Image acquisition method, image acquisition device, storage medium and program product

Abstract

The invention provides an image acquisition method, an image acquisition device, a storage medium and a program product. The method is applied to the intelligent monitoring equipment and comprises the steps that the current exposure parameter of the intelligent monitoring equipment is obtained, and the current exposure parameter is the exposure parameter of a current picture collected by the intelligent monitoring equipment at the current moment; determining whether the current exposure parameter is greater than a parameter threshold; when the current exposure parameter is greater than a parameter threshold, adjusting a current brightness value of a target scene in the current picture to obtain a target brightness value, and adjusting the current exposure parameter according to the target brightness value and the prepared brightness value to obtain a target exposure parameter; under the condition that the current exposure parameter is smaller than or equal to a parameter threshold value, determining a target exposure parameter according to the current brightness value, the prepared brightness value and the parameter threshold value; and collecting a target image according to the target exposure parameter. The problem that in the prior art, an intelligent monitoring camera cannot accurately recognize objects and details in a picture in a backlight environment is solved.

Description

Technical Field

[0001] The present application relates to the field of image acquisition, and in particular, to an image acquisition method, an image acquisition device, a computer-readable storage medium, and a computer program product. Background Art

[0002] Surveillance cameras have the advantages of high sensitivity, strong light resistance, small distortion, small size, long life, and vibration resistance. In the surveillance camera security system, the image generation is currently mainly from the CCD camera, and the stored charge can also be taken out to change the voltage. It has the characteristics of vibration and impact resistance and is widely used. The camera is currently the fastest growing sensor in the ADAS field, and the dynamic parameters of the camera's shooting picture are the basis of the sensor's work, which directly determines the accuracy of the camera's shooting picture; however, in actual use, the existing intelligent surveillance camera automatically adjusts the low beam amount when capturing the picture according to the overall picture. In a general environment, the image obtained by the surveillance camera is sufficient for subsequent processing to complete the corresponding function, but in a backlit environment, due to the need to balance the brightness of the entire picture, the main part of the picture may be dark, and the objects in the picture cannot be identified, let alone the details, which affects the normal use of the surveillance camera and causes safety hazards.

[0003] Therefore, there is an urgent need for an image acquisition method that can overcome the above problems. Summary of the invention

[0004] The main purpose of the present application is to provide an image acquisition method, an image acquisition device, a computer-readable storage medium and a computer program product, so as to at least solve the problem in the prior art that intelligent surveillance cameras cannot accurately identify objects and details in the picture in a backlit environment.

[0005] According to one aspect of the present application, an image acquisition method is provided, which is applied to an intelligent monitoring device, and the method includes: obtaining a current exposure parameter of the intelligent monitoring device, the current exposure parameter being an exposure parameter of a current picture acquired by the intelligent monitoring device at a current moment; determining whether the current exposure parameter is greater than a parameter threshold; if the current exposure parameter is greater than the parameter threshold, adjusting a current brightness value of a target scene in the current picture to obtain a target brightness value, and adjusting the current exposure parameter according to the target brightness value and a preliminary brightness value to obtain a target exposure parameter, the current picture including a plurality of scenes, the target scene being any one of the plurality of scenes, and the preliminary brightness value being a brightness value of other scenes among the plurality of scenes except the target scene; if the current exposure parameter is less than or equal to the parameter threshold, determining the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold; and acquiring a target image according to the target exposure parameter.

[0006] Optionally, when the current exposure parameter is greater than the parameter threshold, the current brightness value of the target scene in the current picture is adjusted to obtain a target brightness value, including: segmenting the current picture to obtain multiple segmented pictures, wherein one segmented picture includes at least one scene; obtaining the brightness value of each segmented picture to obtain multiple scene brightness values; obtaining the brightness value of the same scene in different historical pictures to obtain multiple historical brightness values, wherein the historical pictures are pictures collected by the intelligent monitoring device before the current moment; calculating the average of the multiple historical brightness values ​​to obtain a brightness threshold; adjusting the current brightness value according to the brightness threshold and the current brightness value to obtain the target brightness value.

[0007] Optionally, the current brightness value is adjusted according to the brightness threshold and the current brightness value to obtain the target brightness value, including: determining whether the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold; when the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold, adjusting the current brightness value to be closer to the brightness threshold to obtain the target brightness value; when the absolute value of the difference between the current brightness value and the brightness threshold is less than or equal to the absolute value threshold, determining the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold.

[0008] Optionally, when the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold, the current brightness value is adjusted to be closer to the brightness threshold to obtain the target brightness value. The method also includes: according to the target brightness value, reducing the brightness value of the exposure point in the current picture to obtain the exposure point brightness value.

[0009] Optionally, adjusting the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain the target exposure parameter includes: a first fusion step of fusing the target brightness value and the preliminary brightness value to obtain a fused brightness value of the target scene, wherein the fusion process includes one of weighted averaging, histogram equalization and local contrast enhancement, the segmented screen corresponding to the target scene is the target segmented screen, and the preliminary brightness value is the brightness value of the segmented screen adjacent to the target segmented screen; a first repetition step of repeating the first fusion step at least once until all the segmented screens in the current screen are traversed to obtain a plurality of fused brightness values; and a first adjustment step of adjusting the current exposure parameter according to the average value of the plurality of fused brightness values ​​to obtain the target exposure parameter.

[0010] Optionally, when the current exposure parameter is less than or equal to the parameter threshold, the target exposure parameter is determined according to the current brightness value, the preliminary brightness value and the parameter threshold, including: a second fusion step of fusing the target brightness value, the preliminary brightness value and the parameter threshold to obtain a fused brightness value of the target scene, wherein the fusion processing includes one of weighted averaging, histogram equalization and local contrast enhancement, the segmented screen corresponding to the target scene is the target segmented screen, and the preliminary brightness value is the brightness value of the segmented screen adjacent to the target segmented screen; a second repetition step of repeating the second fusion step at least once until all the segmented screens in the current screen are traversed to obtain multiple fused brightness values; a second adjustment step of adjusting the current exposure parameter according to the average value of the multiple fused brightness values ​​to obtain the target exposure parameter.

[0011] Optionally, capturing a target image according to the target exposure parameters includes: determining, according to the target exposure parameters, capture parameters of the intelligent monitoring device to capture the target image, the capture parameters including at least one of a shutter speed, an aperture size, and an ISO sensitivity.

[0012] According to another aspect of the present application, an image acquisition device is provided, which is applied to an intelligent monitoring device, and the device includes: an acquisition unit, which is used to acquire a current exposure parameter of the intelligent monitoring device, wherein the current exposure parameter is an exposure parameter of a current picture acquired by the intelligent monitoring device at a current moment; a first determination unit, which is used to determine whether the current exposure parameter is greater than a parameter threshold; an adjustment unit, which is used to adjust a current brightness value of a target scene in the current picture to obtain a target brightness value when the current exposure parameter is greater than the parameter threshold, and adjust the current exposure parameter according to the target brightness value and a preliminary brightness value to obtain a target exposure parameter, wherein the current picture includes a plurality of scenes, the target scene is any one of the plurality of scenes, and the preliminary brightness value is a brightness value of other scenes among the plurality of scenes except the target scene; a second determination unit, which is used to determine the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold when the current exposure parameter is less than or equal to the parameter threshold; and an acquisition unit, which is used to acquire a target image according to the target exposure parameter.

[0013] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0014] According to another aspect of the present application, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of any one of the methods described are implemented.

[0015] The technical solution of the present application is applied to provide an image acquisition method. First, the current exposure parameter of the intelligent monitoring device is obtained, and the current exposure parameter is the exposure parameter of the current picture collected by the intelligent monitoring device at the current moment; determine whether the current exposure parameter is greater than the parameter threshold; then, when the current exposure parameter is greater than the parameter threshold, adjust the current brightness value of the target scene in the current picture to obtain the target brightness value, and adjust the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain the target exposure parameter; then, when the current exposure parameter is less than or equal to the parameter threshold, determine the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold; finally, collect the target image according to the target exposure parameter. By judging the size relationship between the current exposure parameter and the parameter threshold, when the current exposure parameter exceeds the parameter threshold, the brightness value of the current picture scene is automatically adjusted to a reasonable range, and the brightness value of the scene after adjustment is fused with the brightness value of other current positions to automatically adjust the exposure parameter of the entire picture. Collecting the target image according to the adjusted exposure parameter can improve the picture processing efficiency, shorten the picture correction time, further improve the picture refresh rate and the picture softness, and ensure that high-quality monitoring images can be obtained even in complex environments such as backlight. The problem that the intelligent monitoring camera in the prior art cannot accurately identify objects and details in the picture under backlight environment is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for executing an image acquisition method provided in an embodiment of the present application is shown;

[0018] Figure 2 A schematic diagram of a process of an image acquisition method provided according to an embodiment of the present application is shown;

[0019] Figure 3 A structural block diagram of an image acquisition device provided according to an embodiment of the present application is shown.

[0020] The above drawings include the following reference numerals:

[0021] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0022] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that 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 are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] As introduced in the background technology, in the prior art, smart surveillance cameras cannot accurately identify objects and details in the picture under backlighting conditions. To solve the above problem, the embodiments of the present application provide an image acquisition method, an image acquisition device, a computer-readable storage medium and a computer program product.

[0026] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0027] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal of an image acquisition method according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0028] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the image acquisition method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific example of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0029] In this embodiment, an image acquisition method running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] Figure 2 FIG. 1 is a flow chart of an image acquisition method according to an embodiment of the present application. Figure 2 As shown, the above method is applied to an intelligent monitoring device, and the method comprises the following steps:

[0031] Step S201, obtaining the current exposure parameter of the intelligent monitoring device, where the current exposure parameter is the exposure parameter of the current picture collected by the intelligent monitoring device at the current moment;

[0032] Specifically, when the camera monitors the target position angle, it obtains the exposure parameters of the current picture in real time and records them.

[0033] Step S202, determining whether the above current exposure parameter is greater than a parameter threshold;

[0034] Specifically, the above parameter threshold settings are related to the type of intelligent monitoring equipment.

[0035] Step S203, when the current exposure parameter is greater than the parameter threshold, adjusting the current brightness value of the target scene in the current picture to obtain a target brightness value, and adjusting the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain a target exposure parameter, the current picture includes a plurality of scenes, the target scene is any one of the plurality of scenes, and the preliminary brightness value is the brightness value of the other scenes among the plurality of scenes except the target scene;

[0036] Specifically, when the above-mentioned current exposure parameter is greater than the above-mentioned parameter threshold, that is, the current picture is in a backlit state, resulting in the exposure parameter and brightness of the current picture being much greater than the calculated exposure parameter and brightness value, the brightness of the scene in the current picture that is the same as that in the previous frame will be automatically adjusted, so as to facilitate the adjustment of the overall brightness and exposure of the entire picture as a reference.

[0037] Step S204, when the current exposure parameter is less than or equal to the parameter threshold, determining the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold;

[0038] Specifically, when the current exposure parameter is less than or equal to the parameter threshold, that is, when the current picture is not backlit, the overall exposure parameter in the current picture is adjusted to improve the refresh rate and softness of the picture.

[0039] Step S205: acquiring a target image according to the target exposure parameters.

[0040] Specifically, when all target exposure parameters are set and the preview is confirmed to be correct, the camera will formally capture the target image. At this time, the camera will capture the image according to the set exposure parameters to ensure that the brightness, contrast and details of the image are optimally presented.

[0041] Through this embodiment, an image acquisition method is provided. First, the current exposure parameter of the intelligent monitoring device is obtained, and the current exposure parameter is the exposure parameter of the current picture collected by the intelligent monitoring device at the current moment; determine whether the current exposure parameter is greater than the parameter threshold; then, when the current exposure parameter is greater than the parameter threshold, adjust the current brightness value of the target scene in the current picture to obtain the target brightness value, and adjust the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain the target exposure parameter; then, when the current exposure parameter is less than or equal to the parameter threshold, determine the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold; finally, acquire the target image according to the target exposure parameter. By judging the magnitude relationship between the current exposure parameter and the parameter threshold, when the current exposure parameter exceeds the parameter threshold, the brightness value of the current picture scene is automatically adjusted to a reasonable range, and the brightness value of the scene after adjustment is fused with the brightness value of other current positions to automatically adjust the exposure parameter of the entire picture. Acquiring the target image according to the adjusted exposure parameter can improve the picture processing efficiency, shorten the picture correction time, further improve the picture refresh rate and the picture softness, and ensure that high-quality monitoring images can be obtained even in complex environments such as backlight. The problem that the intelligent monitoring camera in the prior art cannot accurately identify objects and details in the picture under backlight environment is solved.

[0042] In the specific implementation process, the above step S203 can be implemented by the following steps: step S2031, segmenting the above current picture to obtain multiple segmented pictures, wherein one segmented picture includes at least one of the above scenes; step S2032, obtaining the brightness value of each of the above segmented pictures to obtain multiple scene brightness values; step S2033, obtaining the brightness value of the same scene in different historical pictures to obtain multiple historical brightness values, wherein the above historical pictures are pictures collected by the above intelligent monitoring device before the above current moment; step S2034, calculating the average value of the above historical brightness values ​​to obtain a brightness threshold; step S2035, adjusting the above current brightness value according to the above brightness threshold and the above current brightness value to obtain the above target brightness value. This method can further improve the picture processing efficiency, shorten the picture correction time, and improve the accuracy and efficiency of automatic adjustment.

[0043] Specifically, when the camera always divides the picture into grids during the shooting process, the brightness values ​​and exposure parameters of different grids are determined. When encountering backlight, the exposure and range in the picture, as well as the change in the brightness of the scenes in different grids, are known through the changes in the brightness values ​​and exposure parameters of different grids, so as to facilitate the automatic adjustment of the brightness of the scenes in the grids and the exposure and exposure range in the picture in the later stage. In addition, the brightness and exposure of the next frame can be calculated in advance, so that when the camera records the next frame, it can be directly compared and adjusted. The preset threshold of the brightness value of the current foreground object is a certain range of the average value of the brightness value of the same scene in the previous multiple frames. The brightness threshold of the scene in the current picture is not fixed, but changes with the overall environment in the current picture, which does not affect the overall movement of the picture and the picture accuracy of the shooting record, and improves the correction efficiency and stability.

[0044] The above step S2035 of the present application can be implemented by the following steps: step S20351, determining whether the absolute value of the difference between the above current brightness value and the above brightness threshold is greater than the absolute value threshold; step S20352, when the absolute value of the difference between the above current brightness value and the above brightness threshold is greater than the above absolute value threshold, adjusting the above current brightness value to be closer to the above brightness threshold to obtain the above target brightness value; step S20353, when the absolute value of the difference between the above current brightness value and the above brightness threshold is less than or equal to the above absolute value threshold, determining the above target exposure parameter according to the above current brightness value, the above preliminary brightness value and the above parameter threshold. This method can further avoid the brightness of the scene changing with the brightness adjustment of other scenes, affecting the shooting accuracy of the scene, and improving the correction effect of the picture.

[0045] Specifically, if the brightness value of the scene in the current picture is greater than the preset threshold, the calculated average brightness value of the scene in the picture is compared with the current brightness value of the same scene to determine whether the brightness difference is greater than the absolute value threshold. In other words, when backlighting causes the brightness of the scene in the current picture to be much greater than the average value calculated for the previous frame, it is determined whether the brightness difference between the two data is greater than the absolute value threshold to determine whether the brightness of the current foreground needs to be adjusted.

[0046] The above step S20352 may also be implemented in other ways, for example: step S20354, according to the above target brightness value, reducing the brightness value of the exposure point in the above current picture to obtain the exposure point brightness value.

[0047] Specifically, since the exposure point is the part with the largest exposure parameter in the picture, the brightness value of the exposure point should be reduced.

[0048] In some embodiments, the above step S203 can be specifically implemented by the following steps: step S2036, a first fusion step, fusing the above target brightness value and the above preliminary brightness value to obtain the fused brightness value of the above target scene, wherein the above fusion processing includes one of weighted averaging, histogram equalization and local contrast enhancement, the above segmented screen corresponding to the above target scene is the target segmented screen, and the above preliminary brightness value is the brightness value of the above segmented screen adjacent to the above target segmented screen; step S2037, a first repetition step, repeating the above first fusion step at least once until all the above segmented screens in the above current screen are traversed to obtain multiple fused brightness values; step S2038, a first adjustment step, adjusting the above current exposure parameter according to the average value of the multiple fused brightness values ​​to obtain the above target exposure parameter. This method can further shorten the exposure time and improve the monitoring and recording effect.

[0049] Specifically, the brightness of the foreground object is automatically adjusted and then processed through image analysis and fusion to directly obtain the required image brightness. Combined with the adjusted predicted exposure brightness, the current exposure parameters are adjusted as a whole to improve the accuracy and precision after adjustment, improve the harmony of the image, and collect target images through the camera lens for real-time monitoring.

[0050] The above step S204 can be implemented by the following steps: step S2041, a second fusion step, fusing the above target brightness value, the above preliminary brightness value and the above parameter threshold to obtain the fused brightness value of the above target scene, wherein the above fusion process includes one of weighted average, histogram equalization and local contrast enhancement, the above segmented screen corresponding to the above target scene is the target segmented screen, and the above preliminary brightness value is the brightness value of the above segmented screen adjacent to the above target segmented screen; step S2042, a second repetition step, repeating the above second fusion step at least once until all the above segmented screens in the above current screen are traversed to obtain multiple fused brightness values; step S2043, a second adjustment step, adjusting the above current exposure parameter according to the average value of the multiple fused brightness values ​​to obtain the above target exposure parameter. This method can further quickly determine the above target exposure parameter.

[0051] Specifically, weighted averaging is a method of fusing multiple images into one image, where the pixel values ​​of each image are weighted and calculated according to their weights. The weights can be determined based on the quality of the image, the exposure level, or the importance of a particular scene. In the application of surveillance cameras, this means that the brightness values ​​of the current frame and other frames can be fused in a certain weighted ratio to obtain a more stable and higher quality final brightness value. For example, if the exposure parameter of the current frame is too large, the final brightness can be balanced by increasing the weight of the historical frames to avoid overexposure. Histogram equalization is used to improve the contrast of an image, especially when the brightness of a local area of ​​the image varies greatly. By adjusting the distribution of image pixels, the histogram of the image tends to be uniform, thereby increasing the global contrast of the image and making the image look clearer. In smart surveillance cameras, histogram equalization can be used for the entire or local area to optimize the exposure and contrast of the image, especially in low light or high light conditions. For example, if most of the surveillance area is in shadow, histogram equalization can help increase the brightness of the shadow area, making the details more clearly visible. Local contrast enhancement improves the visual effect of an image by enhancing the contrast of a local area of ​​the image. This is usually achieved by applying a local filter or Gaussian blur, then calculating the brightness difference in the local area and adjusting it. In smart surveillance cameras, local contrast enhancement can be used to highlight the details of key scenes in the picture, ensuring that important information is clearly displayed even in the case of overall underexposure or overexposure. For example, if the foreground object is much brighter than the background, local contrast enhancement can help adjust the brightness of the foreground while maintaining the details of the background, making the entire picture more balanced and clear.

[0052] The above step S205 can be implemented by the following steps: Step S2051, according to the above target exposure parameters, determine the acquisition parameters of the above intelligent monitoring device to acquire the above target image, the above acquisition parameters include at least one of shutter speed, aperture size and ISO sensitivity. This method can further quickly acquire the above target image.

[0053] Specifically, the steps for capturing the target image are as follows: First, the system has calculated or adjusted the most suitable target exposure parameters for the current scene through algorithms. This includes shutter speed, aperture size, ISO sensitivity, and possible brightness and contrast adjustment values. Set camera parameters: Apply the target exposure parameters to the hardware settings of the camera, including adjusting the shutter speed, aperture size, ISO sensitivity, etc., to ensure that the camera shoots according to the calculated parameters. Preview and fine-tuning: Before actual shooting, the camera may perform a preview shot to check whether the target exposure parameters have actually achieved the expected effect. If there is still a problem with the exposure of the preview image, the system will fine-tune the parameters according to the actual situation until a satisfactory exposure effect is achieved.

[0054] The embodiment of the present application also provides an image acquisition device. It should be noted that the image acquisition device of the embodiment of the present application can be used to execute the image acquisition method provided by the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0055] The following is an introduction to the image acquisition device provided in the embodiments of the present application.

[0056] Figure 3 is a schematic diagram of an image acquisition device according to an embodiment of the present application. Figure 3 As shown, the above device is applied to intelligent monitoring equipment, and the device includes:

[0057] An acquisition unit 10 is used to acquire a current exposure parameter of the intelligent monitoring device, where the current exposure parameter is an exposure parameter of a current picture collected by the intelligent monitoring device at a current moment;

[0058] Specifically, when the camera monitors the target position angle, it obtains the exposure parameters of the current picture in real time and records them.

[0059] A first determining unit 20, configured to determine whether the current exposure parameter is greater than a parameter threshold;

[0060] Specifically, the above parameter threshold settings are related to the type of intelligent monitoring equipment.

[0061] The adjusting unit 30 is used to adjust the current brightness value of the target scene in the current picture to obtain a target brightness value when the current exposure parameter is greater than the parameter threshold, and adjust the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain the target exposure parameter, the current picture includes a plurality of scenes, the target scene is any one of the plurality of scenes, and the preliminary brightness value is the brightness value of the other scenes in the plurality of scenes except the target scene;

[0062] Specifically, when the above-mentioned current exposure parameter is greater than the above-mentioned parameter threshold, that is, the current picture is in a backlit state, resulting in the exposure parameter and brightness of the current picture being much greater than the calculated exposure parameter and brightness value, the brightness of the scene in the current picture that is the same as that in the previous frame will be automatically adjusted, so as to facilitate the adjustment of the overall brightness and exposure of the entire picture as a reference.

[0063] A second determining unit 40 is configured to determine the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold value when the current exposure parameter is less than or equal to the parameter threshold value;

[0064] Specifically, when the current exposure parameter is less than or equal to the parameter threshold, that is, when the current picture is not backlit, the overall exposure parameter in the current picture is adjusted to improve the refresh rate and softness of the picture.

[0065] The acquisition unit 50 is used to acquire a target image according to the above target exposure parameters.

[0066] Specifically, when all target exposure parameters are set and the preview is confirmed to be correct, the camera will formally capture the target image. At this time, the camera will capture the image according to the set exposure parameters to ensure that the brightness, contrast and details of the image are optimally presented.

[0067] Through this embodiment, an image acquisition device is provided. An acquisition unit acquires the current exposure parameter of the intelligent monitoring device, and the current exposure parameter is the exposure parameter of the current picture collected by the intelligent monitoring device at the current moment; a first determination unit determines whether the current exposure parameter is greater than a parameter threshold; an adjustment unit adjusts the current brightness value of the target scene in the current picture to obtain a target brightness value when the current exposure parameter is greater than the parameter threshold, and adjusts the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain a target exposure parameter; a second determination unit determines the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold when the current exposure parameter is less than or equal to the parameter threshold; and an acquisition unit acquires a target image according to the target exposure parameter. By judging the magnitude relationship between the current exposure parameter and the parameter threshold, when the current exposure parameter exceeds the parameter threshold, the brightness value of the scene in the current picture is automatically adjusted to a reasonable range, and the brightness value of the scene after adjustment is fused with the brightness value of other current positions to automatically adjust the exposure parameter of the entire picture. By acquiring the target image according to the adjusted exposure parameter, the picture processing efficiency can be improved, the picture correction time can be shortened, the refresh rate of the picture and the softness of the picture can be further improved, and high-quality monitoring images can be obtained even in complex environments such as backlight. The problem that the intelligent monitoring camera in the prior art cannot accurately identify objects and details in the picture under backlight environment is solved.

[0068] In the specific implementation process, the adjustment unit includes a processing module, a first acquisition module, a second acquisition module, a calculation module and a first adjustment module, wherein the processing module is used to segment the current screen to obtain multiple segmented screens, wherein one segmented screen includes at least one scene; the first acquisition module is used to obtain the brightness value of each segmented screen to obtain multiple scene brightness values; the second acquisition module is used to obtain the brightness value of the same scene in different historical screens to obtain multiple historical brightness values, wherein the historical screen is the screen collected by the intelligent monitoring device before the current moment; the calculation module is used to calculate the average value of the multiple historical brightness values ​​to obtain the brightness threshold; the first adjustment module is used to adjust the current brightness value according to the brightness threshold and the current brightness value to obtain the target brightness value. The device can further improve the image processing efficiency, shorten the image correction time, and improve the accuracy and efficiency of automatic adjustment.

[0069] Specifically, when the camera always divides the picture into grids during the shooting process, the brightness values ​​and exposure parameters of different grids are determined. When encountering backlight, the exposure and range in the picture, as well as the change in the brightness of the scenes in different grids, are known through the changes in the brightness values ​​and exposure parameters of different grids, so as to facilitate the automatic adjustment of the brightness of the scenes in the grids and the exposure and exposure range in the picture in the later stage. In addition, the brightness and exposure of the next frame can be calculated in advance, so that when the camera records the next frame, it can be directly compared and adjusted. The preset threshold of the brightness value of the current foreground object is a certain range of the average value of the brightness value of the same scene in the previous multiple frames. The brightness threshold of the scene in the current picture is not fixed, but changes with the overall environment in the current picture, which does not affect the overall movement of the picture and the picture accuracy of the shooting record, and improves the correction efficiency and stability.

[0070] The adjustment module of the present application includes a first determination submodule, an adjustment submodule and a second determination submodule, wherein the first determination submodule is used to determine whether the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold; the adjustment submodule is used to adjust the current brightness value to be closer to the brightness threshold to obtain the target brightness value when the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold; the second determination submodule is used to determine the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold when the absolute value of the difference between the current brightness value and the brightness threshold is less than or equal to the absolute value threshold. The device can further prevent the brightness of the scene from changing with the brightness adjustment of other scenes, affecting the shooting accuracy of the scene, and improving the correction effect of the picture.

[0071] Specifically, if the brightness value of the scene in the current picture is greater than the preset threshold, the calculated average brightness value of the scene in the picture is compared with the current brightness value of the same scene to determine whether the brightness difference is greater than the absolute value threshold. In other words, when backlighting causes the brightness of the scene in the current picture to be much greater than the average value calculated for the previous frame, it is determined whether the brightness difference between the two data is greater than the absolute value threshold to determine whether the brightness of the current foreground needs to be adjusted.

[0072] The adjustment submodule is used to reduce the brightness value of the exposure point in the current picture according to the target brightness value to obtain the exposure point brightness value.

[0073] Specifically, since the exposure point is the part with the largest exposure parameter in the picture, the brightness value of the exposure point should be reduced.

[0074] In some embodiments, the adjustment unit includes a first fusion module, a first repetition module, and a second adjustment module, wherein the first fusion module is used in the first fusion step to fuse the target brightness value and the preliminary brightness value to obtain the fused brightness value of the target scene, wherein the fusion process includes one of weighted average, histogram equalization, and local contrast enhancement, the segmented screen corresponding to the target scene is the target segmented screen, and the preliminary brightness value is the brightness value of the segmented screen adjacent to the target segmented screen; the first repetition module is used in the first repetition step to repeat the first fusion step at least once until all the segmented screens in the current screen are traversed to obtain multiple fused brightness values; the second adjustment module is used in the first adjustment step to adjust the current exposure parameter according to the average value of the multiple fused brightness values ​​to obtain the target exposure parameter. The device can further shorten the exposure time and improve the monitoring and recording effect.

[0075] Specifically, the brightness of the foreground object is automatically adjusted and then processed through image analysis and fusion to directly obtain the required image brightness. Combined with the adjusted predicted exposure brightness, the current exposure parameters are adjusted as a whole to improve the accuracy and precision after adjustment, improve the harmony of the image, and collect target images through the camera lens for real-time monitoring.

[0076] The second determination unit includes a second fusion module, a second repetition module and a third adjustment module, wherein the second fusion module is used in the second fusion step to fuse the target brightness value, the preliminary brightness value and the parameter threshold to obtain the fused brightness value of the target scene, wherein the fusion process includes one of weighted average, histogram equalization and local contrast enhancement, the segmented screen corresponding to the target scene is the target segmented screen, and the preliminary brightness value is the brightness value of the segmented screen adjacent to the target segmented screen; the second repetition module is used in the second repetition step to repeat the second fusion step at least once until all the segmented screens in the current screen are traversed to obtain multiple fused brightness values; the third adjustment module is used in the second adjustment step to adjust the current exposure parameter according to the average value of the multiple fused brightness values ​​to obtain the target exposure parameter. The device can further quickly determine the target exposure parameter.

[0077] Specifically, weighted averaging is a method of fusing multiple images into one image, where the pixel values ​​of each image are weighted and calculated according to their weights. The weights can be determined based on the quality of the image, the exposure level, or the importance of a particular scene. In the application of surveillance cameras, this means that the brightness values ​​of the current frame and other frames can be fused in a certain weighted ratio to obtain a more stable and higher quality final brightness value. For example, if the exposure parameter of the current frame is too large, the final brightness can be balanced by increasing the weight of the historical frames to avoid overexposure. Histogram equalization is used to improve the contrast of an image, especially when the brightness of a local area of ​​the image varies greatly. By adjusting the distribution of image pixels, the histogram of the image tends to be uniform, thereby increasing the global contrast of the image and making the image look clearer. In smart surveillance cameras, histogram equalization can be used for the entire or local area to optimize the exposure and contrast of the image, especially in low light or high light conditions. For example, if most of the surveillance area is in shadow, histogram equalization can help increase the brightness of the shadow area, making the details more clearly visible. Local contrast enhancement improves the visual effect of an image by enhancing the contrast of a local area of ​​the image. This is usually achieved by applying a local filter or Gaussian blur, then calculating the brightness difference in the local area and adjusting it. In smart surveillance cameras, local contrast enhancement can be used to highlight the details of key scenes in the picture, ensuring that important information is clearly displayed even in the case of overall underexposure or overexposure. For example, if the foreground object is much brighter than the background, local contrast enhancement can help adjust the brightness of the foreground while maintaining the details of the background, making the entire picture more balanced and clear.

[0078] The acquisition unit includes a determination module for determining acquisition parameters of the intelligent monitoring device according to the target exposure parameters to acquire the target image, wherein the acquisition parameters include at least one of shutter speed, aperture size and ISO sensitivity. The device can further quickly acquire the target image.

[0079] Specifically, the steps for capturing the target image are as follows: First, the system has calculated or adjusted the most suitable target exposure parameters for the current scene through algorithms. This includes shutter speed, aperture size, ISO sensitivity, and possible brightness and contrast adjustment values. Set camera parameters: Apply the target exposure parameters to the hardware settings of the camera, including adjusting the shutter speed, aperture size, ISO sensitivity, etc., to ensure that the camera shoots according to the calculated parameters. Preview and fine-tuning: Before actual shooting, the camera may perform a preview shot to check whether the target exposure parameters have actually achieved the expected effect. If there is still a problem with the exposure of the preview image, the system will fine-tune the parameters according to the actual situation until a satisfactory exposure effect is achieved.

[0080] The image acquisition device includes a processor and a memory, and the acquisition unit, the first determination unit, the adjustment unit, the second determination unit, and the adjustment unit are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0081] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and images can be acquired by adjusting kernel parameters.

[0082] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0083] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the image acquisition method.

[0084] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the image acquisition method is executed when the program is run.

[0085] An embodiment of the present invention provides a device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, at least the steps of the above-mentioned image acquisition method are implemented. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0086] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes at least the following steps of the above-mentioned image acquisition method.

[0087] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0088] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0089] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0092] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0093] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0094] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0095] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0096] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0097] 1) The image acquisition method of the present application first obtains the current exposure parameter of the intelligent monitoring device, which is the exposure parameter of the current picture collected by the intelligent monitoring device at the current moment; determines whether the current exposure parameter is greater than the parameter threshold; then, when the current exposure parameter is greater than the parameter threshold, adjusts the current brightness value of the target scene in the current picture to obtain the target brightness value, and adjusts the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain the target exposure parameter; then, when the current exposure parameter is less than or equal to the parameter threshold, determines the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold; finally, acquires the target image according to the target exposure parameter. By judging the magnitude relationship between the current exposure parameter and the parameter threshold, when the current exposure parameter exceeds the parameter threshold, the brightness value of the current picture scene is automatically adjusted to a reasonable range, and the brightness value of the scene after adjustment is fused with the brightness value of other current positions to automatically adjust the exposure parameter of the entire picture. Acquiring the target image according to the adjusted exposure parameter can improve the picture processing efficiency, shorten the picture correction time, further improve the picture refresh rate and the picture softness, and ensure that high-quality monitoring images can be obtained even in complex environments such as backlight. The problem that the intelligent monitoring camera in the prior art cannot accurately identify objects and details in the picture under backlight environment is solved.

[0098] 2) In the image acquisition device of the present application, the acquisition unit acquires the current exposure parameter of the intelligent monitoring device, and the current exposure parameter is the exposure parameter of the current picture collected by the intelligent monitoring device at the current moment; the first determination unit determines whether the current exposure parameter is greater than the parameter threshold; the adjustment unit adjusts the current brightness value of the target scene in the current picture to obtain the target brightness value when the current exposure parameter is greater than the parameter threshold, and adjusts the current exposure parameter according to the target brightness value and the preliminary brightness value to obtain the target exposure parameter; the second determination unit determines the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold when the current exposure parameter is less than or equal to the parameter threshold; the acquisition unit acquires the target image according to the target exposure parameter. By judging the magnitude relationship between the current exposure parameter and the parameter threshold, when the current exposure parameter exceeds the parameter threshold, the brightness value of the current picture scene is automatically adjusted to a reasonable range, and the brightness value of the scene after adjustment is fused with the brightness value of other current positions to automatically adjust the exposure parameter of the entire picture. By acquiring the target image according to the adjusted exposure parameter, the picture processing efficiency can be improved, the picture correction time can be shortened, the refresh rate and the softness of the picture can be further improved, and high-quality monitoring images can be obtained even in complex environments such as backlight. The problem that the intelligent monitoring camera in the prior art cannot accurately identify objects and details in the picture under backlight environment is solved.

[0099] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An image acquisition method, characterized in that: The method is applied to an intelligent monitoring device, and the method comprises: Acquire a current exposure parameter of the intelligent monitoring device, where the current exposure parameter is an exposure parameter of a current picture collected by the intelligent monitoring device at the current moment; Determining whether the current exposure parameter is greater than a parameter threshold; When the current exposure parameter is greater than the parameter threshold, adjusting the current brightness value of the target scene in the current picture to obtain a target brightness value, and adjusting the current exposure parameter according to the target brightness value and a preliminary brightness value to obtain a target exposure parameter, wherein the current picture includes a plurality of scenes, the target scene is any one of the plurality of scenes, and the preliminary brightness value is the brightness value of the other scenes among the plurality of scenes except the target scene; When the current exposure parameter is less than or equal to the parameter threshold, determining the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold; According to the target exposure parameters, a target image is acquired.

2. The method according to claim 1, characterized in that When the current exposure parameter is greater than the parameter threshold, adjusting the current brightness value of the target scene in the current picture to obtain a target brightness value includes: Performing segmentation processing on the current picture to obtain a plurality of segmented pictures, wherein one of the segmented pictures includes at least one of the scenes; Acquire the brightness value of each of the split images to obtain a plurality of scene brightness values; Obtaining brightness values ​​of the same scene in different historical images to obtain multiple historical brightness values, wherein the historical images are images collected by the intelligent monitoring device before the current moment; Calculate an average value of a plurality of the historical brightness values ​​to obtain a brightness threshold; According to the brightness threshold and the current brightness value, the current brightness value is adjusted to obtain the target brightness value.

3. The method according to claim 2, characterized in that According to the brightness threshold and the current brightness value, adjusting the current brightness value to obtain the target brightness value includes: Determine whether the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold; When the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold, adjusting the current brightness value to be closer to the brightness threshold to obtain the target brightness value; When the absolute value of the difference between the current brightness value and the brightness threshold is less than or equal to the absolute value threshold, the target exposure parameter is determined according to the current brightness value, the preliminary brightness value and the parameter threshold.

4. The method according to claim 3, characterized in that When the absolute value of the difference between the current brightness value and the brightness threshold is greater than the absolute value threshold, adjusting the current brightness value to be closer to the brightness threshold to obtain the target brightness value, the method further includes: According to the target brightness value, the brightness value of the exposure point in the current picture is reduced to obtain the exposure point brightness value.

5. The method according to claim 2, characterized in that: According to the target brightness value and the preliminary brightness value, the current exposure parameter is adjusted to obtain the target exposure parameter, including: A first fusion step is to fuse the target brightness value and the preliminary brightness value to obtain a fused brightness value of the target scene, wherein the fusion process includes one of weighted averaging, histogram equalization and local contrast enhancement, the segmented picture corresponding to the target scene is the target segmented picture, and the preliminary brightness value is the brightness value of the segmented picture adjacent to the target segmented picture; a first repetition step, repeating the first fusion step at least once until all the segmented pictures in the current picture are traversed to obtain a plurality of fusion brightness values; The first adjustment step is to adjust the current exposure parameter according to an average value of the multiple fused brightness values ​​to obtain the target exposure parameter.

6. The method according to claim 2, characterized in that When the current exposure parameter is less than or equal to the parameter threshold, determining the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold includes: A second fusion step of fusing the target brightness value, the preliminary brightness value and the parameter threshold to obtain a fused brightness value of the target scene, wherein the fusion process includes one of weighted averaging, histogram equalization and local contrast enhancement, the segmented picture corresponding to the target scene is the target segmented picture, and the preliminary brightness value is the brightness value of the segmented picture adjacent to the target segmented picture; a second repeating step, repeating the second fusion step at least once until all the segmented pictures in the current picture are traversed to obtain a plurality of fusion brightness values; The second adjustment step is to adjust the current exposure parameter according to the average value of the multiple fused brightness values ​​to obtain the target exposure parameter.

7. The method according to claim 2, characterized in that According to the target exposure parameter, acquiring a target image includes: According to the target exposure parameter, the acquisition parameter of the intelligent monitoring device is determined to acquire the target image, and the acquisition parameter includes at least one of a shutter speed, an aperture size, and an ISO sensitivity.

8. An image acquisition device, characterized in that: The device is applied to intelligent monitoring equipment, and the device comprises: An acquisition unit, used to acquire a current exposure parameter of the intelligent monitoring device, wherein the current exposure parameter is an exposure parameter of a current picture collected by the intelligent monitoring device at a current moment; A first determining unit, configured to determine whether the current exposure parameter is greater than a parameter threshold; an adjusting unit, configured to adjust a current brightness value of a target scene in the current picture to obtain a target brightness value when the current exposure parameter is greater than the parameter threshold, and to adjust the current exposure parameter according to the target brightness value and a preliminary brightness value to obtain a target exposure parameter, wherein the current picture includes a plurality of scenes, the target scene is any one of the plurality of scenes, and the preliminary brightness value is a brightness value of the other scenes among the plurality of scenes except the target scene; a second determining unit, configured to determine the target exposure parameter according to the current brightness value, the preliminary brightness value and the parameter threshold value when the current exposure parameter is less than or equal to the parameter threshold value; The acquisition unit is used to acquire a target image according to the target exposure parameter.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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