Display screen control method and device of smart watch, equipment and storage medium

Abstract

The invention relates to the technical field of data processing, and provides a display screen control method and device of a smart watch, equipment and a storage medium, and the method comprises the steps: carrying out the real-time detection of a current state of a display screen of the smart watch, obtaining a brightness parameter, a color temperature parameter and display content distribution information of the display screen, carrying out the analysis and adjustment, and obtaining a brightness value of the display screen; obtaining a partition display output and a pre-display interface; and analyzing and processing the partition display output and the pre-display interface, generating an optimization parameter group, and controlling the smart watch based on the optimization parameter group. The intelligent watch is controlled after the brightness parameter, the color temperature parameter and the display content distribution information of the display screen are detected, analyzed and adjusted to generate the optimized parameter group, so that the intelligent watch can provide the optimal display effect in different use scenes, and the problem that the display effect is poor when the screen display content is complex and fine display is needed is solved. A traditional brightness and color temperature control method is difficult to achieve an ideal effect, and the problem of non-uniform display effect exists.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and more particularly to a display screen control method, device, equipment and storage medium for a smart watch. Background Art

[0002] With the rapid development of science and technology, the smart wearable device market has gradually emerged, and smart watches have become one of the most popular products. Smart watches can not only provide basic functions such as time display and daily activity recording, but also realize health monitoring, message reminders, navigation and other functions. Its portability and versatility meet consumers' needs for convenient life and promote the rapid development of the smart watch industry.

[0003] In the prior art, the display screen control of smart watches is mainly achieved through brightness sensors and color temperature sensors. The brightness sensor detects changes in ambient light and adjusts the brightness of the display screen according to the light intensity to ensure clear display in different lighting environments. The color temperature sensor can adjust the color temperature of the display screen so that the screen display effect is more in line with the visual comfort of the human body. This control method realizes the adaptive display of smart watches in different environments and improves the user experience.

[0004] Regarding the above technical solution, although the brightness and color temperature of the display screen can be adjusted through the brightness sensor and the color temperature sensor to adapt to different ambient lighting conditions, when the screen display content is complex and requires fine display, the traditional brightness and color temperature control method is difficult to achieve the ideal effect, and there is a problem of uneven display effect. Summary of the invention

[0005] In order to improve the problem that traditional brightness and color temperature control methods are difficult to achieve ideal results and have uneven display effects when the screen display content is complex and requires fine display, the present application provides a display screen control method, device, equipment and storage medium for a smart watch.

[0006] The present invention provides a display screen control method for a smart watch, comprising: performing real-time detection on a current state of a display screen of the smart watch to obtain brightness parameters, color temperature parameters and display content distribution information of the display screen; adjusting a backlight module of the display screen based on the brightness parameters and the color temperature parameters to obtain a full-screen brightness control signal and a full-screen color temperature control signal; inputting the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjusting pixel partitions of the display screen to obtain partition brightness distribution information, and performing detailed adjustment on each pixel of the display screen using the partition brightness distribution information and the display content distribution information to obtain a pixel driving signal; performing partition driving on the display screen based on the pixel driving signal to obtain a partition display output, and preferentially adjusting an interactive area of ​​the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface; analyzing and processing the partition display output and the pre-display interface to generate an optimization parameter group, and controlling the smart watch based on the optimization parameter group.

[0007] As a preferred solution, the step of performing real-time detection on the current state of the display screen of the smart watch to obtain the brightness parameter, color temperature parameter and display content distribution information of the display screen includes: collecting ambient light intensity and color temperature information around the display screen through a photodiode sensor module to obtain ambient brightness parameter and ambient color temperature parameter, applying a Gaussian filter algorithm to perform denoising on the ambient brightness parameter and the ambient color temperature parameter to obtain ambient light correction parameter; inputting the ambient light correction parameter and the luminous intensity and RGB color output information of the display screen into a preset multi-layer perceptron model to obtain the brightness parameter and color temperature parameter of the display screen; dividing the display content of the display screen into regions to obtain initial display content distribution information and initial partition feature parameters; performing partition refinement processing on the initial display content distribution information using a watershed segmentation algorithm based on grayscale gradient to obtain refined brightness distribution information, and performing fitting processing on the refined brightness distribution information and the initial partition feature parameters to obtain brightness distribution information; generating screen state feature parameters and regional display features according to the brightness distribution information, and extracting main features of the screen state feature parameters and the regional display features using a principal component analysis method to obtain display content distribution information.

[0008] As a preferred solution, the step of adjusting the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal includes: parsing the brightness parameter and the color temperature parameter by a Kalman filter algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, performing partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain a brightness correction parameter and a color temperature correction parameter of each display partition; adjusting the light-emitting unit of the backlight module of the display screen region by region by pulse width modulation technology according to the brightness correction parameter to obtain a regional brightness control signal; applying a proportional integral differential control algorithm to refine the color temperature adjustment unit of the backlight module of the display screen according to the color temperature correction parameter to obtain a regional color temperature control signal; and performing weighted averaging processing on the regional brightness control signal and the regional color temperature control signal to generate a full-screen brightness control signal and a full-screen color temperature control signal.

[0009] As a preferred solution, the step of parsing the brightness parameter and the color temperature parameter by a Kalman filter algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and performing partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain a brightness correction parameter and a color temperature correction parameter of each display partition includes: performing time series parsing on the brightness parameter by a Kalman filter algorithm to obtain a brightness trend prediction value and a brightness residual, performing moving average filtering processing on the brightness trend prediction value to obtain a brightness reference value, performing fast Fourier transform on the brightness residual to obtain a brightness frequency domain characteristic parameter; based on the brightness reference value and the brightness frequency domain characteristic parameter, performing a segmented regression calculation by a least squares polynomial fitting method to obtain an initial brightness adjustment value and a brightness offset correction value, and converting the initial brightness adjustment value into a brightness reference value. The integer value is weighted and synthesized with the brightness offset correction value to obtain a target brightness adjustment value; the color temperature parameter is recursively analyzed by using a Kalman filter algorithm to obtain a color temperature trend prediction value and a color temperature dynamic change parameter, the color temperature trend prediction value is subjected to wavelet transform analysis to obtain a multi-resolution color temperature detail parameter, the significance weight of the color temperature dynamic change parameter is calculated by an entropy weight method, and a color temperature change significance parameter is generated; the multi-resolution color temperature detail parameter and the color temperature change significance parameter are weighted based on a local weighted regression method to generate a target color temperature adjustment value; the target brightness adjustment value is fitted partition by partition by a weighted linear regression calculation method of regional partitions to obtain a brightness correction parameter for each display partition; the target color temperature adjustment value is refined partition by partition based on a regression model of a support vector machine to generate a color temperature correction parameter for each display partition.

[0010] As a preferred solution, the step of inputting the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjusting the pixel partitions of the display screen to obtain partition brightness distribution information, and using the partition brightness distribution information and the display content distribution information to refine and adjust each pixel of the display screen to obtain a pixel driving signal includes: resampling the full-screen brightness control signal and the full-screen color temperature control signal using a bilinear interpolation algorithm, adjusting the initial brightness distribution of the pixels of each display partition, and obtaining adjusted partition brightness distribution information; cross-analyzing the adjusted partition brightness distribution information and the display content distribution information using a cosine similarity calculation method to obtain pixel feature parameters; refining the pixel feature parameters based on a bilateral filtering algorithm to obtain a pixel brightness control signal and a pixel color temperature control signal for each pixel; and fusing the pixel brightness control signal and the pixel color temperature control signal using a homography matrix transformation algorithm to obtain a pixel driving signal.

[0011] As a preferred solution, the step of partitioning the display screen based on the pixel drive signal to obtain a partitioned display output, and preferentially adjusting the interactive area of ​​the display screen according to the display content distribution information and the user interaction data to obtain a pre-display interface includes: partitioning the pixel drive signal through a Voronoi diagram generation algorithm to generate a partitioned drive signal, and using the partitioned drive signal to independently drive each partition of the display screen to obtain a partitioned display output; using a support vector machine to classify the partitioned display output and the display content distribution information to obtain a display priority for each area, and using an entropy weight method to weight the display priority and the user interaction data to identify an interactive priority area; wherein the user interaction data includes any one of the following: touch interaction data, gesture interaction data, and voice input data; using a linear interpolation method to preferentially adjust the display parameters of the interactive priority area to obtain an enhanced interactive partitioned display output; and performing weighted linear fusion processing on the partitioned display output and the enhanced interactive partitioned display output to generate a pre-display interface.

[0012] As a preferred scheme, the steps of analyzing and processing the partition display output and the pre-display interface to generate an optimization parameter group, and controlling the smart watch based on the optimization parameter group include: using a convolutional neural network to extract features of the partition display output and the pre-display interface to obtain interface feature parameters and partition display output characteristic data, and fusing the interface feature parameters and the partition display output characteristic data by using linear discriminant analysis to generate an optimization parameter group; parsing the optimization parameter group to generate screen refresh rate adjustment parameters, touch response adjustment parameters and display content arrangement parameters; according to the screen refresh rate adjustment parameters, applying a servo control algorithm to dynamically adjust the display refresh rate; according to the touch response adjustment parameters, applying a generalized predictive control algorithm to adjust the touch module; according to the display content arrangement parameters, optimizing the layout and arrangement of the display screen content of the smart watch.

[0013] The present application also provides a display screen control device for a smart watch, comprising: a detection module, used to perform real-time detection on the current state of the display screen of the smart watch, and obtain brightness parameters, color temperature parameters and display content distribution information of the display screen; an adjustment module, used to adjust the backlight module of the display screen based on the brightness parameters and the color temperature parameters, and obtain a full-screen brightness control signal and a full-screen color temperature control signal; a regulation module, used to input the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjust the pixel partitions of the display screen, and obtain partition brightness distribution information, and use the partition brightness distribution information and the display content distribution information to perform detailed adjustment on each pixel of the display screen to obtain a pixel driving signal; a driving module, used to drive the display screen in partitions based on the pixel driving signal, obtain a partition display output, and preferentially adjust the interactive area of ​​the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface; a control module, used to analyze and process the partition display output and the pre-display interface, generate an optimization parameter group, and control the smart watch based on the optimization parameter group.

[0014] The present application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the display screen control method of the smart watch described in any one of the above is implemented.

[0015] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor executes the display screen control method of a smart watch as described in any one of the above.

[0016] Compared with the prior art, the present application has the following beneficial effects: high flexibility and uniform display effect. By real-time detection of the brightness parameters, color temperature parameters and display content distribution information of the display screen, the current state of the display screen can be accurately obtained; based on the brightness parameters and color temperature parameters, the backlight module of the display screen is adjusted to achieve automatic adjustment of the full-screen brightness and color temperature; through the preset display adjustment module, the pixel partitions of the display screen are dynamically adjusted, and each pixel can be independently and finely adjusted to ensure the uniformity of the display effect; based on the pixel drive signal, the partition drive can be used to preferentially adjust the display effect of the interactive area according to the display content distribution information and user interaction data, thereby improving the user experience; by analyzing and processing the partition display output and the pre-display interface, an optimized parameter group is generated, and the display effect is optimized based on the optimized parameter group, so that the smart watch can provide the best display effect and user experience in different usage scenarios, and improve the problem that when the screen display content is complex and requires fine display, the traditional brightness and color temperature control method is difficult to achieve the ideal effect, and there is an uneven display effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0018] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0019] Figure 1 is a flow chart of a display screen control method of a smart watch provided by an embodiment of the present invention; Figure 2 is a schematic block diagram of the structure of a display screen control device for a smart watch provided by an embodiment of the present invention; Figure 3 It is a schematic block diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0020] Description of reference numerals: 10. Display screen control device of smart watch; 11. Detection module; 12. Adjustment module; 13. Regulation module; 14. Drive module; 15. Control module; 20. Electronic device; 21. Memory; 22. Processor. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0023] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0024] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0026] Embodiment 1: like Figure 1 As shown, Example 1: The present application provides a display screen control method for a smart watch, comprising steps S100 to S500.

[0027] Step S100: Detect the current state of the display screen of the smart watch in real time to obtain brightness parameters, color temperature parameters and display content distribution information of the display screen.

[0028] In this step, the current state of the display screen is detected in real time through the sensor module, which includes a brightness sensor, a color temperature sensor and an image sensor; specifically, the brightness sensor is used to detect the brightness of the ambient light, the color temperature sensor is used to detect the color temperature of the ambient light, and the image sensor is used to obtain the distribution information of the content displayed on the display screen.

[0029] For example, when a user uses a smart watch in an outdoor environment with strong light, the brightness sensor detects a higher ambient brightness parameter, the color temperature sensor detects changes in the color temperature parameter, and the image sensor obtains the distribution information of the currently displayed content.

[0030] Step S200: Based on the brightness parameter and the color temperature parameter, the backlight module of the display screen is adjusted to obtain a full-screen brightness control signal and a full-screen color temperature control signal.

[0031] In this step, the backlight module of the display screen is adjusted by the control module, and the control module generates a full-screen brightness control signal and a full-screen color temperature control signal according to the brightness parameters and the color temperature parameters; specifically, the control module adjusts the brightness of the backlight module according to the brightness parameters, and adjusts the color temperature of the backlight module according to the color temperature parameters, so that the display screen adapts to the current ambient lighting conditions.

[0032] For example, when the ambient brightness is high, the control module will generate a stronger full-screen brightness control signal to increase the brightness of the display screen so that the user can still clearly see the screen content in a strong light environment; at the same time, the color temperature control signal will adjust the color temperature of the backlight module to make the display effect more comfortable.

[0033] Step S300: input the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjust the pixel partitions of the display screen, obtain partition brightness distribution information, and use the partition brightness distribution information and display content distribution information to refine each pixel of the display screen to obtain a pixel drive signal.

[0034] In this step, the pixel partitions of the display screen are dynamically adjusted through the display adjustment module, and the display adjustment module refines the brightness and color temperature of each pixel partition according to the full-screen brightness control signal and the full-screen color temperature control signal; specifically, the display adjustment module divides the screen into multiple pixel partitions, and independently adjusts the brightness and color temperature of each pixel partition according to the partition brightness distribution information and the display content distribution information, and generates a corresponding pixel drive signal.

[0035] For example, when the display content distribution information shows that the left half of the screen is mainly a dark image, and the right half is mainly a light image, the display adjustment module will reduce the brightness of the pixel partition in the left half and increase the brightness of the pixel partition in the right half according to the partition brightness distribution information to ensure the uniformity of the overall display effect.

[0036] Step S400: drive the display screen in partitions based on the pixel driving signal to obtain partition display output, and preferentially adjust the interactive area of ​​the display screen according to the display content distribution information and the user interaction data to obtain a pre-display interface.

[0037] In this step, the display screen is partition-driven by a partition driving module, and the partition driving module drives each pixel partition according to a pixel driving signal; specifically, the partition driving module divides the display screen into multiple areas, independently adjusts the brightness and color temperature of each area, and based on the display content distribution information and user interaction data, preferentially adjusts the display effect of the user interaction area to generate a pre-display interface.

[0038] For example, when a user interacts with a certain area of ​​the display screen, the partition driver module will give priority to increasing the brightness and color temperature of the interactive area to ensure that the user can clearly see the screen content during the interaction, thereby improving the user experience.

[0039] Step S500: Analyze and process the partition display output and the pre-display interface to generate an optimized parameter group, and control the smart watch based on the optimized parameter group.

[0040] In this step, the partition display output and the pre-display interface are analyzed and processed by the analysis module, and the analysis module generates an optimization parameter group according to the feedback information of the display effect; specifically, the analysis module comprehensively analyzes the partition display output of the display screen, and evaluates the display effect in combination with the user interaction data, and generates an optimization parameter group including brightness adjustment, color temperature adjustment, etc.

[0041] For example, when a user reports that the display effect of a certain area is not ideal, the analysis module will adjust the partition display output based on the feedback information and generate an optimized parameter group to improve the overall display effect of the display screen.

[0042] In this embodiment, the current state of the display screen of the smart watch is detected in real time to obtain the brightness parameter, color temperature parameter and display content distribution information of the display screen; then, based on the brightness parameter and color temperature parameter, the backlight module of the display screen is adjusted to generate a full-screen brightness control signal and a full-screen color temperature control signal; these signals are input into a preset display adjustment module to dynamically adjust the pixel partitions of the display screen to obtain partition brightness distribution information; using the partition brightness distribution information and display content distribution information, each pixel of the display screen is finely adjusted to generate a pixel driving signal; finally, based on the pixel driving signal, the display screen is partitioned and driven to obtain a partition display output, and according to the display content distribution information and user interaction data, the interactive area of ​​the display screen is preferentially adjusted to generate a pre-display interface, and finally, by analyzing and processing the partition display output and the pre-display interface, an optimized parameter group is generated to control the smart watch. Refined adjustment of the display screen of the smart watch is achieved to improve the uniformity and clarity of the display effect. This method can not only automatically adjust the brightness and color temperature according to the ambient light conditions, but also perform partition driving according to the display content and user interaction data, so that the display screen can provide the best display effect and user experience in different usage scenarios. In addition, this method can also optimize the display effect of the interactive area, improving the user's operational convenience and visual comfort.

[0043] Embodiment 2: In step S100, the ambient light intensity and color temperature information around the display screen is collected by a photodiode sensor module to obtain ambient brightness parameters and ambient color temperature parameters, and a Gaussian filter algorithm is applied to denoise the ambient brightness parameters and ambient color temperature parameters to obtain ambient light correction parameters.

[0044] The photodiode sensor module is used to monitor the ambient light intensity and color temperature information around the display screen in real time, and collect ambient brightness parameters and ambient color temperature parameters; specifically, the photodiode in the photodiode sensor module detects the intensity and color temperature of the ambient light, and transmits the detection data to the signal processing module; the signal processing module uses a Gaussian filtering algorithm to denoise the collected ambient brightness parameters and ambient color temperature parameters to obtain stable and accurate ambient light correction parameters.

[0045] For example, when a user goes from indoors to outdoors, the photodiode sensor module detects a significant change in ambient light intensity and uses a Gaussian filtering algorithm to remove noise from the ambient light signal to ensure the accuracy of the ambient light correction parameters.

[0046] The ambient light correction parameters, the luminous intensity of the display screen, and the RGB color output information are input into a preset multi-layer perceptron model to obtain the brightness parameters and color temperature parameters of the display screen.

[0047] The ambient light correction parameters, the luminous intensity and the RGB color output information of the display screen are comprehensively processed through a preset multi-layer perceptron model; specifically, the ambient light correction parameters, the luminous intensity and the RGB color output information are first normalized and then input into the multi-layer perceptron model; the multi-layer perceptron model performs nonlinear mapping on the input information through a training learning algorithm, and outputs the brightness parameters and color temperature parameters of the display screen.

[0048] For example, when the ambient light intensity is high and the luminous intensity of the display screen is low, the multi-layer perceptron model will calculate the result that the display screen brightness parameters need to be increased, thereby improving the display effect.

[0049] The display content of the display screen is divided into regions to obtain initial display content distribution information and initial partition characteristic parameters. The initial display content distribution information is partitioned and refined using a grayscale gradient-based watershed segmentation algorithm to obtain refined brightness distribution information of each display region. The refined brightness distribution information is fitted with the initial partition characteristic parameters to obtain brightness distribution information of each display region.

[0050] The display content is divided into regions by the K-means clustering algorithm. Specifically, the display content is firstly gray-processed, and then the K-means clustering algorithm is applied to perform cluster analysis on the processed image to obtain initial display content distribution information and initial partition feature parameters. Then, the initial display content distribution information is partitioned and refined by the grayscale gradient-based watershed segmentation algorithm to obtain refined brightness distribution information of each display region. Finally, the weighted least squares method is applied to fit the refined brightness distribution information with the initial partition feature parameters to obtain brightness distribution information of each display region.

[0051] For example, when the displayed content includes text, images, and videos, similar content is clustered in the same area using the K-means clustering algorithm, and then the watershed segmentation algorithm is used to further refine the area boundaries. Finally, the brightness distribution information of each area is calculated using the weighted least squares method.

[0052] Screen state characteristic parameters and regional display characteristics are generated according to the brightness distribution information.

[0053] The brightness and color temperature states of the display screen are dynamically detected through a dynamic time warping algorithm. Specifically, the brightness and color temperature changes of the display screen are monitored in real time based on the brightness distribution information, and the monitoring data is input into the dynamic time warping algorithm. The algorithm extracts the screen state characteristic parameters and regional display characteristics by analyzing the time series change trends of brightness and color temperature.

[0054] For example, when the display screen switches from day mode to night mode, the dynamic time warping algorithm can detect the changing trends of brightness and color temperature and generate corresponding screen state characteristic parameters.

[0055] The principal component analysis method is used to extract the main features of the screen state characteristic parameters and regional display features to obtain the display content distribution information.

[0056] The main features of the screen state characteristic parameters and regional display features are extracted through principal component analysis. Specifically, the screen state characteristic parameters and regional display features are input into the principal component analysis model, and the model performs dimensionality reduction processing on the input data, extracts the main characteristic variables, and obtains the optimized display content distribution information.

[0057] For example, the principal component analysis method can extract the brightness and color temperature features that have the greatest impact on the display effect from the screen state characteristic parameters, and generate simplified display content distribution information.

[0058] In step S200, the brightness parameters and color temperature parameters are analyzed by the Kalman filter algorithm to obtain the target brightness adjustment value and the target color temperature adjustment value, and the target brightness adjustment value and the target color temperature adjustment value are partition mapped using a preset linear regression model to obtain the brightness correction parameters and color temperature correction parameters of each display partition.

[0059] The brightness parameter and the color temperature parameter are analyzed by the Kalman filter algorithm to obtain the target brightness adjustment value and the target color temperature adjustment value; specifically, the Kalman filter algorithm is used to perform time series analysis on the brightness parameter to obtain the brightness trend prediction value and the brightness residual, the brightness trend prediction value is subjected to moving average filtering to obtain the brightness reference value, the brightness residual is subjected to fast Fourier transform to obtain the brightness frequency domain characteristic parameter; the color temperature parameter is then recursively analyzed by the Kalman filter algorithm to obtain the color temperature trend prediction value and the color temperature dynamic change parameter, the color temperature trend prediction value is subjected to wavelet transform analysis to obtain the multi-resolution color temperature detail parameter, the significance weight of the color temperature dynamic change parameter is calculated by the entropy weight method, and the color temperature change significance parameter is generated.

[0060] For example, for brightness parameters, the Kalman filter algorithm can be used to predict the brightness change trend in the future, and the periodic characteristics of brightness changes can be analyzed through frequency domain characteristic parameters; for color temperature parameters, the multi-scale characteristics of color temperature changes can be analyzed through wavelet transform, and the corresponding color temperature adjustment value can be generated.

[0061] According to the brightness correction parameters, the light-emitting units of the backlight module of the display screen are adjusted region by region through pulse width modulation technology to obtain a regional brightness control signal.

[0062] The light-emitting units of the backlight module of the display screen are adjusted region by region through pulse width modulation technology; specifically, the display screen is divided into multiple regions according to the brightness correction parameters, and the light-emitting units of each region are independently pulse-width modulated to generate regional brightness control signals to achieve precise control of the brightness of different regions.

[0063] For example, when the brightness correction parameter of a certain area is high, the pulse width modulation technology will increase the driving current of the light-emitting unit in the area to improve the brightness of the area; conversely, it will reduce the driving current and weaken the brightness of the area.

[0064] According to the color temperature correction parameters, the proportional integral differential control algorithm is applied to finely adjust the color temperature adjustment unit of the backlight module of the display screen to obtain a regional color temperature control signal.

[0065] The color temperature adjustment unit of the backlight module of the display screen is finely adjusted through the proportional-integral-differential control algorithm; specifically, according to the color temperature correction parameters, the proportional-integral-differential control algorithm is used to accurately control the working state of the color temperature adjustment unit to generate a regional color temperature control signal.

[0066] For example, when the color temperature of a certain area needs to be increased, the proportional integral derivative control algorithm will adjust the operating voltage of the color temperature adjustment unit to increase the color temperature of the area; otherwise, the color temperature will be reduced.

[0067] The regional brightness control signal and the regional color temperature control signal are respectively subjected to weighted average processing to generate a full-screen brightness control signal and a full-screen color temperature control signal.

[0068] The brightness control signal and color temperature control signal of each area are integrated through weighted averaging processing; specifically, the regional brightness control signal and the regional color temperature control signal are weighted averaged according to preset weights to generate a full-screen brightness control signal and a full-screen color temperature control signal to uniformly adjust the overall brightness and color temperature of the display screen.

[0069] For example, when the brightness control signal of most areas is high, the full-screen brightness control signal will also be correspondingly high; if the color temperature control signal of some areas is low, the full-screen color temperature control signal will be adjusted on an average.

[0070] Among them, the brightness parameters and color temperature parameters are analyzed by the Kalman filter algorithm to obtain the target brightness adjustment value and the target color temperature adjustment value, and the target brightness adjustment value and the target color temperature adjustment value are partition-mapped by using a preset linear regression model to obtain the brightness correction parameter and the color temperature correction parameter of each display partition. The steps include: using the Kalman filter algorithm to perform time series analysis on the brightness parameters to obtain the brightness trend prediction value and the brightness residual, performing moving average filtering on the brightness trend prediction value to obtain the brightness reference value, and performing fast Fourier transform on the brightness residual to obtain the brightness frequency domain characteristic parameter.

[0071] The Kalman filter algorithm is used to monitor the changes in brightness parameters in real time, and the brightness trend prediction value and brightness residual are extracted. Specifically, by analyzing the time series data of the brightness parameters, the brightness change trend in the future period is predicted, and the brightness residual is calculated. The short-term fluctuations are eliminated through moving average filtering to obtain a stable brightness reference value. The brightness residual is subjected to fast Fourier transform, the brightness frequency domain characteristic parameters are extracted, and the frequency characteristics of the brightness changes are analyzed.

[0072] For example, when the brightness of the display screen changes frequently and has periodic fluctuations, the Kalman filter algorithm can accurately extract the brightness trend prediction value, and identify the periodic characteristics of the brightness change through fast Fourier transform to generate brightness reference value and frequency domain characteristic parameters.

[0073] Based on the brightness reference value and the brightness frequency domain characteristic parameters, a piecewise regression calculation is performed using the least squares polynomial fitting method to obtain an initial brightness adjustment value and a brightness offset correction value. The initial brightness adjustment value and the brightness offset correction value are weighted and synthesized to obtain a target brightness adjustment value.

[0074] The brightness reference value and the brightness frequency domain characteristic parameters are subjected to segmented regression calculation by the polynomial fitting method of the least squares method; specifically, according to the brightness reference value and the brightness frequency domain characteristic parameters, the least squares method is applied to perform polynomial fitting on the brightness data to obtain the initial brightness adjustment value and the brightness offset correction value, which are weighted and synthesized to obtain the final target brightness adjustment value, so as to achieve precise control of the display screen brightness.

[0075] For example, when the brightness reference value of the display screen is low and the frequency domain characteristic parameter is high, the accuracy of brightness adjustment can be effectively improved by polynomial fitting using the least squares method, and an accurate target brightness adjustment value can be generated.

[0076] The Kalman filter algorithm is used to recursively analyze the color temperature parameters to obtain the color temperature trend prediction value and the color temperature dynamic change parameter. The color temperature trend prediction value is analyzed by wavelet transform to obtain the multi-resolution color temperature detail parameter. The significance weight of the color temperature dynamic change parameter is calculated by the entropy weight method to generate the color temperature change significance parameter.

[0077] The color temperature parameters are recursively parsed through the Kalman filter algorithm. Specifically, the time series data of the color temperature parameters are analyzed using the Kalman filter algorithm to extract the color temperature trend prediction value and the color temperature dynamic change parameters. Multi-resolution analysis is performed on the color temperature trend prediction value using wavelet transform to extract color temperature detail parameters of different scales. The significance weights of the color temperature dynamic change parameters are calculated using the entropy weight method to generate the color temperature change significance parameters for further adjusting the color temperature.

[0078] For example, when there are obvious multi-scale changes in color temperature parameters, the Kalman filter algorithm and wavelet transform can be used to accurately extract the detailed features of color temperature, and the entropy weight method can be used to calculate the significance weight to improve the accuracy of color temperature adjustment.

[0079] Based on the local weighted regression method, the multi-resolution color temperature detail parameters and the color temperature change significance parameters are weighted to generate the target color temperature adjustment value.

[0080] The multi-resolution color temperature detail parameters and the color temperature change significance parameters are weighted by a local weighted regression method; specifically, the multi-resolution color temperature detail parameters and the color temperature change significance parameters are input into a local weighted regression model, and different parameters are weighted to generate a target color temperature adjustment value to achieve precise control of the color temperature.

[0081] For example, when the color temperature detail parameters are complex and vary significantly, the local weighted regression method can be used to effectively weight different parameters and generate accurate target color temperature adjustment values.

[0082] Through the weighted linear regression calculation method of regional partitions, the target brightness adjustment value is fitted partition by partition to obtain the brightness correction parameters of each display partition; the target color temperature adjustment value is refined partition by partition based on the regression model of support vector machine to generate the color temperature correction parameters of each display partition.

[0083] The target brightness adjustment value and the target color temperature adjustment value are fitted and refined partition by partition through a preset linear regression model; specifically, the target brightness adjustment value and the target color temperature adjustment value are first input into the linear regression model, and a weighted linear regression calculation method is applied to perform fitting processing according to the characteristics of each display partition to obtain the brightness correction parameters of each display partition; at the same time, the target color temperature adjustment value is refined partition by partition based on the regression model of the support vector machine to generate the color temperature correction parameters of each display partition.

[0084] For example, when the brightness of some partitions of the display screen is higher and that of other partitions is lower, the linear regression model and the support vector machine regression model can effectively adjust the brightness and color temperature of each partition to make the overall display effect more uniform.

[0085] In step S300, a full-screen brightness control signal and a full-screen color temperature control signal are resampled using a bilinear interpolation algorithm to adjust the initial brightness distribution of pixels in each display partition to obtain adjusted partition brightness distribution information.

[0086] The full-screen brightness control signal and the full-screen color temperature control signal are resampled by a bilinear interpolation algorithm; specifically, the full-screen brightness control signal and the full-screen color temperature control signal are input into the bilinear interpolation algorithm, and resampled according to the initial brightness distribution of each display partition, the pixel brightness of each partition is adjusted, and the adjusted partition brightness distribution information is generated.

[0087] For example, when the full-screen brightness control signal is relatively consistent but the initial brightness distribution of each partition is uneven, the brightness signal can be resampled through a bilinear interpolation algorithm to ensure the uniformity of the brightness distribution of each partition.

[0088] The adjusted partition brightness distribution information and display content distribution information are cross-analyzed by the cosine similarity calculation method to obtain pixel feature parameters; the pixel feature parameters are refined based on the bilateral filtering algorithm to obtain the pixel brightness control signal and pixel color temperature control signal of each pixel.

[0089] The partition brightness distribution information and the display content distribution information are cross-analyzed by the cosine similarity calculation method; specifically, the adjusted partition brightness distribution information and the display content distribution information are input into the cosine similarity calculation model, the similarity between the two is calculated, and the pixel feature parameters are obtained; the pixel feature parameters are refined based on the bilateral filtering algorithm to generate a pixel brightness control signal and a pixel color temperature control signal for each pixel.

[0090] For example, when the display content of a certain area is mainly dark images with low brightness, the cosine similarity calculation method can accurately analyze the characteristics of the area, and refine the pixel brightness and color temperature control signals through the bilateral filtering algorithm to improve the display effect.

[0091] The pixel brightness control signal and the pixel color temperature control signal are fused using the homography matrix transformation algorithm to obtain the pixel driving signal.

[0092] The pixel brightness control signal and the pixel color temperature control signal are fused through the homography matrix transformation algorithm; specifically, the pixel brightness control signal and the pixel color temperature control signal are input into the homography matrix transformation model, and the two are fused through matrix transformation to generate a comprehensive pixel driving signal to achieve independent and precise control of each pixel.

[0093] For example, when a certain area needs to adjust the brightness and color temperature at the same time, the homography matrix transformation algorithm can fuse the control signals of the two to generate a unified pixel drive signal to ensure the consistency of the display effect.

[0094] In step S400, the pixel driving signal is partitioned and mapped by a Voronoi diagram generation algorithm to generate a partition driving signal, and each partition of the display screen is independently driven by the partition driving signal to obtain a partition display output.

[0095] The pixel driving signal is partitioned and mapped by a Voronoi diagram generation algorithm; specifically, a Voronoi diagram is generated according to the pixel driving signal, the display screen is divided into a plurality of independent partitions, and a corresponding partition driving signal is generated for each partition; each partition is independently driven by the partition driving signal to obtain a partition display output.

[0096] For example, when the display content is complex and contains multiple different areas, the Voronoi diagram generation algorithm can effectively divide the screen into multiple areas. Each area generates an independent partition drive signal based on the pixel drive signal to ensure the consistency of the display effect of each area.

[0097] A support vector machine is used to classify the partition display output and display content distribution information to obtain the display priority of each area. The display priority and user interaction data are weighted by entropy weight method to identify the interaction priority area; wherein the user interaction data includes any of the following: touch interaction data, gesture interaction data, and voice input data.

[0098] The partition display output and display content distribution information are classified by a support vector machine; specifically, the partition display output and display content distribution information are input into a support vector machine model, each area is classified, and the display priority of each area is obtained; the display priority and user interaction data are weighted by an entropy weight method to determine the interaction priority area; the user interaction data may include touch interaction data, gesture interaction data, and voice input data.

[0099] For example, when a user frequently interacts with a certain area by touch, the support vector machine model can identify the area as a high-priority area and calculate its interaction weight through the entropy weight method to ensure that the area has the best display effect.

[0100] The display parameters of the interactive priority area are adjusted preferentially using the linear interpolation method to obtain the enhanced interactive partition display output.

[0101] The display parameters of the interactive priority area are adjusted preferentially through linear interpolation; specifically, the brightness and color temperature parameters of the high priority area are accurately adjusted using the linear interpolation algorithm to ensure that the display effect of the area reaches the best state and generate enhanced interactive partition display output.

[0102] For example, when a user performs gesture interaction in a certain area, the display parameters of the area are adjusted preferentially through linear interpolation to improve its brightness and color temperature, making the interactive experience smoother and more comfortable.

[0103] The partition display output and the enhanced interactive partition display output are subjected to weighted linear fusion processing to generate a pre-display interface.

[0104] The partition display output and the enhanced interactive partition display output are comprehensively processed through weighted linear fusion processing; specifically, each partition display output and the enhanced interactive partition display output are weighted fused according to preset weights to generate a pre-display interface to optimize the overall display effect of the display screen.

[0105] For example, when the display effects of multiple partitions are different, the display characteristics of each area can be integrated through weighted linear fusion processing to generate a more consistent pre-display interface.

[0106] In step S500, a convolutional neural network is used to extract features of the partition display output and the pre-display interface to obtain interface feature parameters and partition display output characteristic data. The interface feature parameters and the partition display output characteristic data are fused by linear discriminant analysis to generate an optimized parameter group.

[0107] The partition display output and the pre-display interface are feature extracted through a convolutional neural network. Specifically, the partition display output and the pre-display interface are input into the convolutional neural network to extract interface feature parameters and partition display output characteristic data. The extracted features are then fused through linear discriminant analysis to generate an optimized parameter group to further optimize the control effect of the display screen.

[0108] For example, when the pre-display interface has problems with uneven brightness and color temperature, the convolutional neural network can extract these features and generate an optimized parameter group through linear discriminant analysis to improve the display effect.

[0109] The optimization parameter group is parsed to generate screen refresh rate adjustment parameters, touch response adjustment parameters, and display content arrangement parameters.

[0110] By parsing the optimization parameter group, specific control parameters are generated; specifically, the data in the optimization parameter group is parsed to generate screen refresh rate adjustment parameters, touch response adjustment parameters and display content arrangement parameters, so as to optimize various performance of the display screen.

[0111] For example, by parsing the screen refresh rate adjustment data in the optimization parameter group, specific refresh rate adjustment parameters can be generated to ensure the smoothness of the display screen in different scenarios.

[0112] According to the screen refresh rate adjustment parameters, the display refresh rate is dynamically adjusted using a servo control algorithm.

[0113] The screen refresh rate is dynamically adjusted through a servo control algorithm; specifically, according to the screen refresh rate adjustment parameters, the servo control algorithm is applied to adjust the refresh rate of the display screen in real time to ensure the best display effect in different usage scenarios.

[0114] For example, when a user is watching a video, the servo control algorithm can dynamically increase the screen refresh rate to provide a smoother visual experience.

[0115] The parameters are adjusted according to the touch response, and the touch module is adjusted using a generalized predictive control algorithm.

[0116] The touch module is adjusted through a generalized predictive control algorithm; specifically, the parameters are adjusted according to the touch response, and the generalized predictive control algorithm is applied to optimize the response speed and sensitivity of the touch module to enhance the user's interactive experience.

[0117] For example, when a user quickly slides on the screen, the generalized predictive control algorithm can improve the response speed of the touch module, making the operation more sensitive and smooth.

[0118] According to the display content arrangement parameters, the layout and arrangement of the display screen content of the smart watch are optimized.

[0119] By optimizing the display content arrangement parameters, the layout and arrangement of the display screen content are adjusted; specifically, according to the display content arrangement parameters, the content distribution of each display area is optimized to improve the readability and visual aesthetics of the information.

[0120] For example, when multiple applications are displayed on the display screen at the same time, the layout of each application can be made more reasonable by adjusting the content arrangement parameters, thereby improving the user experience.

[0121] In this embodiment, the ambient light intensity and color temperature information are collected by the photodiode sensor module, and the ambient light correction parameters are obtained by combining the Gaussian filter algorithm for denoising, and the ambient light correction parameters are input into the multi-layer perceptron model with the luminous intensity and RGB color output information of the display screen to generate the brightness parameters and color temperature parameters of the display screen. In addition, the K-means clustering algorithm and the grayscale gradient watershed segmentation algorithm are used to divide and refine the display content to obtain the brightness distribution information of each display area. Then, the screen brightness and color temperature state are dynamically detected by the dynamic time warping algorithm and the principal component analysis method, and the main features are extracted to obtain the optimized display content distribution information. The Kalman filter algorithm analyzes the brightness parameters and color temperature parameters, generates the target brightness and color temperature adjustment values, and uses the linear regression model and the support vector machine regression model for partition processing to obtain the brightness and color temperature correction parameters of each partition. Through the pulse width modulation technology and the proportional integral differential control algorithm, the light-emitting unit and the color temperature adjustment unit of the backlight module are adjusted region by region to generate the full-screen brightness and color temperature control signal to ensure that the brightness and color temperature of the display screen are evenly distributed. In addition, the adjusted brightness and color temperature distribution information is processed through bilinear interpolation algorithm and cosine similarity calculation method to generate pixel drive signals, and the brightness and color temperature control signals are fused using homography matrix transformation algorithm. The Voronoi diagram generation algorithm and support vector machine classification method optimize the partition drive signal, and the display priority is calculated based on the entropy weight method to generate a pre-display interface. Finally, convolutional neural network and linear discriminant analysis are used to extract interface features and generate an optimized parameter group. The screen refresh rate and touch response are dynamically adjusted through servo control algorithm and generalized predictive control algorithm, and the display screen content layout is optimized to improve the overall display effect and user experience of smart watches.

[0122] Embodiment 3: like Figure 2 As shown, the present application also provides a display screen control device 10 for a smart watch, including a detection module 11, an adjustment module 12, a regulation module 13, a driving module 14 and a control module 15.

[0123] The detection module 11 is mainly used to perform real-time detection on the current state of the display screen of the smart watch, and obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen.

[0124] The adjustment module 12 is mainly used to adjust the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal.

[0125] The adjustment module 13 is mainly used to input the full-screen brightness control signal and the full-screen color temperature control signal into the preset display adjustment module 12, dynamically adjust the pixel partitions of the display screen, obtain the partition brightness distribution information, and use the partition brightness distribution information and display content distribution information to refine each pixel of the display screen to obtain a pixel driving signal.

[0126] The driving module 14 is mainly used to drive the display screen in partitions based on the pixel driving signal to obtain partition display output, and to prioritize the interactive area of ​​the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface.

[0127] The control module 15 is mainly used to analyze and process the partition display output and the pre-display interface, generate an optimized parameter group, and control the smart watch based on the optimized parameter group.

[0128] In this embodiment, the current state of the display screen is detected in real time by the detection module 11, and the brightness parameter, color temperature parameter and display content distribution information are obtained to ensure that the state of the display screen accurately reflects the current use environment. The adjustment module 12 adjusts the backlight module based on the brightness parameter and the color temperature parameter, generates a full-screen brightness control signal and a full-screen color temperature control signal, and ensures that the display screen can provide the best brightness and color temperature in different environments. The adjustment module 13 inputs these signals into the preset display adjustment module 12, dynamically adjusts the pixel partitions, and refines and adjusts each pixel according to the partition brightness distribution information and the display content distribution information to generate a pixel drive signal. The drive module 14 drives the display screen in partitions based on the pixel drive signal to obtain a partition display output, and preferentially adjusts the interactive area of ​​the display screen according to the display content distribution information and the user interaction data, generates a pre-display interface, and improves the user experience. The control module 15 analyzes and processes the partition display output and the pre-display interface, generates an optimization parameter group, and finely controls the smart watch based on the optimization parameter group to ensure the optimization of the display effect and user experience.

[0129] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned smart watch display screen control method embodiment, and will not be repeated here.

[0130] Embodiment 4: like Figure 3 As shown, the present application also provides an electronic device 20, including a memory 21 and a processor 22, the memory 21 stores a computer program that can be run on the processor 22, and when the processor 22 executes the computer program, the display screen control method of the smart watch of Example 1 is implemented.

[0131] In this embodiment, the computer program stored in the memory 21 is run by the memory 21 and the processor 22 of the electronic device 20 to execute the display screen control method of the smart watch. The processor 22 detects the current state of the display screen in real time through the computer program, obtains the brightness parameter, the color temperature parameter and the display content distribution information, and adjusts the backlight module of the display screen based on these parameters to generate a full-screen brightness control signal and a full-screen color temperature control signal. The processor 22 inputs the control signal into the preset display adjustment module 12, dynamically adjusts the pixel partitions of the display screen, and generates partition brightness distribution information and pixel drive signals. By driving the pixel drive signal by partition, the processor 22 realizes the partition display output, and according to the display content distribution information and the user interaction data, the interactive area is preferentially adjusted to generate a pre-display interface. Finally, the processor 22 analyzes and processes the partition display output and the pre-display interface, generates an optimized parameter group, and improves the display effect and user experience through fine control of the smart watch.

[0132] Embodiment 5: The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor executes the display screen control method of a smart watch as described in Example 1.

[0133] In this embodiment, the computer program stored in a computer-readable storage medium is used, and the processor executes the display screen control method of the smart watch when running the computer program. Specifically, the processor detects the current state of the display screen in real time through the computer program, obtains the brightness parameter, the color temperature parameter and the display content distribution information, adjusts the backlight module of the display screen based on these parameters, and generates a full-screen brightness control signal and a full-screen color temperature control signal. The processor inputs the control signal into the display adjustment module, dynamically adjusts the pixel partitions of the display screen, and obtains the partition brightness distribution information and the pixel drive signal. The processor partitions the display screen based on the pixel drive signal, generates a partition display output, and preferentially adjusts the interactive area according to the display content distribution information and the user interaction data, and generates a pre-display interface. Finally, the processor analyzes and processes the partition display output and the pre-display interface, generates an optimization parameter group, and ensures the improvement of the display effect and user experience through the optimization control of the smart watch.

[0134] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling a display screen of a smart watch, characterized in that: include: Perform real-time detection on the current state of the display screen of the smart watch to obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen; Based on the brightness parameter and the color temperature parameter, a backlight module of the display screen is adjusted to obtain a full-screen brightness control signal and a full-screen color temperature control signal; Input the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjust the pixel partitions of the display screen to obtain partition brightness distribution information, and use the partition brightness distribution information and the display content distribution information to fine-tune each pixel of the display screen to obtain a pixel driving signal; The display screen is driven by partitions based on the pixel driving signal to obtain a partition display output, and the interactive area of ​​the display screen is preferentially adjusted according to the display content distribution information and the user interaction data to obtain a pre-display interface; The partition display output and the pre-display interface are analyzed and processed to generate an optimization parameter group, and the smart watch is controlled based on the optimization parameter group.

2. The display screen control method of a smart watch according to claim 1, characterized in that: The step of detecting the current state of the display screen of the smart watch in real time to obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen includes: The photodiode sensor module is used to collect ambient light intensity and color temperature information around the display screen to obtain ambient brightness parameters and ambient color temperature parameters, and a Gaussian filter algorithm is used to perform denoising on the ambient brightness parameters and the ambient color temperature parameters to obtain ambient light correction parameters; Inputting the ambient light correction parameter and the luminous intensity and RGB color output information of the display screen into a preset multi-layer perceptron model to obtain the brightness parameter and color temperature parameter of the display screen; Dividing the display content of the display screen into regions to obtain initial display content distribution information and initial partition characteristic parameters; Using a grayscale gradient-based watershed segmentation algorithm to partition and refine the initial display content distribution information to obtain refined brightness distribution information, and fitting the refined brightness distribution information with the initial partition feature parameters to obtain brightness distribution information; Screen state characteristic parameters and regional display characteristics are generated according to the brightness distribution information, and main characteristics of the screen state characteristic parameters and the regional display characteristics are extracted using a principal component analysis method to obtain display content distribution information.

3. The display screen control method of a smart watch according to claim 1, characterized in that: The step of adjusting the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal comprises: The brightness parameter and the color temperature parameter are parsed by a Kalman filter algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and a preset linear regression model is used to perform partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value to obtain a brightness correction parameter and a color temperature correction parameter of each display partition; According to the brightness correction parameter, the light-emitting unit of the backlight module of the display screen is adjusted region by region through pulse width modulation technology to obtain a regional brightness control signal; According to the color temperature correction parameter, a proportional-integral-differential control algorithm is applied to fine-tune the color temperature adjustment unit of the backlight module of the display screen to obtain a regional color temperature control signal; The regional brightness control signal and the regional color temperature control signal are respectively subjected to weighted average processing to generate a full-screen brightness control signal and a full-screen color temperature control signal.

4. The display screen control method of a smart watch according to claim 3, characterized in that: The step of parsing the brightness parameter and the color temperature parameter by using a Kalman filter algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and performing partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain a brightness correction parameter and a color temperature correction parameter of each display partition includes: Using the Kalman filter algorithm to perform time series analysis on the brightness parameter to obtain a brightness trend prediction value and a brightness residual, performing moving average filtering on the brightness trend prediction value to obtain a brightness reference value, and performing fast Fourier transform on the brightness residual to obtain a brightness frequency domain characteristic parameter; Based on the brightness reference value and the brightness frequency domain characteristic parameter, a piecewise regression calculation is performed using a least squares polynomial fitting method to obtain an initial brightness adjustment value and a brightness offset correction value, and the initial brightness adjustment value and the brightness offset correction value are weighted and synthesized to obtain a target brightness adjustment value; The color temperature parameters are recursively analyzed by using a Kalman filter algorithm to obtain a color temperature trend prediction value and a color temperature dynamic change parameter, the color temperature trend prediction value is subjected to a wavelet transform analysis to obtain a multi-resolution color temperature detail parameter, and the significance weight of the color temperature dynamic change parameter is calculated by an entropy weight method to generate a color temperature change significance parameter; weighting the multi-resolution color temperature detail parameter and the color temperature change significance parameter based on a local weighted regression method to generate a target color temperature adjustment value; By using a weighted linear regression calculation method for regional partitions, the target brightness adjustment value is subjected to a partition-by-partition fitting process to obtain a brightness correction parameter for each display partition; The target color temperature adjustment value is refined partition by partition based on a regression model of a support vector machine to generate a color temperature correction parameter for each display partition.

5. The display screen control method of a smart watch according to claim 1, characterized in that: The step of inputting the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjusting the pixel partitions of the display screen to obtain partition brightness distribution information, and finely adjusting each pixel of the display screen using the partition brightness distribution information and the display content distribution information to obtain a pixel driving signal includes: Resampling the full-screen brightness control signal and the full-screen color temperature control signal by using a bilinear interpolation algorithm, adjusting the initial brightness distribution of pixels in each display partition, and obtaining adjusted partition brightness distribution information; Cross-analyzing the adjusted partition brightness distribution information and the display content distribution information by a cosine similarity calculation method to obtain pixel feature parameters; Refine the pixel characteristic parameters based on a bilateral filtering algorithm to obtain a pixel brightness control signal and a pixel color temperature control signal for each pixel; A homography matrix transformation algorithm is applied to fuse the pixel brightness control signal and the pixel color temperature control signal to obtain a pixel driving signal.

6. The display screen control method of a smart watch according to claim 1, characterized in that: The step of driving the display screen by partitions based on the pixel driving signal to obtain a partition display output, and preferentially adjusting the interactive area of ​​the display screen according to the display content distribution information and the user interaction data to obtain a pre-display interface includes: Performing partition mapping on the pixel drive signal by using a Voronoi diagram generation algorithm to generate a partition drive signal, and using the partition drive signal to independently drive each partition of the display screen to obtain a partition display output; A support vector machine is used to classify the partition display output and the display content distribution information to obtain the display priority of each area, and the display priority and user interaction data are weighted by an entropy weight method to identify the interaction priority area; wherein the user interaction data includes any one of the following: touch interaction data, gesture interaction data, and voice input data; Using a linear interpolation method to preferentially adjust the display parameters of the interactive priority area to obtain an enhanced interactive partition display output; The partition display output and the enhanced interactive partition display output are subjected to weighted linear fusion processing to generate a preview display interface.

7. The display screen control method of a smart watch according to claim 1, characterized in that: The step of analyzing and processing the partition display output and the pre-display interface to generate an optimization parameter group, and controlling the smart watch based on the optimization parameter group includes: Using a convolutional neural network to extract features from the partition display output and the pre-display interface to obtain interface feature parameters and partition display output characteristic data, and using linear discriminant analysis to fuse the interface feature parameters and the partition display output characteristic data to generate an optimization parameter group; Parsing the optimization parameter group to generate screen refresh rate adjustment parameters, touch response adjustment parameters, and display content arrangement parameters; According to the screen refresh rate adjustment parameter, a servo control algorithm is applied to dynamically adjust the display refresh rate; According to the touch response adjustment parameter, a generalized predictive control algorithm is applied to adjust the touch module; According to the display content arrangement parameters, the layout and arrangement of the display screen content of the smart watch are optimized.

8. A display screen control device for a smart watch, characterized in that: include: A detection module is used to detect the current state of the display screen of the smart watch in real time to obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen; An adjustment module, used to adjust the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal; an adjustment module, configured to input the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module, dynamically adjust the pixel partitions of the display screen to obtain partition brightness distribution information, and use the partition brightness distribution information and the display content distribution information to perform detailed adjustment on each pixel of the display screen to obtain a pixel driving signal; A driving module, configured to drive the display screen in partitions based on the pixel driving signal to obtain a partition display output, and to preferentially adjust the interactive area of ​​the display screen according to the display content distribution information and the user interaction data to obtain a pre-display interface; The control module is used to analyze and process the partition display output and the pre-display interface, generate an optimization parameter group, and control the smart watch based on the optimization parameter group.

9. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the display screen control method of the smart watch according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the processor executes the display screen control method of a smart watch as claimed in any one of claims 1 to 7.

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