Information acquisition method and apparatus, and electronic device and computer-readable storage medium

Abstract

Disclosed in the embodiments of the present application are an information acquisition method and apparatus, and an electronic device and a computer-readable storage medium. The method comprises: in response to a starting operation for a photographing device, acquiring a preview image for a target scene, and recording brightness change events corresponding to the preview image; performing motion detection on the preview image, so as to identify texture change region information in the preview image; on the basis of the texture change region information, filtering the brightness change events, so as to obtain static brightness change events; and on the basis of the static brightness change events, generating target light source frequency information of the target scene. The elimination of motion interference in a scene is facilitated, so as to realize the selection of effective static brightness change events, and accurate target light source frequency information can then be generated on the basis of the static brightness change events, thereby improving the accuracy of the target light source frequency information.

Description

Information acquisition methods, devices, electronic devices and computer-readable storage media

[0001] This application claims priority to Chinese patent application filed on July 18, 2024, with application number 202410969002.5 and entitled "Information Acquisition Method, Apparatus, Electronic Device and Computer-Readable Storage Medium", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of image processing, specifically to an information acquisition method, apparatus, electronic device, and computer-readable storage medium. Background Technology

[0003] In digital image processing, anti-banding is a technique for treating striped artifacts or color banding in images. These artifacts typically appear in transitional areas of an image, particularly at gradual color or brightness changes. The goal of anti-banding algorithms is to reduce or eliminate these bands to improve image quality. The effectiveness of anti-banding algorithms is related to the frequency of the light source corresponding to the input image; that is, anti-banding algorithms that match the light source frequency perform better in processing image stripes. Technical issues

[0004] Currently, the light source frequency is mainly obtained through user selection or system preset. However, the light source frequency set in this way is prone to discrepancies with the actual light source frequency. Technical solutions

[0005] This application provides an information acquisition method, apparatus, electronic device, and computer-readable storage medium that can automatically identify the frequency of a light source and improve the accuracy of the light source frequency.

[0006] In a first aspect, embodiments of this application provide an information acquisition method applied to a shooting device, the method comprising:

[0007] In response to the activation operation of the shooting device, a preview image of the target scene is acquired, and the brightness change event corresponding to the preview image is recorded;

[0008] Motion detection is performed on the preview image to identify texture change regions in the preview image;

[0009] The brightness change events are filtered based on the texture change region information to obtain static brightness change events;

[0010] The target light source frequency information of the target scene is generated based on the static brightness change event.

[0011] Secondly, embodiments of this application also provide an information acquisition device applied to a shooting device, the device comprising:

[0012] The acquisition module is used to acquire a preview image of the target scene in response to the start operation of the shooting device, and to record the brightness change event corresponding to the preview image;

[0013] The recognition module is used to perform motion detection on the preview image in order to identify texture change areas in the preview image;

[0014] The filtering module is used to filter the brightness change events based on the texture change region information to obtain static brightness change events;

[0015] The generation module is used to generate target light source frequency information of the target scene based on the static brightness change event.

[0016] Optionally, in some embodiments of this application, the brightness change event corresponds to brightness change area information and event time information, and the filtering module includes:

[0017] A filtering unit is used to filter motion brightness change events from the brightness change events based on the brightness change region information, the texture change region information, and the event time information.

[0018] A filtering unit is used to filter out the motion brightness change events from the brightness change events to obtain static brightness change events.

[0019] In some embodiments of this application, the generation module includes:

[0020] The information acquisition unit is used to obtain event duration information based on the event time information of each of the static brightness change events;

[0021] The duration calculation unit is used to calculate the average event duration information of each of the static brightness change events to obtain the average event duration information;

[0022] The generation unit is used to generate target light source frequency information of the target scene based on the average event duration information.

[0023] In some embodiments of this application, the identification module includes:

[0024] The difference calculation unit is used to calculate the difference between each pixel in adjacent preview images to obtain the pixel difference.

[0025] A pixel determination unit is used to determine a target pixel from the preview image based on a preset threshold and the pixel difference;

[0026] The information determination unit is used to use the position information corresponding to the target pixel as texture change region information.

[0027] In some embodiments of this application, the shooting device integrates an event camera, and the acquisition module includes:

[0028] The event acquisition unit is used to respond to the start operation of the shooting device, acquire a preview image of the target scene through a conventional camera, and simultaneously capture an event in which the brightness change exceeds a preset brightness threshold through the event camera to obtain a brightness change event.

[0029] In some embodiments of this application, the device further includes a correction module, which includes:

[0030] The strategy determination unit is used to determine an anti-striping processing strategy according to the target light source frequency information;

[0031] The processing unit is used to perform anti-striping processing on the preview image according to the anti-striping processing strategy to obtain the target image; the capturing unit is used to capture the target image in response to the image capturing command.

[0032] In some embodiments of this application, the acquisition module includes:

[0033] A response unit is configured to respond to a startup operation of the shooting device, acquire a preview image of the target scene through a preset exposure time, and record the brightness change event corresponding to the preview image. The preset exposure time is determined based on historical preview images and historical brightness change events of the target scene.

[0034] The recognition module includes:

[0035] A quality detection unit is used to perform quality detection on the preview image and obtain the quality detection result;

[0036] The motion detection unit is used to perform motion detection on the preview image if the quality detection result of the preview image does not meet the preset conditions, so as to identify the texture change area information in the preview image.

[0037] Thirdly, embodiments of this application also provide an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps in the information acquisition method described above.

[0038] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in the information acquisition method described above.

[0039] Fifthly, embodiments of this application also provide a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described in embodiments of this application. Beneficial effects

[0040] In summary, the shooting device of this application embodiment, in response to the start operation of the shooting device, acquires a preview image of the target scene and records the brightness change event corresponding to the preview image, performs motion detection on the preview image to identify texture change region information in the preview image, filters the brightness change event according to the texture change region information to obtain a static brightness change event, and generates target light source frequency information of the target scene according to the static brightness change event.

[0041] By recording brightness change events corresponding to the preview image, it is possible to automatically analyze and generate frequency information of brightness changes based on these events. Furthermore, by identifying texture change regions in the preview image and filtering brightness change events based on this information, motion interference in the scene can be eliminated, achieving effective screening of static brightness change events. Based on these effective static brightness change events, accurate target light source frequency information can be generated, improving the accuracy of the target light source frequency information. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 is a schematic diagram of a scene in which the shooting device provided in an embodiment of this application performs the information acquisition method;

[0044] Figure 2 is a flowchart illustrating the information acquisition method provided in an embodiment of this application;

[0045] Figure 3 is an architecture diagram of the information acquisition system corresponding to the information acquisition method provided in the embodiments of this application;

[0046] Figure 4 is a schematic diagram of the information acquisition device provided in an embodiment of this application;

[0047] Figure 5 is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. Embodiments of the present invention

[0048] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] This application provides an information acquisition method, apparatus, electronic device, and computer-readable storage medium. Specifically, this application provides an information acquisition apparatus suitable for electronic devices, including imaging devices such as cameras (e.g., digital cameras, SLR cameras, camcorders, etc.) and mobile phones, and can also be used in other image processing applications that require stripe removal (e.g., scanners, monitoring systems, medical devices, etc.).

[0050] Specifically, please refer to Figure 1. Figure 1 is a schematic diagram of a scenario in which the shooting device provided in this application performs the information acquisition method. The specific execution process of the shooting device performing the information acquisition method is as follows:

[0051] In response to the start operation of the shooting device 10, the shooting device 10 acquires a preview image of the target scene and records the brightness change event corresponding to the preview image, performs motion detection on the preview image to identify texture change area information in the preview image, filters the brightness change event based on the texture change area information to obtain a static brightness change event, and generates target light source frequency information of the target scene based on the static brightness change event.

[0052] In summary, the embodiments of this application, by recording brightness change events corresponding to preview images, facilitate the automated analysis and generation of brightness change frequency information based on these events. Specifically, by identifying texture change regions in the preview image and filtering brightness change events based on this information, motion interference in the scene can be eliminated, achieving effective screening of static brightness change events. Furthermore, based on these effective static brightness change events, accurate target light source frequency information can be generated, improving the accuracy of the target light source frequency information.

[0053] The following sections provide detailed descriptions of each example. It should be noted that the order in which the embodiments are described is not intended to limit the priority of the embodiments.

[0054] Please refer to Figure 2, which is a flowchart illustrating the information acquisition method provided in an embodiment of this application. Although the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown in the figures. Specifically, this information acquisition method is applied to a shooting device, and the specific flow of the information acquisition method is as follows: 101. In response to a startup operation on the shooting device, a preview image of the target scene is acquired, and the brightness change event corresponding to the preview image is recorded.

[0055] Understandably, the "startup operation" refers to the operation of activating the shooting function of the shooting device. For example, when the shooting device is a camera, the startup operation means activating the camera to take a picture. When the shooting device is a mobile phone with a shooting function, the startup operation means activating the shooting function of the mobile phone, such as activating the shooting application of the mobile phone.

[0056] Among them, the preview image is an image displayed in a preview mode. For example, before the shooting device confirms that an image that can be stored in the album has been captured, the real-time image data collected by the sensor of the shooting device is displayed on the screen of the shooting device as the shooting angle of the shooting device changes. For example, after the mobile phone launches the camera application, the preview image displayed on the screen is only generated based on the real-time preview image when the shooting control is clicked, so that the photo that can be stored in the album is generated.

[0057] It should be noted that a brightness change event is an event recorded by the shooting device when a change in brightness occurs in the target scene. For example, a brightness change event is generated when the light intensity in the target scene changes. This brightness change event can be captured by an event camera. An event camera (EVS, Event-Based Vision Sensor) is essentially a sensor that generates events by detecting brightness changes, rather than outputting images at a fixed frame rate.

[0058] Accordingly, in the embodiments of this application, a preview image can be acquired based on a traditional camera, and a brightness change event can be acquired through an event camera. That is, optionally, in some embodiments of this application, the step "in response to the start operation of the shooting device, acquire a preview image of the target scene, and record the brightness change event corresponding to the preview image" includes:

[0059] In response to the activation operation of the shooting device, a preview image of the target scene is acquired using a conventional camera, and simultaneously, an event camera is used to capture an event in which the brightness change exceeds a preset brightness threshold, thus obtaining a brightness change event. Here, a conventional camera refers to a camera that outputs images at a fixed frame rate, such as common digital cameras, SLR cameras, camcorders, and mobile phone cameras.

[0060] In this embodiment of the application, the event camera is integrated into the conventional camera to form an imaging device. That is, the imaging device integrates the conventional camera and the event camera, or it can be understood as embedding the photosensitive element of the event camera into the visual sensor of the conventional camera, so that the visual sensor has the ability to output event data and conventional CMOS image data at the same time.

[0061] 102. Perform motion detection on the preview image to identify texture change areas in the preview image.

[0062] Motion detection of the preview image refers to identifying texture change region information from the preview image. Texture change region information refers to the region information in the preview image where the texture changes. This region information refers to the pixel coordinate information in the preview image, such as the position information or coordinate information of the pixels in the preview image where the texture changes.

[0063] Image texture variation refers to how texture features in an image change over time or under different conditions. Texture is a recurring pattern or pattern in an image; it can be lines, dots, shapes, etc., and these patterns or patterns can be regular, random, or semi-regular. Texture variation can be caused by a variety of factors, including lighting conditions, viewing angle, the physical properties of the object's surface, background noise, camera shake, or the motion properties of the object itself. For example, when there is a moving object in a scene, the preview image for that scene will contain areas of texture variation corresponding to that object.

[0064] 103. Filter the brightness change events based on the texture change region information to obtain static brightness change events. Since the main objective of this embodiment is to analyze the light source frequency, after recording the brightness change events, it is necessary to filter out brightness change events not caused by light source flicker to eliminate the influence of motion noise on the light source frequency calculation. Therefore, in this embodiment, after identifying the texture change region information in the preview image, the brightness change events are filtered based on this texture change region information to obtain static brightness change events. In this embodiment, the static brightness change event refers to the brightness change event recorded by the event camera based on the flicker of the target light source in the target scene. The target scene refers to the environment where the shooting location is located. The light source frequency, also known as the flicker frequency, refers to the flicker frequency of artificial light sources (such as fluorescent lamps), typically 50Hz or 60Hz. This flicker frequency is generally related to the AC power supply frequency, and different countries or regions may have different standards. Correspondingly, a brightness change threshold can be set for the event camera to record brightness change events. For example, the event camera will only record the brightness change event corresponding to the brightness change when the brightness of the light source flickers exceeds the set threshold, so as to control the event camera to capture valid brightness change events.

[0065] 104. Generate the target light source frequency information of the target scene based on the static brightness change event.

[0066] Since the static brightness change event is based on the stroboscopic recording of the light source, the frequency of the light source's flicker can be determined based on this static brightness change event, thereby obtaining the target light source's frequency information.

[0067] In summary, the embodiments of this application, by recording brightness change events corresponding to preview images, facilitate the automated analysis and generation of brightness change frequency information based on these events. Specifically, by identifying texture change regions in the preview image and filtering brightness change events based on this information, motion interference in the scene can be eliminated, achieving effective screening of static brightness change events. Furthermore, based on these effective static brightness change events, accurate target light source frequency information can be generated, improving the accuracy of the target light source frequency information.

[0068] Optionally, since the event time information and brightness change area information of the brightness change event are recorded simultaneously when recording the brightness change event, the event time information and brightness change area information can be matched with the texture change area information. The motion brightness change events corresponding to the brightness change area information that matches the texture change area information are then filtered to obtain static brightness change events. That is, optionally, in some embodiments of this application, the brightness change event corresponds to brightness change area information and event time information. The step "filtering the brightness change event according to the texture change area information to obtain static brightness change events" includes:

[0069] Based on the brightness change region information, the texture change region information, and the event time information, filter motion brightness change events from the brightness change events;

[0070] Filter out the motion brightness change events from the brightness change events to obtain the static brightness change events.

[0071] It should be noted that the event time information is the timestamp information corresponding to the recorded brightness change event, which reflects the start and end timestamp information of the light source flickering.

[0072] Additionally, the brightness change area information records the area information of the brightness change event in the target scene or preview image, such as the position information of the light source. The event time information and brightness change area information are detailed information generated by the event camera when it captures a brightness change event caused by light source flickering. These details record the characteristics of the brightness change event, i.e., the time and location corresponding to the brightness change event.

[0073] Optionally, since the static brightness change event is obtained by filtering out scene motion interference from the brightness change event, the static brightness change event is for the static area of ​​the light source flickering. Therefore, the target light source frequency information can be directly calculated based on the time information corresponding to the static brightness change event. That is, optionally, in some embodiments of this application, the step "generating the target light source frequency information of the target scene based on the static brightness change event" includes:

[0074] The event duration information is obtained based on the event time information of each static brightness change event;

[0075] Calculate the mean of the event duration information for each of the static brightness change events to obtain the average event duration information;

[0076] The target light source frequency information of the target scene is generated based on the average event duration information.

[0077] Based on the start and end timestamps corresponding to the event time information, the event duration can be calculated. The average duration of the light source flicker can be calculated by averaging the durations of various static brightness change events. Correspondingly, the frequency corresponding to the average duration can be calculated by reciprocal, i.e., the target light source frequency information, which is also the flicker frequency f of the light source. flicker , can be represented as: f flicker =1 / T mean

[0078] Among them, T mean It is the average duration of static brightness change events.

[0079] Optionally, in this embodiment, texture change region information can be determined by the pixel difference between temporally adjacent preview images. That is, optionally, in some embodiments of this application, the step "performing motion detection on the preview image to identify texture change region information in the preview image" includes:

[0080] Calculate the difference between each pixel in adjacent preview images to obtain the pixel difference;

[0081] The target pixel is determined from the preview image based on a preset threshold and the pixel difference.

[0082] The position information corresponding to the target pixel is used as the texture change region information.

[0083] By calculating the pixel difference between adjacent preview images, it is possible to determine whether a pixel has changed. For example, if the pixel difference is greater than a preset threshold, the pixel is considered to have changed. Accordingly, the pixel is taken as the target pixel, and the position information of each target pixel is used as the texture change area information.

[0084] Furthermore, in this embodiment, optical flow or deep learning models can also be used to identify texture variation regions in the preview image.

[0085] Accordingly, after calculating the target light source frequency information of the target scene, an anti-striping processing strategy can be determined based on the target light source frequency information, and the preview image can be processed based on the anti-striping processing strategy. That is, optionally, in some embodiments of this application, after the step of "generating the target light source frequency information of the target scene based on the static brightness change event", the method further includes:

[0086] Determine the anti-striping processing strategy based on the target light source frequency information;

[0087] The preview image is subjected to anti-striping processing according to the aforementioned anti-striping processing strategy to obtain the target image;

[0088] In response to an image capture command, the target image is captured.

[0089] Banding, also known as stripes, occurs when the flicker of an artificial light source (such as fluorescent light) is out of sync with the camera's shutter speed, resulting in alternating horizontal or vertical stripes or bands of light and dark in an image. Banding can be identified using image recognition tools (such as image recognition software or image recognition APIs) or through trained image recognition models (machine learning models). Banding possesses information such as location, quantity, and width, and affects image quality.

[0090] In this embodiment, the anti-striping processing strategy is a strategy or method for eliminating stripes in an image. The anti-striping processing strategy may include exposure time-based adjustment algorithms, image analysis-based interpolation or filtering algorithms, and machine learning-based optimization algorithms. It is understood that the anti-striping processing strategy may also be a combination of one or more of the aforementioned algorithms. By selecting an anti-striping processing strategy that matches the frequency information of the target light source at the time of shooting, when image stripe elimination processing is performed based on the selected anti-striping processing strategy, the impact of stripes on the image can be more effectively eliminated or reduced, improving image quality.

[0091] For example, exposure time refers to the duration of time the camera shutter is open, specifically the length of time the shutter is open and allows light to reach the image sensor (such as a sensor or film). Exposure time is crucial for photographic creation, affecting image brightness, dynamic range, and the ability to capture moving objects, thus determining image brightness and sharpness. Exposure time is usually expressed in seconds or fractions of a second, such as 1 / 60 second, 1 / 125 second, 1 / 250 second, etc. The smaller the value, the shorter the exposure time; the larger the value, the longer the exposure time.

[0092] It should be noted that the relationship between exposure time and light source frequency also affects image quality. For example, if the exposure time is an integer multiple of the light source frequency, it can effectively eliminate or reduce stripes in the image and improve image quality. Therefore, once the target light source frequency information of the target scene is determined, the exposure time can be adjusted based on the target light source frequency information to make the exposure time an integer multiple of the light source frequency, thereby solving the stripe defect in the image and improving image quality.

[0093] Optionally, in this embodiment of the application, when capturing a preview image after the shooting device is started, the exposure time of the shooting device can be adjusted based on the historical light source frequency information of the target scene, and the image shooting can be controlled based on the exposure time. It is hoped that the previously determined historical light source frequency information and exposure time of the target scene can be directly used to capture a preview image with fewer stripes and higher quality.

[0094] Therefore, a preview image can be captured by first determining a preset exposure time based on the historical light source frequency information of the target scene, and then analyzed to determine whether it meets the quality conditions through quality detection. That is, optionally, in some embodiments of this application, the step "in response to the start operation of the shooting device, acquire a preview image of the target scene, and record the brightness change event corresponding to the preview image" includes:

[0095] In response to the start operation of the shooting device, a preview image of the target scene is acquired through a preset exposure time, and the brightness change event corresponding to the preview image is recorded. The preset exposure time is determined based on the historical preview images and historical brightness change events of the target scene.

[0096] The step of performing motion detection on the preview image to identify texture change regions in the preview image includes:

[0097] The preview image is subjected to quality inspection to obtain the quality inspection result;

[0098] If the quality detection result of the preview image does not meet the preset conditions, motion detection is performed on the preview image to identify texture change areas in the preview image.

[0099] The preset exposure time can be determined by recognizing the preview image. For example, after the shooting device is turned on, the first few frames of preview images are captured. The first few frames of preview images are used to determine whether the current shooting scene is the target scene. If it is the target scene, the historical light source frequency information is determined by the historical preview images and historical brightness change events of the target scene, and then the preset exposure time is determined based on the historical light source frequency information.

[0100] Quality inspection can be achieved through methods such as image recognition. For example, by recognizing an image, analyzing whether it contains stripes, and determining information such as the position, number, and width of the stripes, the corresponding quality inspection result can be obtained. The quality inspection result can be presented as a quality score, with higher quality scores corresponding to higher image quality. The quality score is determined based on factors such as the position, number, width, and depth of the stripes.

[0101] Optionally, in this embodiment of the application, there may be shooting needs of multiple shooting devices for the same target scene. Therefore, for shooting situations of multiple shooting devices in the same target scene, the target light source frequency of the target scene can be quickly obtained by sharing the target light source frequency information between the devices. For example, receiving reference light source frequency information pushed by other shooting devices and reference scene information corresponding to the reference light source frequency information; if the reference scene information is consistent with the scene information of the target scene, the reference light source frequency information is output to the screen of the shooting device; in response to the selection operation of the reference light source frequency information on the screen, the reference light source frequency information is used as the target light source frequency information.

[0102] Among them, by receiving reference scene information and reference light source frequency information shared by other devices, the determination of target light source frequency information for the shooting device in the target scene can be accelerated.

[0103] Correspondingly, for current shooting devices, after calculating the target light source frequency information through preview images and brightness change events, it can also be pushed or shared with other devices. For example, after "generating the target light source frequency information of the target scene based on the static brightness change events", the method further includes:

[0104] The scene information of the target scene and the frequency information of the target light source are pushed to other shooting devices within a preset broadcast range;

[0105] It is understandable that the preset broadcast range indicates that the multiple shooting devices are basically in the target scene, or that the scene in which the multiple shooting devices are shooting is basically the target scene.

[0106] The push of the target light source frequency information and scene information must meet the corresponding device permissions or privacy terms, and can only be pushed or received with the user's permission.

[0107] The camera can also upload the target light source frequency information and scene information to a server. This server can be a local area network (LAN) for the target scene. The target light source frequency information and scene information uploaded by a single camera can be distributed or forwarded to other camera devices in the LAN through LAN distribution.

[0108] In summary, the embodiments of this application, by recording brightness change events corresponding to preview images, facilitate the automated analysis and generation of brightness change frequency information based on these events. Specifically, by identifying texture change regions in the preview image and filtering brightness change events based on this information, motion interference in the scene can be eliminated, achieving effective screening of static brightness change events. Furthermore, based on these effective static brightness change events, accurate target light source frequency information can be generated, improving the accuracy of the target light source frequency information.

[0109] This involves capturing preview images with a traditional camera and recording brightness change events with an event camera, then collaboratively calculating the target light source frequency information of the target scene. This achieves the calculation of target light source frequency information based on a combination of traditional and event cameras.

[0110] To facilitate understanding of the information acquisition method of this application embodiment, the following description will focus on the overall solution of this application embodiment. Please refer to Figure 3, which is an architecture diagram of the information acquisition system corresponding to the information acquisition method provided in this application embodiment. The information acquisition system includes:

[0111] The startup module 201 is used to simultaneously start the image preview module 202 and the event recording module 204 in response to the startup operation of the shooting device.

[0112] Image preview module 202 is used to obtain a preview image by using a conventional camera at 30fps;

[0113] The motion detection module 203 is used to perform motion detection on the preview image obtained by the image preview module 202 in order to identify texture change region information in the preview image;

[0114] Event logging module 204 is used to acquire event stream data within a preset time period via an event camera at 600fps;

[0115] Event building module 205 is used to parse brightness change events from event stream data;

[0116] Event filtering module 206 is used to filter brightness change events based on texture change area information to obtain static brightness change events;

[0117] The flicker calculation module 207 is used to calculate the target light source frequency information of the target scene based on the static brightness change event. Correspondingly, after calculating the target light source frequency information, the capturing device can determine an anti-striping processing strategy based on this information and apply it to the preview image to obtain the target image. Specifically, the target light source frequency information of the target scene is calculated collaboratively by capturing the preview image with a traditional camera and recording the brightness change event with an event camera, achieving the calculation of the target light source frequency information using a combination of traditional and event cameras.

[0118] To facilitate better implementation of the information acquisition method of this application, this application also provides an information acquisition device based on the above-described information acquisition method. The meanings of the terms used are the same as in the information acquisition method described above, and specific implementation details can be found in the descriptions of the method embodiments.

[0119] Please refer to Figure 4, which is a schematic diagram of the structure of the information acquisition device provided in the embodiment of this application. The information acquisition device is applied to a shooting device, and can be specifically as follows:

[0120] The acquisition module 301 is used to acquire a preview image of the target scene in response to the start operation of the shooting device, and to record the brightness change event corresponding to the preview image;

[0121] The recognition module 302 is used to perform motion detection on the preview image in order to identify texture change region information in the preview image;

[0122] Filtering module 303 is used to filter the brightness change event based on the texture change area information to obtain static brightness change event;

[0123] The generation module 304 is used to generate target light source frequency information of the target scene based on the static brightness change event. Optionally, in some embodiments of this application, the brightness change event corresponds to brightness change area information and event time information, and the filtering module 303 includes:

[0124] A filtering unit is used to filter motion brightness change events from the brightness change events based on the brightness change region information, the texture change region information, and the event time information.

[0125] A filtering unit is used to filter out the motion brightness change events from the brightness change events to obtain static brightness change events.

[0126] In some embodiments of this application, the generation module 304 includes:

[0127] The information acquisition unit is used to obtain event duration information based on the event time information of each of the static brightness change events;

[0128] The duration calculation unit is used to calculate the average event duration information of each of the static brightness change events to obtain the average event duration information;

[0129] The generation unit is used to generate target light source frequency information of the target scene based on the average event duration information.

[0130] In some embodiments of this application, the identification module 302 includes:

[0131] The difference calculation unit is used to calculate the difference between each pixel in adjacent preview images to obtain the pixel difference.

[0132] A pixel determination unit is used to determine a target pixel from the preview image based on a preset threshold and the pixel difference;

[0133] The information determination unit is used to use the position information corresponding to the target pixel as texture change region information.

[0134] In some embodiments of this application, the shooting device integrates an event camera, and the acquisition module 301 includes:

[0135] The event acquisition unit is used to respond to the start operation of the shooting device, acquire a preview image of the target scene through a conventional camera, and simultaneously capture an event in which the brightness change exceeds a preset brightness threshold through the event camera to obtain a brightness change event.

[0136] In some embodiments of this application, the device further includes a correction module, which includes:

[0137] The strategy determination unit is used to determine an anti-striping processing strategy according to the target light source frequency information;

[0138] The processing unit is used to perform anti-striping processing on the preview image according to the anti-striping processing strategy to obtain the target image; the capturing unit is used to capture the target image in response to the image capturing command.

[0139] In some embodiments of this application, the acquisition module 301 includes:

[0140] A response unit is configured to respond to a startup operation of the shooting device, acquire a preview image of the target scene through a preset exposure time, and record the brightness change event corresponding to the preview image. The preset exposure time is determined based on historical preview images and historical brightness change events of the target scene.

[0141] The recognition module 302 includes:

[0142] A quality detection unit is used to perform quality detection on the preview image and obtain the quality detection result;

[0143] The motion detection unit is used to perform motion detection on the preview image if the quality detection result of the preview image does not meet the preset conditions, so as to identify the texture change area information in the preview image.

[0144] In this embodiment, the acquisition module 301, in response to a startup operation of the shooting device, acquires a preview image of the target scene and records the brightness change events corresponding to the preview image. Next, the recognition module 302 performs motion detection on the preview image to identify texture change regions. Then, the filtering module 303 filters the brightness change events based on the texture change region information to obtain static brightness change events. Finally, the generation module 304 generates target light source frequency information for the target scene based on the static brightness change events. This embodiment, by recording the brightness change events corresponding to the preview image, facilitates the automated analysis and generation of brightness change frequency information based on these events. Furthermore, by identifying texture change regions in the preview image and filtering brightness change events based on this information, motion interference in the scene is eliminated, achieving effective screening of static brightness change events. Based on these effective static brightness change events, accurate target light source frequency information can be generated, improving the accuracy of the target light source frequency information.

[0145] In addition, this application also provides an electronic device, as shown in Figure 5, which illustrates the structural schematic diagram of the electronic device involved in this application. Specifically:

[0146] The electronic device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will understand that the electronic device structure shown in FIG5 does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0147] The processor 401 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 402, and by calling data stored in the memory 402, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Optionally, the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 401. The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback, image playback, etc.), etc.; the data storage area may store data created based on the use of the electronic device. Furthermore, memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory 402 may also include a memory controller to provide processor 401 with access to memory 402.

[0148] The electronic device also includes a power supply 403 that supplies power to the various components. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 403 may also include one or more DC or AC power supplies, recharging systems, power equipment debugging circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0149] The electronic device may further include an input unit 404, which can be used to receive input numerical or character information and generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable files corresponding to the processes of one or more application programs into the memory 402 according to the following instructions, and the processor 401 runs the application programs stored in the memory 402, thereby implementing the steps in any of the information acquisition methods provided in the embodiments of this application.

[0150] The imaging device in this embodiment of the application, in response to a startup operation, acquires a preview image of the target scene and records the brightness change events corresponding to the preview image. It then performs motion detection on the preview image to identify texture change regions, filters the brightness change events based on the texture change region information to obtain static brightness change events, and generates target light source frequency information for the target scene based on these static brightness change events. Recording the brightness change events corresponding to the preview image facilitates the automated analysis and generation of brightness change frequency information. Identifying texture change regions in the preview image and filtering brightness change events based on this information helps eliminate motion interference in the scene, achieving effective screening of static brightness change events. Furthermore, based on these effective static brightness change events, accurate target light source frequency information can be generated, improving the accuracy of the target light source frequency information.

[0151] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0152] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0153] Therefore, this application provides a computer-readable storage medium storing a computer program that can be loaded by a processor to execute the steps in any of the information acquisition methods provided in this application.

[0154] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0155] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0156] Since the instructions stored in the computer-readable storage medium can execute the steps of any of the information acquisition methods provided in this application, the beneficial effects that any of the information acquisition methods provided in this application can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0157] The above provides a detailed description of an information acquisition method, apparatus, electronic device, and computer-readable storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, those skilled in the art will recognize that there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

[0158] It should be noted that, in the specific embodiments of this application, data related to preview images, target scenes, brightness change events, texture change area information, brightness change area information, event time information, and pixel differences are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions.

Claims

1. An information acquisition method, wherein, Applied to a shooting device, the method comprises: In response to a starting operation for the shooting device, a preview image for a target scene is acquired, and a brightness change event corresponding to the preview image is recorded; Motion detection is performed on the preview image to identify texture change region information in the preview image; The brightness change event is filtered according to the texture change region information to obtain a static brightness change event; Target light source frequency information of the target scene is generated according to the static brightness change event.

2. The information acquisition method according to claim 1, wherein The brightness change event corresponds to brightness change region information and event time information, and the filtering of the brightness change event according to the texture change region information to obtain a static brightness change event comprises: Motion brightness change events are screened from the brightness change event according to the brightness change region information, the texture change region information and the event time information; The motion brightness change events are filtered from the brightness change event to obtain a static brightness change event.

3. The information acquisition method according to claim 1, wherein The generation of the target light source frequency information of the target scene according to the static brightness change event comprises: Event duration information is obtained according to the event time information of each static brightness change event; The average event duration information is obtained by calculating the average of the event duration information of each static brightness change event; The target light source frequency information of the target scene is generated according to the average event duration information.

4. The information acquisition method according to claim 1, wherein The motion detection on the preview image to identify the texture change region information in the preview image comprises: Pixel differences are calculated for each pixel in adjacent preview images to obtain pixel differences; A target pixel is determined from the preview image according to a preset threshold and the pixel differences; Position information corresponding to the target pixel is taken as the texture change region information.

5. The information acquisition method according to claim 1, wherein The shooting device is integrated with an event camera, and the acquisition of the preview image for the target scene and the recording of the brightness change event corresponding to the preview image in response to the starting operation for the shooting device comprises: In response to the starting operation for the shooting device, a preview image for the target scene is acquired by a traditional camera, and a brightness change event is captured by the event camera when the brightness change exceeds a preset brightness threshold.

6. The information acquisition method according to claim 1, wherein After the generation of the target light source frequency information of the target scene according to the static brightness change event, the method further comprises: An anti-streak processing strategy is determined according to the target light source frequency information; An anti-streak processing is performed on the preview image according to the anti-streak processing strategy to obtain a target image; In response to an image shooting instruction, the target image is shot.

7. The information acquisition method according to claim 1, wherein The acquisition of the preview image for the target scene and the recording of the brightness change event corresponding to the preview image in response to the starting operation for the shooting device comprises: In response to the starting operation for the shooting device, a preview image for the target scene is acquired by a preset exposure time, and a brightness change event corresponding to the preview image is recorded, wherein the preset exposure time is determined based on historical preview images and historical brightness change events of the target scene.

8. The information acquisition method according to claim 7, wherein The motion detection is performed on the preview image to identify texture change region information in the preview image, including: performing quality detection on the preview image to obtain a quality detection result; if the quality detection result of the preview image does not satisfy a preset condition, performing motion detection on the preview image to identify texture change region information in the preview image.

9. The information acquisition method according to Claim 1, wherein The luminance change event is an event recorded when luminance change occurs in a target scene photographed by the photographing device.

10. The information acquisition method according to claim 5, wherein The photographing device includes the traditional camera and the event camera, and the event camera is integrated in the traditional camera.

11. The information acquisition method according to claim 10, wherein The event camera is integrated in the traditional camera, including: The light-sensitive component of the event camera is embedded in the visual sensor of the traditional camera.

12. The information acquisition method according to claim 1, wherein The texture includes at least one of a line, a point, and a shape in an image.

13. The information acquisition method according to claim 2, wherein The event time information and the luminance change region information are detailed information generated by the event camera when the event camera collects light source flicker to generate a luminance change event, and are used to record characteristics of the luminance change event. The event time information includes a time corresponding to the luminance change event, and the luminance change region information includes a position corresponding to the luminance change event.

14. The information acquisition method according to claim 1, wherein The method further includes identifying the texture change region information in the preview image by using an optical flow method or a deep learning model.

15. The information acquisition method according to claim 1, wherein After the target light source frequency information of the target scene is generated according to the static luminance change event, the method further includes: pushing the scene information of the target scene and the target light source frequency information to other photographing devices within a preset broadcast range.

16. An information acquisition apparatus, wherein, The device is applied to a photographing device, and includes: an acquisition module configured to, in response to a start operation of the photographing device, acquire a preview image of a target scene, and record a luminance change event corresponding to the preview image; an identification module configured to perform motion detection on the preview image to identify texture change region information in the preview image; a filtering module configured to filter the luminance change event according to the texture change region information to obtain a static luminance change event; a generation module configured to generate target light source frequency information of the target scene according to the static luminance change event.

17. The information acquisition apparatus according to claim 16, wherein The luminance change event corresponds to luminance change region information and event time information, and the filtering of the luminance change event according to the texture change region information to obtain a static luminance change event includes: screening a motion luminance change event from the luminance change event according to the luminance change region information, the texture change region information, and the event time information; filtering out the motion luminance change event from the luminance change event to obtain a static luminance change event.

18. The information acquisition apparatus according to claim 16, wherein The generation of the target light source frequency information of the target scene according to the static luminance change event includes: obtaining event duration information according to event time information of each static luminance change event; calculating a mean value of the event duration information of each static luminance change event to obtain average event duration information; generating the target light source frequency information of the target scene according to the average event duration information.

19. An electronic device, comprising: A computer program product, comprising a computer readable storage medium having stored thereon computer program means, the computer program means comprising instructions executable by a processor to cause the processor to perform the steps of the information acquisition method according to any one of claims 1-15.

20. A computer readable storage medium, wherein, A computer readable storage medium having stored thereon a computer program, the computer program comprising instructions executable by a processor to cause the processor to perform the steps of the information acquisition method according to any one of claims 1-15.

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