number them in sequence to obtain chromosome codes. The chromosome code set is: {1(225,225,225,400:1),2(200,200,225,400:1),...,N(255,255,255,600:1)} Among them, 1 represents the chromosome code of the brightness data and contrast data after processing numbered 1, N represents the chromosome code of the brightness data and contrast data after processing numbered N, 225, 225, 225 represent the brightness quantization values ​​of R, G, and B respectively, 400:1 represents the contrast value at the current brightness, 200, 200, 225 represent the brightness quantization values ​​of R, G, and B respectively, 255, 255, 255 represent the brightness quantization values ​​of R, G, and B respectively, and 600:1 represents the contrast value at the current brightness; S42, initializing the population; S43, establishing a fitness function; S44, genetic operator selection operation; S45, chromosome crossover operation; S46, iteratively executing steps S42-S45 until the contrast adjustment variable converges; The converged contrast adjustment variable is used as the contrast adjustment variable in the calculation of the current contrast and brightness combination adjustment model, thereby obtaining the optimal contrast and brightness combination adjustment model.

6. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, wherein: The population initialization comprises the following steps: Select 4 chromosome codes from the N processed brightness data and contrast data to generate an initial population; Sort the data in the generated initial population by number; An initial value of a contrast adjustment variable in a contrast and brightness combination adjustment model is set, and data in the sorted initial population is adjusted based on the contrast and brightness combination adjustment model with the set initial value of the contrast adjustment variable to obtain data after contrast and brightness combination adjustment.

7. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, wherein: The establishment of the fitness function comprises the following steps: During the process of adjusting the data in the sorted initial population by the contrast and brightness combination adjustment model, when the user is satisfied with the brightness of the OLED display after the current contrast and brightness combination adjustment, the fitness value of the contrast and brightness combination adjustment is determined by the user touching the OLED display; When the contrast and brightness combination adjustment model is adjusting the data in the sorted initial population, if the user does not touch the OLED display to determine the fitness value after the contrast and brightness combination adjustment, a new population is generated and processed by the genetic algorithm; Recording the fitness value after the determined contrast and brightness combination is adjusted, and setting the fitness value after the determined contrast and brightness combination is adjusted as a genetic operator; Constructing a fitness function based on the determined fitness value after adjusting the contrast and brightness combination; The fitness function is set as follows: Among them, Fix(i) represents the fitness of the contrast and brightness of the i-th group in the initialization population, Q i Represents the contrast and brightness combination adjustment value of the i-th contrast and brightness group of the initialized population in the fitness function.

8. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, wherein: The genetic operator selection operation includes the following steps: By randomly selecting the genetic operator in a roulette wheel manner, the probability of each contrast and brightness group being selected is proportional to the fitness, and the contrast and brightness with the highest fitness are selected; The probability formula for the genetic operator to be selected is as follows: Where I represents the population size, Fix(i) represents the fitness of the i-th contrast and brightness group in the initialization population, and p(i) represents the probability that the i-th contrast and brightness group in the initialization population is selected.

9. The method for adjusting brightness and contrast of an OLED display based on artificial intelligence according to claim 5, wherein: The chromosome crossover operation comprises the following steps: The chromosome codes of the selected genetic operators are copied to generate offspring populations, the chromosome codes in the generated offspring populations are randomly paired, and crossover points are randomly selected. The genetic operators in the offspring populations are cross-propagated by sequential crossover to generate a new pair of chromosome codes. The newly generated chromosome codes are also used as data to participate in the iteration.

10. A system for implementing the artificial intelligence-based OLED display brightness and contrast combination adjustment method according to any one of claims 1 to 9, characterized in that: include: Data collection module, database, brightness and contrast combination adjustment module, adjustment optimization module and display module; The data collection module is used to collect brightness data of the OLED display and contrast data when the brightness remains unchanged; The database is used to store the brightness data of the OLED display and the contrast data when the brightness remains unchanged collected by the data collection module; The brightness and contrast combination adjustment module is used to establish a contrast and brightness combination adjustment model through a brightness adjustment algorithm and a contrast adjustment algorithm; The adjustment optimization module is used to optimize the established contrast and brightness combination adjustment model through a genetic algorithm; The display module is used to display the brightness data and contrast data adjusted by the contrast and brightness combination adjustment model.

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