Stroboflash processing method and device and electronic equipment

Abstract

The invention provides a stroboflash processing method and device and electronic equipment, and the method comprises the steps: at a target moment, obtaining at least one group of target data of an optical signal detected by the electronic equipment based on a target sensor, and a target refresh rate and target brightness of a target screen in the electronic equipment at the same moment; one group of target data comprises a signal frequency and a first energy intensity of the optical signal on the signal frequency, and the target sensor is arranged below the target screen; determining second energy intensity corresponding to the target refresh rate and the target brightness; and according to the target refresh rate and the second energy intensity, determining the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the at least one group of target data.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to a stroboscopic processing method, device and electronic equipment. Background Art

[0002] With the widespread popularity of various electronic devices such as mobile phones and computers, people spend more and more time facing electronic screens in their study, work and life. However, in actual use, the luminous flux of the ambient light source often fluctuates at a certain frequency, resulting in the flicker phenomenon of rapid changes in the brightness of the ambient light source, causing users to see alternating light and dark stripes when viewing the content displayed on the screen, reducing the viewing quality. It can also cause health problems such as visual fatigue and vision damage to users due to long-term exposure to the flickering screen.

[0003] In order to improve the above problems, Figure 1 As shown in the figure, currently, the effect of flicker is usually reduced by dynamically adjusting the screen brightness based on the ambient light brightness sensed by the rear optical sensor. However, this method has great limitations, such as Figure 2 In the scenario shown, that is, when the user uses the front camera to take pictures, this method cannot solve the flicker problem. If a professional flicker removal sensor is additionally installed around the front camera, the equipment cost will increase. Summary of the invention

[0004] In view of the above problems, this application provides the following technical solutions:

[0005] In a first aspect, the present application provides a stroboscopic processing method, which is applied to an electronic device, and the method comprises:

[0006] At a target moment, obtaining at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen;

[0007] determining a second energy intensity corresponding to the target refresh rate and the target brightness;

[0008] According to the target refresh rate and the second energy intensity, the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment is determined from the at least one set of target data.

[0009] Optionally, the determining the second energy intensity corresponding to the target refresh rate and the target brightness includes any one of the following:

[0010] Querying the correspondence between each combination of different refresh rates and different brightnesses of the target screen in the electronic device and different energy intensities, and determining a second energy intensity corresponding to the target refresh rate and the target brightness;

[0011] Input the target refresh rate and the target brightness into a trained machine learning model for analysis, and predict a second energy intensity corresponding to the target refresh rate and the target brightness;

[0012] Among them, the machine learning model is used to analyze the energy intensity of the screen light signal detected by the target sensor at different refresh rates and different brightness when the target screen in the electronic device is in the absence of ambient light.

[0013] Optionally, determining, from the at least one set of target data, the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment according to the target refresh rate and the second energy intensity, includes:

[0014] Comparing the target refresh rate and the second energy intensity with each group of target data to obtain corresponding comparison results;

[0015] According to the comparison result, the ambient light strobe frequency of the environment where the target screen is located at the target moment is determined from the signal frequency.

[0016] Optionally, determining, based on the comparison result, from the signal frequency, the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment, includes:

[0017] If the number of the at least one signal frequency is one and is the same as the target refresh rate, the first energy intensity is greater than the second energy intensity, and the signal frequency is determined as the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment.

[0018] Optionally, determining, based on the comparison result, from the signal frequency, the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment, includes:

[0019] Determining, from a plurality of sets of target data, candidate data having different refresh rates from the target refresh rate and the second energy intensity according to the comparison result;

[0020] If the candidate data is a group, the signal frequency in the candidate data is determined as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment;

[0021] If there are multiple groups of candidate data, the first energy intensities of the multiple groups of candidate data are compared, and the signal frequency of the group with the maximum first energy intensity is determined as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment.

[0022] Optionally, the method further includes:

[0023] In the image acquisition mode of the electronic device, a target exposure time of an image collector of the electronic device is determined according to the ambient light stroboscopic frequency; the target exposure time is an integer multiple of the ambient light stroboscopic period, and the ambient light stroboscopic period is determined according to the ambient light stroboscopic frequency;

[0024] According to the target exposure time, the configuration parameters of the image collector are adjusted.

[0025] Optionally, the machine learning model is trained by at least the following methods:

[0026] In the absence of ambient light, adjusting the refresh rate and brightness of the target screen in the electronic device to obtain the actual energy intensity of the corresponding screen light signal detected by the target sensor;

[0027] Inputting the refresh rate and brightness of the target screen obtained by each adjustment into the initial machine learning model for analysis to obtain the corresponding predicted energy intensity;

[0028] The machine learning model is obtained by reducing the prediction loss between the predicted energy intensity and the corresponding actual energy intensity and adjusting the parameters of the initial machine learning model.

[0029] Optionally, the process of acquiring the corresponding relationship includes any one of the following:

[0030] In the absence of ambient light, gradually adjusting the refresh rate and brightness of the target screen in the electronic device, and obtaining the energy intensity of the corresponding screen light signal detected by the target sensor to establish the corresponding relationship;

[0031] Based on the machine learning model, the energy intensities corresponding to the various combinations of different refresh rates and different brightness of the target screen in the electronic device are determined to establish the corresponding relationship.

[0032] A second aspect of the present application provides a stroboscopic processing device, which is applied to electronic equipment, and the device includes:

[0033] A first acquisition module is used to acquire, at a target moment, at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen;

[0034] A first determination module, configured to determine a second energy intensity corresponding to the target refresh rate and the target brightness;

[0035] The second determination module is used to determine the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the at least one set of target data according to the target screen refresh rate and the second energy intensity.

[0036] A third aspect of the present application provides an electronic device, the electronic device comprising at least one target sensor, at least one memory and at least one processor, wherein:

[0037] The target sensor is arranged below the target screen of the electronic device, and is used to detect the optical signal, process the optical signal, and obtain at least one set of target data; a set of the target data includes a signal frequency and a first energy intensity of the optical signal at the signal frequency;

[0038] The memory is used to store a plurality of computer instructions;

[0039] The processor is used to load and execute the computer instructions to implement the following steps:

[0040] At a target moment, obtaining at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen;

[0041] determining a second energy intensity corresponding to the target refresh rate and the target brightness;

[0042] According to the target screen refresh rate and the second energy intensity, the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment is determined from the at least one set of target data. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0044] Figure 1 A schematic diagram of a scene for stroboscopic processing based on optical sensors around a rear camera;

[0045] Figure 2 A schematic diagram of a stroboscopic processing scenario when shooting with a front camera;

[0046] Figure 3 A schematic diagram of an application scenario of a stroboscopic processing method provided in an embodiment of the present application;

[0047] Figure 4 A schematic diagram of an optional hardware structure of an electronic device applicable to the stroboscopic processing method proposed in the embodiment of the present application;

[0048] Figure 5 A schematic diagram of a flow chart of a stroboscopic processing method provided in Example 1 of the present application;

[0049] Figure 6 A schematic flow chart of a stroboscopic processing method provided in Embodiment 2 of the present application;

[0050] Figure 7 A schematic diagram of the correspondence between various combinations of different refresh rates and different brightnesses of a target screen in an electronic device and different energy intensities in a stroboscopic processing method provided in an embodiment of the present application;

[0051] Figure 8 A schematic diagram of target data detected by a target sensor in a stroboscopic processing method provided in an embodiment of the present application;

[0052] Fig. 9 A schematic diagram of a flow chart of a stroboscopic processing method provided in Embodiment 3 of the present application;

[0053] Fig.10 A schematic diagram of the structure of a stroboscopic processing device proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation mode of the present application are only used to explain the specific embodiments of the present application and are not intended to limit the present application. The embodiments of the present application are described below in conjunction with the drawings. It is known to those of ordinary skill in the art that with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0055] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0056] In order to solve the above problems, the present application provides a new flicker processing method, which does not require the installation of additional professional flicker removal sensors around the front camera of the electronic device (or other cameras without optical sensors installed, etc.), and directly reuses the target sensor already set under the target screen of the electronic device, that is, the under-screen sensor, such as Figure 3 In the application scenario shown, since each set of target data of the light signal actually detected by the target sensor at this time includes the signal frequency and energy intensity of the ambient light, as well as the signal frequency and energy intensity of the target screen light, by executing the stroboscopic processing method proposed in this application, the signal frequency and energy intensity of the target screen light detected by the target sensor can be quickly eliminated, the influence of the screen light on the target sensor can be removed, and the stroboscopic frequency of the ambient light in the environment where the target screen is located can be accurately obtained, so that appropriate measures can be taken to eliminate the stroboscopic frequency in the future, and the user can be prevented from seeing alternating light and dark stripes on the target screen, thereby improving the user's experience of using the electronic device and the reliability of the stroboscopic processing results. In addition, since the original target sensor of the electronic device is directly used, no additional sensor is installed near the camera, which simplifies the processing process and reduces the equipment cost. The stroboscopic processing method proposed in the embodiment of the present application and the electronic device using it will be described in detail below in conjunction with the accompanying drawings.

[0057] Reference Figure 4, is a schematic diagram of an optional hardware structure of an electronic device applicable to the stroboscopic processing method proposed in an embodiment of the present application, and the electronic device may include a terminal device with a screen such as a smart phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an edge device, a robot, a smart medical / transportation device, etc., such as Figure 4 As shown, the electronic device may include: at least one target sensor 41, at least one memory 42 and at least one processor 43, wherein:

[0058] At least one target sensor 41, at least one memory 42 and at least one processor 43 can communicate with each other via a bus. The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The bus is represented by only a line with a double-headed arrow, but it does not mean that there is only one bus or only one type of bus.

[0059] The target sensor 41 can be arranged below the target screen of the electronic device, and is used to detect the light signal, process the light signal, and obtain at least one set of target data; a set of target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency. For example, the energy intensity (i.e., luminous intensity) corresponding to 60Hz (signal frequency) is detected to include 15nit (unit: nit), and the energy intensity corresponding to 100Hz is detected to include 20nit, etc.

[0060] In the actual scenario where users usually use electronic devices, since the target sensor is located under the target screen, the light source sensed by it, in addition to the external ambient light source, will also include the target screen backlight, that is, the light source under the target screen, which is reflected by the glass above the screen, and the reflected light will pass through the target screen and be sensed by the target sensor. It should be understood that if the deployment position of the light source of the target screen changes, the path of its light sensed by the target sensor may change accordingly, and it is not limited to the screen backlight method described in this embodiment.

[0061] In an embodiment of the present application, if the electronic device includes multiple screens, the target sensor disposed below each screen has the above-mentioned detection function. In order to avoid interference, the screen in a display state (such as a state where the screen is bright and outputs display content) can be determined as a target screen, and the target sensor located below the target screen can be controlled to enter a working state, and then the above-mentioned detection function can be implemented to implement the stroboscopic processing method proposed in an embodiment of the present application. A screen in a non-display state (such as an off-screen state) can be used as a non-target sensor. At this time, the non-target sensor is in a non-working state and does not need to perform the above-mentioned detection function, so that the subsequent stroboscopic processing method is not adversely affected by the data output by such target sensors.

[0062] The memory 42 can be used to store multiple computer instructions for implementing the stroboscopic processing method proposed in the embodiment of the present application; the processor 43 can load and execute the computer instructions stored in the memory 42 to implement the various steps of the stroboscopic processing method proposed in the embodiment of the present application. The implementation process can refer to the description of the corresponding part of the method embodiment below.

[0063] In the embodiment of the present application, the memory 42 may include storage media such as a floppy disk, a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk. The processor 43 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), a digital signal processor (DSP), an application specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0064] It should be understood that Figure 4 The structure of the electronic device shown does not constitute a limitation on the electronic device in the embodiment of the present application. In practical applications, the electronic device may include Figure 4 More or fewer components, or combinations of certain components, may also include microphones, speakers, other sensors (such as temperature sensors, pressure sensors, gravity sensors, and speed sensors, etc.), antennas, power modules, RF components, external ports, and other input / output components, etc., which can be determined based on processing function requirements, and this application does not give detailed examples one by one.

[0065] The stroboscopic processing method proposed in this application is described below. Figure 5 The flowchart of a stroboscopic processing method provided in the first embodiment of the present application is shown in FIG. Figure 5 As shown, the frequency method can be applied to electronic devices, such as Figure 5 As shown, the stroboscopic processing method proposed at this time may include:

[0066] Step S51, at a target moment, obtaining at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment;

[0067] In an embodiment of the present application, the target moment can be any moment, such as the current moment or a specified historical moment, and the target screen can be any screen in the display state in the electronic device, which may be one or more of the multiple screens included in the electronic device. These multiple screens can be independent screens or screens corresponding to different display areas divided by one screen. If the screen is a flexible screen, after the screen is deformed, the part of the screen that continues to display the content can be determined as the target screen.

[0068] In order to avoid adding other devices, the present application can directly reuse the target sensor of the electronic device to realize the detection of the signal frequency and energy intensity of the light signal, which includes the refresh rate of the external light source and the screen light source of the target screen, that is, the signal frequency and the corresponding energy intensity. In order to remove the influence of the screen light source on the detection result of the target sensor, the target refresh rate and brightness of the target screen at the target moment can also be read to query the refresh rate and energy intensity of the target screen light source at the target moment when the target screen is at the target refresh rate, so as to remove the influence of the target screen light source on the detection result of the target sensor.

[0069] Wherein, for each set of target data actually detected by the target sensor at the target time, it may be frequency domain data, such as a signal frequency and a first energy intensity of a light signal (which may include a mixed light signal of an external environment light signal and a target screen light signal) at the signal frequency. The signal frequencies of different sets of target data are different, and the signal frequency includes at least a target refresh rate of the target screen.

[0070] Step S52, determining a second energy intensity corresponding to the target refresh rate and the target brightness;

[0071] In an embodiment of the present application, it is possible to determine in advance by means of experiments or inference calculations, when there is no ambient light, the target screen of the electronic device is at the target refresh rate and target brightness, the signal frequency and energy intensity of the target screen light signal collected by the target sensor, the signal frequency is the target refresh rate of the target screen at the target moment, and the energy intensity can be recorded as the second energy intensity. It should be noted that for electronic devices of different models, even if the target screen is at the same refresh rate and high brightness, in the absence of ambient light, the second energy intensity that can be collected by the target sensor is different, and the present application does not limit the value of the second energy intensity and its acquisition method.

[0072] Step S53, determining the ambient light strobe frequency of the environment where the target screen is located at the target moment from at least one set of target data according to the target refresh rate and the second energy intensity.

[0073] Following the above analysis, the present application can compare the target refresh rate with the signal frequency in each target data, and after determining a group of target data that includes the target refresh rate, compare the first energy intensity in the target data with the second energy intensity to determine whether the target data includes the signal frequency and energy intensity of the ambient light. If included, the second energy intensity of the target screen light can be removed from the target data to obtain the signal frequency and energy intensity of the ambient light of the target screen at the target moment to determine the ambient light stroboscopic frequency; if not included, the group of target data is the data of the target screen light. In this case, the target sensor will also detect other groups of target data, namely the data of the ambient light, from which the ambient light stroboscopic frequency can be determined.

[0074] To summarize, the present application reuses the target sensor under the existing target screen of the electronic device, detects at least one set of target data of the light signal at the target moment, determines the second energy intensity corresponding to the target refresh rate and target brightness of the target screen at the target moment, and then determines the ambient light flicker frequency of the environment in which the target screen is located at the target moment by comparing the target refresh rate and the second energy intensity with the target data, so as to accurately eliminate the flicker and prevent the user from seeing alternating light and dark stripes on the target screen, thereby improving the user experience of the electronic device and the reliability of the flicker processing results. There is no need to install additional sensors on the electronic device, which simplifies the processing process and reduces the equipment cost.

[0075] Reference Figure 6 , is a flow chart of a stroboscopic processing method provided in Embodiment 2 of the present application, such as Figure 6 As shown, the stroboscopic processing method may include:

[0076] Step S61, at a target moment, obtaining at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment;

[0077] Step S62, querying the correspondence between each combination of different refresh rates and different brightness of the target screen and different energy intensities, and determining a second energy intensity corresponding to the target refresh rate and target brightness;

[0078] In the embodiment of the present application, in the absence of external ambient light, when only the target screen light is present, by adjusting the refresh rate and brightness of the target screen, after each adjustment of the refresh rate or brightness, it is necessary to obtain the signal frequency and energy intensity detected by the target sensor, that is, the second energy intensity, and determine the second energy intensity corresponding to the combination of the refresh rate and brightness. In this way, the corresponding relationship between each combination of different refresh rates and different brightnesses of the target screen and different energy intensities can be recorded, which can be represented in a graphical form, such as Figure 7 As shown; it can also be recorded in a table, and corresponding rules can be analyzed to represent the corresponding relationship, etc., so that the second energy intensity corresponding to the target refresh rate and target brightness can be directly queried therefrom. The present application does not limit the storage method of the corresponding relationship and the method for obtaining it.

[0079] It can be seen that for the above correspondence, in the absence of ambient light, the refresh rate and brightness of the target screen in the electronic device can be gradually adjusted to obtain the energy intensity of the corresponding screen light signal detected by the target sensor to establish the above correspondence, such as Figure 7 As shown, the refresh rate and brightness of the target screen are adjusted to include but are not limited to Figure 7 The values ​​shown.

[0080] In another possible implementation, the present application may also determine the energy intensity corresponding to each combination of different refresh rates and different brightness of the target screen in the electronic device based on the machine learning model to establish the above correspondence. The machine learning model may be an artificial intelligence model, such as a fully connected neural network, a convolutional neural network, a random forest algorithm, etc. The machine learning model may be used to fit the correspondence between various refresh rates and brightness of the target screen and the energy intensity (such as the amplitude value in the frequency domain) obtained by Fourier transform of the target screen light signal. The fitted refresh rate and brightness of the target screen include but are not limited to Figure 7 The values ​​shown.

[0081] Step S63, comparing the target refresh rate and the second energy intensity with each group of target data to obtain corresponding comparison results;

[0082] Combined with the above analysis, refer to Figure 3In the application scenario, in order to determine the ambient light stroboscopic frequency at the target moment, after the refresh rate and brightness of the target screen at the target moment are known, the second energy intensity can be compared with the signal frequency and the first energy intensity in each group of target data actually detected by the target sensor, so as to determine the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment from the signal frequencies detected by the target sensor based on the comparison result.

[0083] In one possible implementation, if the number of at least one signal frequency is one and is the same as the target refresh rate, it means that the target screen light signal is consistent with the signal frequency of the external ambient light signal. In this case, the target screen will capture the same phase (bright or dark) of the ambient light source and the target screen light source each time it is refreshed, causing the human eye to perceive obvious flicker. At this time, the target sensor detects a set of target data at the target moment, and the first energy intensity contained therein is obtained by superimposing the energy intensities of the two light signals, so that the first energy intensity detected by the target sensor is greater than the second energy intensity. In this case, the detected signal frequency can be determined as the ambient light flicker frequency (i.e., the flicker of the external light source) of the environment in which the target screen is located at the target moment. The energy intensity of the ambient light signal can be obtained by subtracting the second energy intensity from the first energy intensity, and the flicker can be eliminated subsequently. The flicker elimination method is not limited in this application.

[0084] Combined with the above analysis, in actual applications, since the refresh rate of the target screen is usually continuously changing, even if the refresh rate at the target moment is consistent with the ambient light stroboscopic frequency, the refresh rate of the target screen may be inconsistent with the ambient light stroboscopic frequency at the next moment or several moments later, causing the target screen to display images of different brightness levels in each refresh cycle, causing the user to perceive stroboscopic light. In this case, the target sensor actually detects multiple sets of target data at the corresponding moment, including at least the refresh rate and the second energy intensity of the target screen at that moment. In addition, it can also include at least one set of target data for the ambient light source. Based on the comparison results, the ambient light stroboscopic frequency can be determined according to the following steps to describe the method.

[0085] Step S64, determining candidate data having different refresh rate and second energy intensity from the plurality of sets of target data according to the comparison result;

[0086] Step S65, if the candidate data is a group, the signal frequency in the candidate data is determined as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment;

[0087] Step S66: if there are multiple groups of candidate data, compare the first energy intensities of the multiple groups of candidate data, and determine the signal frequency of the group with the maximum first energy intensity as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment.

[0088] Following the above analysis, by comparing the target refresh rate and the second energy intensity with each group of target data, other groups of target data other than the one group of target data for the target screen light source are determined as candidate data for the ambient light source. If the current ambient light source is a relatively fixed single light source, a group of candidate data may be obtained at this time, and the signal frequency contained in it can be directly determined as the ambient light strobe frequency of the environment in which the target screen is located at the target moment. If the current ambient light source is multiple complex light sources, or the environmental entity will reflect the ambient light source, and the reflected light enters the target screen, it can also enable the target sensor to sense the signal frequency and energy intensity of the ambient light source and the reflected light, such as Figure 8 shown.

[0089] Therefore, when there are multiple groups of candidate data, the first energy intensities contained in each group of candidate data for the ambient light source can be compared, and the signal frequency with the maximum first energy intensity can be determined as the ambient light stroboscopic frequency of the environment where the target screen is located at the target time. Figure 8 As shown, assuming that the refresh rate of the target screen at the target moment is 60Hz and the second energy intensity is 150, it can be eliminated from the multiple groups of target data detected by the target sensor, and from the remaining multiple groups of candidate data, a group of candidate data with a signal frequency of 100Hz and a first energy intensity of 230nit as shown in 8 is selected to be determined as the ambient light flicker parameters of the ambient light source, so as to reliably eliminate flicker.

[0090] In some embodiments, in an image acquisition mode of an electronic device (such as a scene of taking photos with a camera), the target exposure time of the image collector of the electronic device can be determined according to the ambient light stroboscopic frequency at the target moment, so as to adjust the configuration parameters of the image collector according to the target exposure time to eliminate stroboscopic light. The target exposure time is an integer multiple of the ambient light stroboscopic period, and the ambient light stroboscopic period can be determined according to the ambient light stroboscopic frequency.

[0091] It should be noted that regarding the method of eliminating flicker, in addition to the implementation method of adjusting the exposure time described above, the frame rate of the camera can also be adjusted according to the ambient light flicker frequency at the target moment, so that the exposure time of each frame of the image matches the flicker period of the light source. This ensures the brightness consistency between consecutive frames and avoids the appearance of rolling flicker stripes. Alternatively, flicker can be reduced by adjusting the refresh rate of the target screen. For example, when the target screen is at high brightness, DC dimming can be used to reduce flicker, and when the target screen is at low brightness, the visibility of flicker can be reduced by increasing the PWM (pulse width modulation) frequency. In addition, the impact of flicker can be predicted and compensated by software algorithms to reduce the visual impact of flicker. This application does not limit the implementation method of eliminating flicker.

[0092] In some embodiments, the present application can train a machine learning model to analyze the energy intensity of the screen light signal detected by the target sensor at different refresh rates and different brightnesses of the target screen in an electronic device in the absence of ambient light. In this way, after determining the target refresh rate and target brightness of the target screen at the target moment, the target refresh rate and target brightness can be input into the machine learning model for analysis to predict a second energy intensity corresponding to the target refresh rate and target brightness.

[0093] Based on this, Fig. 9 As shown, it is a flow chart of a stroboscopic processing method provided in the third embodiment of the present application. This embodiment can describe an optional training method of the machine learning model for predicting the second energy intensity in the above stroboscopic processing method, such as Fig. 9 As shown, the optional training method may include but is not limited to the following steps:

[0094] Step S91, in the absence of ambient light, adjusting the refresh rate and brightness of the target screen in the electronic device to obtain the actual energy intensity of the corresponding screen light signal detected by the target sensor;

[0095] Step S92, inputting the refresh rate and brightness of the target screen obtained by each adjustment into the initial machine learning model for analysis to obtain the corresponding predicted energy intensity;

[0096] Step S93, by reducing the prediction loss between the predicted energy intensity and the corresponding actual energy intensity, the parameters of the initial machine learning model are adjusted to obtain the machine learning model.

[0097] In the embodiment of the present application, the implementation method of step S91 can be obtained by the experimental test described above, and the implementation process is not described in detail in this application. In this embodiment, the refresh rate and brightness obtained by adjusting the target screen each time can be associated and stored with the actual energy intensity of the screen light signal actually detected as a set of sample data, and the actual energy intensity can be used as a label. In this way, multiple groups of sample data are obtained, and the refresh rate and brightness of the target screen are input into the initial machine learning model for fitting analysis to obtain the corresponding predicted energy intensity, that is, the intensity after the predicted FFT. After that, the loss function can be used to calculate the predicted loss between the predicted energy intensity and the corresponding actual energy intensity. According to the predicted loss, the parameters of the initial machine learning model are adjusted until the number of training times reaches the specified number, or the predicted loss converges, etc. The machine learning model finally trained is used as a machine learning model for analyzing the energy intensity of the screen light signal detected by the target sensor at different refresh rates and different brightnesses in the target screen of the electronic device in the absence of ambient light.

[0098] A stroboscopic processing method provided by an embodiment of the present application is introduced above, and a device for executing the stroboscopic processing method will be introduced below.

[0099] Reference Fig.10 , is a schematic diagram of the structure of a stroboscopic processing device proposed in an embodiment of the present application, and the stroboscopic processing device can be applied to the electronic equipment as described above, such as Fig.10 As shown, the stroboscopic processing device may include:

[0100] The first acquisition module 101 is used to acquire at least one set of target data of the electronic device based on the light signal detected by the target sensor at a target moment, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen;

[0101] A first determination module 102, configured to determine a second energy intensity corresponding to the target refresh rate and the target brightness;

[0102] The second determination module 103 is used to determine the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the at least one set of target data according to the target screen refresh rate and the second energy intensity.

[0103] In a possible implementation, the first determining module 102 may include:

[0104] A query unit, used to query the correspondence between each combination of different refresh rates and different brightness of the target screen in the electronic device and different energy intensities, and determine a second energy intensity corresponding to the target refresh rate and the target brightness;

[0105] Alternatively, a prediction unit is used to input the target refresh rate and the target brightness into a trained machine learning model for analysis, and predict a second energy intensity corresponding to the target refresh rate and the target brightness;

[0106] Among them, the machine learning model is used to analyze the energy intensity of the screen light signal detected by the target sensor at different refresh rates and different brightness when the target screen in the electronic device is in the absence of ambient light.

[0107] Optionally, the unit for acquiring the above correspondence may include:

[0108] An energy intensity acquisition subunit, used for gradually adjusting the refresh rate and brightness of the target screen in the electronic device in the absence of ambient light, and acquiring the energy intensity of the corresponding screen light signal detected by the target sensor to establish the corresponding relationship;

[0109] The energy intensity determination subunit is used to determine the energy intensity corresponding to each combination of different refresh rates and different brightness of the target screen in the electronic device based on the machine learning model to establish the corresponding relationship.

[0110] In a possible implementation, the second determining module 103 may include:

[0111] A comparison unit, used for comparing the target refresh rate and the second energy intensity with each group of target data to obtain a corresponding comparison result;

[0112] The first determination unit is used to determine the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the signal frequency according to the comparison result.

[0113] Optionally, the first determining unit may include:

[0114] The first determination subunit is used to determine the signal frequency as the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment if the number of the at least one signal frequency is one and is the same as the target refresh rate and the first energy intensity is greater than the second energy intensity.

[0115] a second determining subunit, configured to determine, from a plurality of sets of target data, candidate data different from the target refresh rate and the second energy intensity according to the comparison result;

[0116] A third determining subunit is used for determining the signal frequency in the candidate data as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment if the candidate data is a group;

[0117] The fourth determination subunit is used to compare the first energy intensities of each of the multiple groups of candidate data if there are multiple groups of candidate data, and determine the signal frequency of the group with the maximum first energy intensity as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment.

[0118] In some embodiments, the stroboscopic processing device may further include:

[0119] A third determination module is used to determine, in the image acquisition mode of the electronic device, a target exposure time of the image collector of the electronic device according to the ambient light stroboscopic frequency; the target exposure time is an integer multiple of the ambient light stroboscopic period, and the ambient light stroboscopic period is determined according to the ambient light stroboscopic frequency;

[0120] The adjustment module is used to adjust the configuration parameters of the image collector according to the target exposure time.

[0121] Optionally, the model training module for training the machine learning model may also include:

[0122] A first acquisition unit, configured to adjust the refresh rate and brightness of a target screen in the electronic device in the absence of ambient light, and acquire an actual energy intensity of a corresponding screen light signal detected by the target sensor;

[0123] An analysis unit, configured to input the refresh rate and brightness of the target screen obtained by each adjustment into an initial machine learning model for analysis to obtain a corresponding predicted energy intensity;

[0124] A parameter adjustment unit is used to adjust the parameters of the initial machine learning model by reducing the prediction loss between the predicted energy intensity and the corresponding actual energy intensity to obtain the machine learning model.

[0125] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any one of the stroboscopic processing methods provided in the embodiments of the present application.

[0126] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any one of the stroboscopic processing methods provided in the embodiment of the present application.

[0127] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0128] Through the description of the above implementation mode, in the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a training device or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that contains one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0129] In addition, the various embodiments in this specification are described in a progressive or parallel manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the devices, electronic devices, products and media disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part description.

Claims

1. A stroboscopic processing method, applied to electronic equipment, the method comprising: At a target moment, obtaining at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen; determining a second energy intensity corresponding to the target refresh rate and the target brightness; According to the target refresh rate and the second energy intensity, the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment is determined from the at least one set of target data.

2. The method according to claim 1, wherein determining the second energy intensity corresponding to the target refresh rate and the target brightness comprises any one of the following: Querying the correspondence between each combination of different refresh rates and different brightnesses of the target screen in the electronic device and different energy intensities, and determining a second energy intensity corresponding to the target refresh rate and the target brightness; Input the target refresh rate and the target brightness into a trained machine learning model for analysis, and predict a second energy intensity corresponding to the target refresh rate and the target brightness; in, The machine learning model is used to analyze the energy intensity of the screen light signal detected by the target sensor at different refresh rates and different brightness when the target screen in the electronic device is in the absence of ambient light.

3. The method according to claim 1, wherein determining the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment from the at least one set of target data according to the target refresh rate and the second energy intensity comprises: Comparing the target refresh rate and the second energy intensity with each group of target data to obtain corresponding comparison results; According to the comparison result, the ambient light strobe frequency of the environment where the target screen is located at the target moment is determined from the signal frequency.

4. The method according to claim 3, wherein determining the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the signal frequency based on the comparison result comprises: If the number of the at least one signal frequency is one and is the same as the target refresh rate, the first energy intensity is greater than the second energy intensity, and the signal frequency is determined as the ambient light stroboscopic frequency of the environment in which the target screen is located at the target moment.

5. The method according to claim 3, wherein determining the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the signal frequency according to the comparison result comprises: Determining, from a plurality of sets of target data, candidate data having different refresh rates from the target refresh rate and the second energy intensity according to the comparison result; If the candidate data is a group, the signal frequency in the candidate data is determined as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment; If there are multiple groups of candidate data, the first energy intensities of the multiple groups of candidate data are compared, and the signal frequency of the group with the maximum first energy intensity is determined as the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment.

6. The method according to any one of claims 1 to 5, further comprising: In the image acquisition mode of the electronic device, determining a target exposure time of an image collector of the electronic device according to the ambient light stroboscopic frequency; The target exposure time is an integer multiple of the ambient light stroboscopic period, and the ambient light stroboscopic period is determined according to the ambient light stroboscopic frequency; According to the target exposure time, the configuration parameters of the image collector are adjusted.

7. According to the method of claim 2, the machine learning model is trained at least in the following manner: In the absence of ambient light, adjusting the refresh rate and brightness of the target screen in the electronic device to obtain the actual energy intensity of the corresponding screen light signal detected by the target sensor; Inputting the refresh rate and brightness of the target screen obtained by each adjustment into the initial machine learning model for analysis to obtain the corresponding predicted energy intensity; The machine learning model is obtained by reducing the prediction loss between the predicted energy intensity and the corresponding actual energy intensity and adjusting the parameters of the initial machine learning model.

8. According to the method of claim 2, the process of acquiring the corresponding relationship comprises any one of the following: In the absence of ambient light, gradually adjusting the refresh rate and brightness of the target screen in the electronic device, and obtaining the energy intensity of the corresponding screen light signal detected by the target sensor to establish the corresponding relationship; Based on the machine learning model, the energy intensities corresponding to the various combinations of different refresh rates and different brightness of the target screen in the electronic device are determined to establish the corresponding relationship.

9. A stroboscopic processing device, applied to electronic equipment, comprising: A first acquisition module is used to acquire, at a target moment, at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen; A first determination module, configured to determine a second energy intensity corresponding to the target refresh rate and the target brightness; The second determination module is used to determine the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment from the at least one set of target data according to the target screen refresh rate and the second energy intensity.

10. An electronic device, comprising at least one target sensor, at least one memory and at least one processor, wherein: The target sensor is arranged below the target screen of the electronic device, and is used to detect the optical signal, process the optical signal, and obtain at least one set of target data; a set of the target data includes a signal frequency and a first energy intensity of the optical signal at the signal frequency; The memory is used to store a plurality of computer instructions; The processor is used to load and execute the computer instructions to implement the following steps: At a target moment, obtaining at least one set of target data of the electronic device based on the light signal detected by the target sensor, and a target refresh rate and a target brightness of a target screen in the electronic device at the same moment; a set of the target data includes a signal frequency and a first energy intensity of the light signal at the signal frequency, and the target sensor is arranged below the target screen; determining a second energy intensity corresponding to the target refresh rate and the target brightness; According to the target screen refresh rate and the second energy intensity, the ambient light stroboscopic frequency of the environment where the target screen is located at the target moment is determined from the at least one set of target data.

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