Unmanned aerial vehicle image transmission picture general plus aerial survey camera information display method and system

Abstract

The invention discloses an unmanned aerial vehicle image transmission picture general plus aerial survey camera information display method and system, and relates to the field of unmanned aerial vehicles, and the method comprises the steps: obtaining a current display picture of an aerial survey camera, monitoring a plurality of continuous frames, calculating the similarity between a previous frame and a next frame in real time, and if the similarity is lower than a preset threshold value, determining that the aerial survey camera information is not displayed; the system analyzes the next frame of picture to obtain detailed picture parameters, matches corresponding predicted shooting parameters through a preset mapping table, pops up a shooting parameter setting frame on a display terminal and sends prompt information, and a user can select whether to apply the predicted parameters or not. The shooting parameters are ensured to dynamically adapt to real-time changing environmental conditions, so that the quality of aerial survey images is improved.

Description

Technical Field

[0001] The present application relates to the field of unmanned aerial vehicles, and in particular to a method and system for displaying information of an unmanned aerial vehicle image transmission screen and an aerial survey camera. Background Art

[0002] With the rapid development of drone technology, drones are increasingly used in various industries, especially in the field of aerial surveying. Drone aerial survey cameras provide key data in terrain surveying, environmental monitoring, agricultural management, etc. by taking a large number of high-resolution images. In order to ensure the accuracy and reliability of aerial survey data, various parameters in the shooting process must be precisely controlled and adjusted.

[0003] In the related art, the operation of the aerial survey camera is generally controlled by preset shooting parameters. Usually, these shooting parameters are set before the drone takes off according to the estimated flight environment and mission requirements. During the flight, the drone automatically maintains these preset parameters through sensors and control systems to ensure the consistency and quality of the aerial survey images.

[0004] However, due to the complexity and unpredictability of the flight environment, the preset shooting parameters often cannot adapt to the real-time changing environmental conditions, resulting in large fluctuations in the quality of aerial survey images. Summary of the invention

[0005] The present application provides a method and system for displaying information of a drone image transmission screen and an aerial survey camera, which are used to improve the quality of aerial survey images.

[0006] In the first aspect, the present application provides a method for displaying information of a drone image transmission screen and a general aerial survey camera, which is applied to a drone image transmission screen and a general aerial survey camera information display system, the method comprising: obtaining a current display screen of the aerial survey camera, and monitoring the current display screen to obtain multiple continuous frames of the current display screen, wherein the aerial survey camera is placed on a drone; calculating the picture similarity between a previous frame and a next frame in the multiple continuous frames; if the picture similarity is lower than a preset similarity threshold, parsing the next frame to obtain picture parameters; matching corresponding predicted shooting parameters in a preset picture parameter-shooting parameter mapping table according to the picture parameters; popping up a shooting parameter setting box on a display terminal and sending a prompt message, the shooting parameter setting box containing predicted shooting parameters, the prompt message being used to ask the user whether to use the predicted shooting parameters; after receiving a confirmation instruction sent by the display terminal, applying the predicted shooting parameters to the aerial survey camera.

[0007] By adopting the above technical solution, by acquiring the current display screen of the aerial survey camera and monitoring multiple consecutive frames, the similarity between the previous frame and the next frame is calculated in real time. If the similarity is lower than the preset threshold, the system will parse the next frame to obtain detailed image parameters, and match the corresponding predicted shooting parameters through a preset mapping table, and pop up a shooting parameter setting box on the display terminal and send a prompt message. The user can choose whether to apply these predicted parameters, ensuring that the shooting parameters can dynamically adapt to real-time changing environmental conditions, thereby improving the quality of aerial survey images.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of calculating the picture similarity between the previous frame and the next frame in the multiple consecutive frames specifically includes: extracting the key point features of the previous frame and the next frame based on the feature point detection algorithm to obtain the first key point feature corresponding to the previous frame and the second key point feature corresponding to the next frame; matching the first key point feature with the second key point feature to obtain matching feature points; calculating the ratio of the total number of feature points in the previous frame to the number of matching feature points to obtain the picture similarity between the previous frame and the next frame.

[0009] By adopting the above technical solution, by using the feature point detection algorithm to extract the key point features of the picture, the system can obtain the first and second key point features corresponding to the previous frame and the next frame respectively, and then the system matches these key point features, calculates the number of matching feature points, and determines the picture similarity based on the ratio of this number to the total number of feature points, thereby improving the accuracy of the similarity calculation and ensuring that when the similarity is lower than the preset threshold, the shooting parameters can be adjusted in time, thereby further improving the quality and consistency of the aerial survey images.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after the step of applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal, the method also includes: obtaining the current flight mission of the UAV in the flight route; calculating the task execution time point of the next flight mission based on the historical task execution time and the current flight mission progress of the UAV; popping up a shooting parameter setting box on the display terminal at the task execution time point; and applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal.

[0011] By adopting the above technical solution, by calculating the mission progress of the UAV in the current flight route, the system can predict the execution time point of the next flight mission. At this time point, a shooting parameter setting box will pop up on the display terminal and send a prompt message. After the user confirms, the predicted shooting parameters will be applied to the aerial survey camera, ensuring that when the UAV performs continuous tasks, the shooting parameters can be dynamically adjusted according to the mission progress and historical data, further improving the efficiency and image quality of the aerial survey mission, and also considering the time nodes of the flight mission, so that the system can more effectively manage the adjustment of shooting parameters and make full use of the flight time and power of the UAV.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after receiving the confirmation instruction sent by the display terminal, after the step of applying the predicted shooting parameters to the aerial survey camera, the method also includes: calculating the flight time required to complete the remaining flight mission based on the historical mission execution time and the current flight mission progress of the UAV; calculating the task power consumption required within the flight time; if the current power of the UAV is lower than the task power consumption, sending a warning message to the display terminal for display.

[0013] By adopting the above technical solution, the historical shooting parameters of the aerial survey camera are obtained, and the most frequently used user shooting parameters (such as exposure time, aperture size and ISO sensitivity) are counted to generate a first user mode. When the user selects this mode on the display terminal, these frequently used shooting parameters can be automatically applied to the aerial survey camera, which can reduce the time for setting parameters before each task and improve work efficiency. At the same time, parameter optimization based on historical data can ensure the reliability and applicability of shooting parameters, thereby improving the quality and consistency of aerial survey images.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal, the method also includes: obtaining the historical shooting parameters of the aerial survey camera, and counting the most frequently used user shooting parameters, the user shooting parameters including exposure time, aperture size and ISO sensitivity; generating the user shooting parameters as a first user mode; and applying the user shooting parameters to the aerial survey camera when receiving the first user mode selection instruction sent by the display terminal.

[0015] By adopting the above technical solution, the historical shooting parameters of the aerial survey camera are obtained, and the most frequently used user shooting parameters (such as exposure time, aperture size and ISO sensitivity) are counted to generate a first user mode. When the user selects this mode on the display terminal, these frequently used shooting parameters can be automatically applied to the aerial survey camera, which can reduce the time for setting parameters before each task and improve work efficiency. At the same time, parameter optimization based on historical data can ensure the reliability and applicability of shooting parameters, thereby improving the quality and consistency of aerial survey images.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after receiving the confirmation instruction sent by the display terminal, after the step of applying the predicted shooting parameters to the aerial survey camera, the method also includes: displaying the predicted shooting parameters on the display terminal; if it is detected that the display terminal has no operation response within a preset time period, hiding the predicted shooting parameters on the display terminal.

[0017] By adopting the above technical solution, the system will display the predicted shooting parameters on the display terminal and set a preset time period. If it is detected that there is no operation response from the display terminal during this time period, the system will automatically hide the predicted shooting parameters to ensure that the user can easily view and confirm the shooting parameters when needed, while avoiding unnecessary information interference. This dynamic display management not only improves the convenience of user operation, but also provides clearer interface information in UAV aerial survey tasks, thereby improving operational efficiency.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of calculating the picture similarity between the previous frame and the next frame in the multiple consecutive frames, the method also includes: if the picture similarity is not lower than a preset similarity threshold, sending the current shooting parameters to the display terminal, so that the current shooting parameters are displayed on the display terminal.

[0019] By adopting the above technical solution, when the system calculates that the image similarity between consecutive frames is not less than the preset value, the current shooting parameters will be sent to the display terminal, which can help the operator quickly determine whether the current shooting settings are appropriate, so as to make timely adjustments and avoid image quality problems caused by improper parameter settings.

[0020] In a second aspect, an embodiment of the present application provides a UAV aerial survey system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the UAV aerial survey system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the above-mentioned computer program product is run on a UAV aerial survey system, the above-mentioned UAV aerial survey system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on a UAV aerial survey system, the UAV aerial survey system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0023] It can be understood that the drone aerial survey system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application obtains the current display screen of the aerial survey camera and monitors multiple consecutive frames, and calculates the similarity between the previous frame and the next frame in real time. If the similarity is lower than the preset threshold, the system will parse the next frame to obtain detailed picture parameters, and match the corresponding predicted shooting parameters through a preset mapping table, and pop up a shooting parameter setting box on the display terminal and send a prompt message. The user can choose whether to apply these predicted parameters, ensuring that the shooting parameters can dynamically adapt to real-time changing environmental conditions, thereby improving the quality of aerial survey images.

[0025] 2. This application uses a feature point detection algorithm to extract key point features of the picture. The system can obtain the first and second key point features corresponding to the previous frame and the next frame respectively. The system then matches these key point features, calculates the number of matching feature points, and determines the picture similarity based on the ratio of this number to the total number of feature points. This improves the accuracy of the similarity calculation and ensures that when the similarity is lower than the preset threshold, the shooting parameters can be adjusted in time, thereby further improving the quality and consistency of the aerial survey images.

[0026] 3. By calculating the mission progress of the drone in the current flight route, the system can predict the execution time of the next flight mission. At this time point, a shooting parameter setting box will pop up on the display terminal and a prompt message will be sent. After the user confirms, the predicted shooting parameters will be applied to the aerial survey camera, ensuring that when the drone performs continuous tasks, the shooting parameters can be dynamically adjusted according to the mission progress and historical data, further improving the efficiency and image quality of the aerial survey mission. It also takes into account the time nodes of the flight mission, so that the system can more effectively manage the adjustment of shooting parameters and make full use of the drone's flight time and power. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a method for displaying information of a drone image transmission screen and a general aerial survey camera in an embodiment of the present application; Figure 2 It is another flow chart of the method for displaying information of the drone image transmission screen and the aerial survey camera in the embodiment of the present application; Figure 3 It is a schematic diagram of the physical device structure of the UAV aerial survey system in the embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0031] Aerial survey technology is widely used to obtain high-resolution image data in various drone application scenarios, such as agricultural monitoring, traffic survey, and construction monitoring. However, these application environments are often complex and changeable, and the preset shooting parameters are difficult to adapt to real-time changing factors such as lighting, weather, and terrain, resulting in unstable aerial survey image quality. In traditional methods, operators need to constantly monitor and manually adjust shooting parameters, which not only increases the workload but also may lead to the loss of important image information. Therefore, there is an urgent need for a method that can dynamically adjust shooting parameters to adapt to various real-time changing environments and improve the quality and consistency of aerial survey images.

[0032] In many drone application fields, traditional aerial survey systems usually control the operation of the camera by presetting shooting parameters. These parameters are usually set before the mission begins, based on the estimation of the flight environment and mission requirements. However, when the drone encounters sudden environmental changes during flight, such as changes in lighting, increased wind speed or complex terrain, the preset parameters are often unable to cope with these changes, resulting in problems such as dark, blurred or underexposed images. Operators can only manually adjust the parameters and reshoot after discovering problems on the ground monitoring screen, which not only wastes time but may also miss the best shooting time. What's more serious is that in large-scale and complex tasks, this adjustment method is difficult to ensure the consistency of quality of all images, affecting the accuracy and efficiency of subsequent data analysis.

[0033] In order to solve the above problems, the related field introduced the method of displaying information of drone image transmission and aerial survey camera proposed in this paper. In actual tasks, the drone obtains the current display screen of the aerial survey camera in real time through the system during flight and monitors the changes of consecutive frames. When the similarity of the picture is detected to be lower than the preset threshold, the system automatically parses the next frame, extracts the picture parameters, and matches the corresponding predicted shooting parameters through the preset mapping table. The system pops up the shooting parameter setting box on the display terminal and sends a prompt message. The operator only needs to confirm to apply these parameters. In this way, the drone can dynamically adjust the shooting parameters according to real-time environmental changes, ensuring the quality and consistency of the aerial survey images. Compared with traditional methods, it greatly reduces the workload of operators and improves the efficiency of task execution and the reliability of data.

[0034] After applying the above solution for a period of time, the relevant field further optimized the UAV aerial survey system. Combining the historical mission execution time and the current flight mission progress, the system can calculate the task execution time point of the next flight mission, and automatically pop up the shooting parameter setting box at this time point. After the operator confirms, the system automatically applies the predicted shooting parameters. In addition, the system can also predict the time and power required to complete the remaining flight missions based on the progress of the flight mission. If the current power is not enough to complete the task, the system will send an early warning message. This optimization enables the UAV aerial survey system to perform better in large-scale, continuous tasks, ensuring the efficient execution of each task and the high quality of image data. At the same time, the system can generate user modes based on historical shooting parameters, further simplify the operation process, and improve overall work efficiency and user experience. In various UAV application fields, such as agricultural monitoring, traffic surveys, and construction monitoring, the system can significantly improve the quality and efficiency of task completion.

[0035] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , which is a flow chart of a method for displaying information of a drone image transmission screen and an aerial survey camera in an embodiment of the present application.

[0036] S101, obtaining a current display screen of an aerial survey camera, and monitoring the current display screen to obtain a plurality of continuous frames of the current display screen, wherein the aerial survey camera is placed on a drone.

[0037] Among them, aerial survey camera refers to the camera equipment installed on the drone for taking aerial survey images; the current display screen refers to the image taken by the aerial survey camera at a certain moment; monitoring is used to indicate the process of continuous observation and recording of the current display screen; multiple continuous frames refer to multiple images taken continuously in a short period of time, which constitute a set of frame sequences; drone refers to an aircraft used to carry aerial survey cameras and perform flight missions.

[0038] Specifically, when the drone performs a flight mission, the system first obtains the current display screen through the aerial survey camera installed on the drone. The screen represents the image taken by the aerial survey camera at the current moment. The system not only obtains a single image, but also continuously captures multiple continuous frames through the monitoring function. These frames are closely connected in time and can reflect environmental changes in a short period of time. In some embodiments, the acquisition and monitoring of the current display screen of the aerial survey camera can be achieved in a variety of ways: optionally, the control module on the drone triggers the shooting command at a fixed time, so that the aerial survey camera continuously shoots images at preset time intervals; optionally, the real-time image captured by the aerial survey camera is transmitted to the ground control center through real-time video streaming technology, and the frame is extracted and recorded in the control center; optionally, the autonomous flight control system of the drone automatically adjusts the shooting frequency and angle according to the flight trajectory and mission requirements to ensure that the acquired continuous frames cover the mission area. It can be understood that other methods can also be used to achieve the acquisition and monitoring of continuous frames, which are not limited here.

[0039] S102: Calculate the picture similarity between the previous frame and the next frame in the plurality of continuous frames.

[0040] Among them, continuous frames refer to multiple images taken continuously in a short period of time; the previous frame refers to an earlier frame in the frame sequence; the next frame refers to the next frame immediately following the previous frame in the frame sequence; the picture similarity is used to represent the numerical value calculated by the algorithm to measure the similarity between two frames.

[0041] Specifically, after acquiring multiple consecutive frames, the system needs to analyze the changes between these frames. First, the system determines the previous frame and the next frame in the frame sequence. On this basis, the similarity between the two frames is calculated through image processing algorithms, such as structural similarity (SSIM) or mean square error (MSE). Image similarity is a numerical value used to quantitatively indicate the degree of similarity between two frames of images. If the similarity is high, it means that the two frames of images have changed little; if the similarity is low, it means that there is a large change between the two frames of images. The purpose of this step is to identify the moment when the picture changes significantly, so as to provide a basis for subsequent image analysis and parameter adjustment.

[0042] In some embodiments, the similarity calculation between consecutive frames can be implemented in a variety of ways: optionally, by a simple method based on pixel difference, the difference between corresponding pixels in two frames is calculated and averaged; optionally, by a method based on feature extraction, an image feature point detection algorithm (such as SIFT or ORB) is used to extract feature points in two frames and calculate the degree of matching; optionally, by a deep learning method, a pre-trained convolutional neural network (CNN) model is used to feature encode the two frames and calculate the cosine similarity between the encoded vectors. It is understandable that other methods can also be used to calculate the similarity of the images, which are not limited here.

[0043] S103: If the picture similarity is lower than a preset similarity threshold, the next frame of the picture is analyzed to obtain picture parameters.

[0044] Among them, picture similarity refers to the value calculated by the algorithm to measure the similarity between two frames of images; the preset similarity threshold refers to a value pre-set by the system, which is used to determine whether the similarity between two frames of images is high enough; the next frame of the picture refers to the next frame of the picture immediately following the previous frame of the picture in the continuous frame; analysis is used to indicate the process of analyzing and processing the image; the picture parameters refer to various values ​​or features extracted from the image, which are used to describe the properties of the image, such as brightness, contrast, hue, etc.

[0045] Specifically, after the system calculates the similarity between the previous frame and the next frame in the continuous frame, it will compare the similarity with the preset similarity threshold. If the similarity is lower than the preset threshold, it means that there is a significant change between the two frames. At this time, the system will perform a detailed analysis of the next frame. The analysis process involves image processing technology, such as brightness histogram analysis, edge detection, etc., to extract parameters that can describe the picture.

[0046] In some embodiments, the analysis of the next frame can be achieved in a variety of ways: optionally, through an image processing algorithm, first perform image preprocessing (such as denoising, sharpening, etc.), then calculate the brightness histogram of the image and extract the brightness parameters; then, perform edge detection and analyze the detailed information of the image; finally, calculate the color distribution of the image and extract the hue and saturation parameters. Optionally, using a machine learning model, first input the image into a pre-trained convolutional neural network (CNN) model to extract high-level features, and then obtain various picture parameters through a fully connected layer; finally, perform parameter normalization. It is understandable that other methods can also be used to achieve the analysis of the picture, which is not limited here.

[0047] S104: Match corresponding predicted shooting parameters in a preset picture parameter-shooting parameter mapping table according to the picture parameter.

[0048] Among them, picture parameters represent various values ​​or features extracted from the image, which are used to describe the attributes of the image; the preset picture parameter-shooting parameter mapping table refers to a table pre-established by the system, which is used to match picture parameters with appropriate shooting parameters; matching is used to represent the process of finding corresponding relationships according to certain rules; predicted shooting parameters represent the shooting settings predicted by the system based on the picture parameters and suitable for the current environment, such as exposure time, ISO value, white balance, etc.

[0049] Specifically, when the system obtains the parameters of the next frame, it will use these parameters to find the corresponding relationship in the preset picture parameter-shooting parameter mapping table. The mapping table contains a large number of pre-set matching relationships between picture parameters and shooting parameters. Through these relationships, the system can quickly find shooting parameters suitable for the current environment. The matching process involves search algorithms, such as hash table search, binary search, etc., to improve matching efficiency. Once the appropriate shooting parameters are found, the system uses these parameters as predicted shooting parameters to guide the drone aerial survey camera to take the next step.

[0050] In some embodiments, the prediction of shooting parameters based on picture parameter matching can be achieved in a variety of ways: Optionally, through a simple search algorithm, the picture parameters are first standardized, and then the corresponding shooting parameters are searched in the hash table; if an exact match is not found, the shooting parameters are estimated using the nearest neighbor interpolation method. Optionally, through a machine learning method, the picture parameters are input using a trained regression model and the predicted shooting parameters are output; the model is trained based on a large amount of historical data and can handle complex parameter relationships. It is understandable that other methods can also be used to achieve the matching of picture parameters and shooting parameters, which are not limited here.

[0051] S105 . A shooting parameter setting box pops up on the display terminal and sends a prompt message. The shooting parameter setting box includes predicted shooting parameters. The prompt message is used to inquire the user whether to use the predicted shooting parameters.

[0052] Among them, the display terminal refers to a device used to display information and interact with the user, such as a computer screen, tablet, mobile phone, etc.; the shooting parameter setting box refers to a user interface element that pops up on the display terminal, which is used to display and adjust the shooting parameters; the predicted shooting parameters represent the shooting settings predicted by the system based on the picture parameters and suitable for the current environment; the prompt information is used to indicate the message displayed by the system in the shooting parameter setting box, asking the user whether to accept or adjust the predicted shooting parameters.

[0053] Specifically, when the system calculates the predicted shooting parameters, a shooting parameter setting box will pop up on the display terminal. This setting box contains the shooting parameters predicted by the system and displays a prompt message asking the user whether to accept these parameters. The display terminal can be the ground control station of the drone, the operator's tablet computer or other device with display function. The purpose of the prompt message is to give the user the opportunity to review and confirm these parameters to ensure that the shooting effect meets expectations. In addition, the user can also fine-tune or completely change the parameters in the setting box to adapt to specific shooting needs or environmental changes.

[0054] In some embodiments, the pop-up of the shooting parameter setting box and the display of prompt information can be realized in a variety of ways: Optionally, through the drone control software, the predicted shooting parameters are first calculated, and then the pop-up function of the display terminal is called to generate a shooting parameter setting box; the predicted shooting parameters are displayed in the setting box, and confirmation or modification options are provided. Optionally, through a mobile application, the predicted shooting parameters sent by the drone system are received to generate a shooting parameter setting interface; the parameters are displayed in the interface, and a slider or input box is provided for the user to adjust. It is understandable that other methods can also be used to realize the display of the shooting parameter setting box and the display of prompt information, which are not limited here.

[0055] S106: After receiving the confirmation instruction sent by the display terminal, apply the predicted shooting parameters to the aerial survey camera.

[0056] Among them, the confirmation instruction refers to the instruction for the user to confirm the use of the predicted shooting parameters by operating on the display terminal; the predicted shooting parameters represent the shooting settings suitable for the current environment predicted by the system based on the picture parameters; the application is used to indicate setting the predicted shooting parameters to the actual aerial survey camera; the aerial survey camera refers to the camera device installed on the drone for taking aerial survey images.

[0057] Specifically, after the user views and confirms the predicted shooting parameters on the display terminal, the system will receive a confirmation instruction sent by the user. This instruction indicates that the user agrees to use the shooting parameters recommended by the system. After receiving the confirmation instruction, the system applies these predicted shooting parameters to the actual aerial survey camera. The application process includes transmitting the parameters to the camera and setting the corresponding shooting parameters, such as exposure time, ISO value, white balance, etc., through the camera's control interface. In this way, the aerial survey camera will shoot according to the updated parameters to ensure that the image quality and shooting effect meet the current environmental conditions and user needs.

[0058] In some embodiments, the reception of confirmation instructions and the application of shooting parameters can be achieved in a variety of ways: Optionally, through the drone control software, first receive the confirmation instruction sent by the display terminal, then parse the instruction content and obtain the predicted shooting parameters; finally, transmit the parameters to the aerial survey camera through the communication module and set the parameters. Optionally, through a mobile application, after the user confirms the parameters in the application, the application generates a confirmation instruction and sends it to the drone system; after the drone system receives the instruction, it parses and applies the shooting parameters to the aerial survey camera. It is understandable that other methods can also be used to achieve the reception of confirmation instructions and the application of parameters, which are not limited here.

[0059] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , which is another flow chart of the method for displaying information of the drone image transmission screen and the aerial survey camera in the embodiment of the present application.

[0060] S021. Acquire a current display screen of an aerial survey camera, and monitor the current display screen to obtain multiple continuous frames of the current display screen, wherein the aerial survey camera is placed on a drone.

[0061] It can be understood that this step is similar to step S101 and will not be described in detail here.

[0062] S202: extract key point features of the previous frame and the next frame based on a feature point detection algorithm to obtain a first key point feature corresponding to the previous frame and a second key point feature corresponding to the next frame.

[0063] Specifically, in drone aerial surveys, the system needs to continuously capture multiple frames of images to cover the target area. However, in order to perform image stitching and subsequent analysis, the feature points of these images must be accurately extracted and matched. Feature point detection algorithms are used to identify points in images that are significantly different and stable. These points remain unchanged under different viewing angles and lighting conditions. Common algorithms include SIFT (Scale Invariant Feature Transform), SURF (Speeded Up Robust Features), and ORB (Oriented Fast and Rotation Invariant).

[0064] The system first obtains the image data of the previous frame and the next frame. Then, the feature point detection algorithm is applied to process the two frames to extract the key point features of each frame. For example, using the SIFT algorithm, the system will perform Gaussian blur and difference operations in different scale spaces of the image, identify feature points with local extreme values, and calculate the descriptor of each feature point. The descriptor is a high-dimensional vector that records the image gradient information around the feature point. After the processing is completed, the system obtains the first key point feature of the previous frame and the second key point feature of the next frame, which will be used for subsequent matching and similarity calculations.

[0065] S203: Match the first key point feature with the second key point feature to obtain matching feature points.

[0066] Specifically, in drone aerial surveys, in order to ensure that continuously shot images can be correctly stitched together, the system needs to match the feature points of the previous frame and the next frame. The matching process is to find the corresponding relationship by comparing the descriptors of the feature points.

[0067] The system first reads the first key point feature extracted from the previous frame and the second key point feature extracted from the next frame. Then, the feature matching algorithm is applied for matching. Commonly used algorithms include Nearest Neighbor, Brute-Force Matching, and FLANN (Fast Approximate Nearest Neighbor Search Library). For example, using the brute-force matching algorithm, the system calculates the Euclidean distance between each first key point feature descriptor and all second key point feature descriptors, and selects the one with the smallest distance as the matching point. If the distance is less than a certain threshold, the match is considered successful. The ratio test can be used in the matching process to improve the accuracy of the match, that is, the matching points with the smallest and second smallest distances are selected. Only when the ratio of the smallest distance to the second smallest distance is lower than a certain threshold, the match is considered successful. Finally, the system obtains a set of matching feature points, and these point pairs will be used to calculate the similarity between the two frames.

[0068] S204: Calculate the ratio of the total number of feature points in the previous frame to the number of matching feature points to obtain the picture similarity between the previous frame and the next frame.

[0069] The system first counts the total number of feature points in the previous frame, that is, the number of first key point features extracted in step S202. Then, the system counts the number of feature points successfully matched in step S203. The calculation method of picture similarity is the ratio of the number of matching feature points to the total number of feature points. This ratio reflects the proportion of similar feature points in the two frames. For example, if 100 feature points are extracted in the previous frame, and 80 feature points are successfully matched, then the picture similarity is 80 / 100, that is, 0.8. Picture similarity can be used as a criterion for judging image changes. When the similarity is lower than a preset threshold, it means that there is a significant change between the two frames, and further processing or adjustment of shooting parameters is required. This ratio can not only quantify the similarity of images, but also help the drone system to achieve more accurate image stitching and data processing during the aerial survey process, thereby improving the efficiency and accuracy of the aerial survey task.

[0070] S205: If the picture similarity is lower than a preset similarity threshold, the next frame of the picture is analyzed to obtain picture parameters.

[0071] It can be understood that this step is similar to step S103 and will not be described in detail here.

[0072] S206: If the picture similarity is not lower than a preset similarity threshold, the current shooting parameters are sent to the display terminal so that the current shooting parameters are displayed on the display terminal.

[0073] Specifically, in the UAV aerial survey system, in order to ensure the quality and consistency of continuous shooting images, the system will evaluate the similarity between the new image and the previous frame after each shooting. If the similarity is not lower than the preset similarity threshold, it means that the current shooting parameters are appropriate, and the system sends these parameters to the display terminal for the operator to view and confirm. First, the system compares the picture similarity calculated in the previous step with the preset similarity threshold. The preset similarity threshold is determined by the specific needs of the aerial survey task, and is usually set according to factors such as terrain complexity and lighting changes. For example, in a day and night shooting task, a higher similarity threshold (such as 0.85) is set to ensure image consistency.

[0074] If the image similarity is not lower than this threshold, it means that the current shooting parameters (such as exposure time, ISO value, aperture size, etc.) can capture images with stable quality in the current environment. Next, the system will organize these current shooting parameters into a data packet and send it to the display terminal through the wireless communication module. The display terminal can be a device such as a ground control station, tablet computer or smart phone used by the operator. After receiving the data packet, the display terminal will parse and display these shooting parameters on the screen so that the operator can monitor and adjust them in real time. For example, if the current shooting parameters are exposure time 1 / 100 second, ISO value 200, aperture f / 8, this information will be clearly displayed on the terminal's user interface.

[0075] S207 . Match corresponding predicted shooting parameters in a preset picture parameter-shooting parameter mapping table according to the picture parameters.

[0076] It can be understood that this step is similar to step S104 and will not be described in detail here.

[0077] S208: A shooting parameter setting box pops up on the display terminal and sends a prompt message, where the shooting parameter setting box includes predicted shooting parameters, and the prompt message is used to inquire the user whether to use the predicted shooting parameters.

[0078] It can be understood that this step is similar to step S105 and will not be described in detail here.

[0079] S209: After receiving the confirmation instruction sent by the display terminal, apply the predicted shooting parameters to the aerial survey camera.

[0080] It can be understood that this step is similar to step S106 and will not be described in detail here.

[0081] S210: Obtain the current flight mission of the UAV in the flight route.

[0082] Specifically, in the UAV aerial survey system, when the UAV performs a flight mission, it will operate according to the preset flight route. Each flight route includes multiple mission nodes, such as shooting points, data collection points, turning points, etc.

[0083] The purpose of this step is to obtain the mission information of the current location of the drone to ensure the smooth execution of the flight mission. First, the system will track the location of the drone in real time through GPS or other positioning systems. Each flight route will be marked with specific mission nodes and their corresponding tasks when planning, such as high-resolution photography or collecting environmental data at a specific location. When the drone flies near a mission node, the system will identify the node and obtain the current flight mission associated with it. For example, if the drone flies to a predetermined shooting point, the system will obtain the shooting mission information of the point, including shooting parameters, shooting angles, etc. This information is usually stored in the system's task database, and the system obtains specific tasks by querying the task node corresponding to the current coordinates.

[0084] S211. Calculate the task execution time point of the next flight task according to the historical task execution time and the current flight task progress of the UAV.

[0085] First, the system will analyze the historical data of the drone's previous execution of similar tasks, including the start and end time of the task, the duration of the task, etc., which are usually recorded in the system log or database. Next, the system will combine the progress information of the current flight mission, such as the current flight speed, flight altitude, remaining distance, etc., to estimate the time required to complete the current task. For example, if historical data shows that it takes an average of 10 minutes for a drone to complete the current task under similar conditions, and the current task has been executed for 5 minutes, then the system can infer that it will take another 5 minutes to complete the current task.

[0086] S212: A shooting parameter setting box pops up on the display terminal at the task execution time.

[0087] The system will set a timer or trigger according to the next task execution time point calculated in step S211. When the time point arrives, the system will send an instruction to the display terminal through the wireless communication module to notify it to pop up the shooting parameter setting box. The display terminal can be a device such as a ground control station, a tablet computer or a smart phone. The shooting parameter setting box is a user interface element that contains detailed information about the current shooting parameters, such as exposure time, ISO value, aperture size, etc. These parameters can be adjusted according to current environmental conditions and task requirements. For example, if the drone is about to enter an area with large changes in light, the system can suggest adjusting the exposure time and ISO value. The operator can view and confirm these parameters, or manually adjust them according to actual conditions. After the user confirms, the display terminal will send the adjusted parameters back to the drone system through the wireless communication module, so that the drone will use the new shooting parameters when performing the next task.

[0088] In some embodiments, the pop-up and confirmation of the shooting parameter setting box can be achieved in a variety of ways: Optionally, through the drone control software, first set a timing trigger according to the calculated task execution time point. When the time point arrives, the system will generate and send a parameter setting instruction to the display terminal. After receiving the instruction, the display terminal pops up the shooting parameter setting box, displays the current shooting parameters, and provides confirmation and adjustment options. Optionally, through a mobile application, the application maintains data synchronization with the drone system. When the task execution time point arrives, the application will automatically pop up the shooting parameter setting box, and the user can view and adjust the parameters on the interface.

[0089] S213: After receiving the confirmation instruction sent by the display terminal, apply the predicted shooting parameters to the aerial survey camera.

[0090] Specifically, in the drone aerial survey system, in order to ensure the quality of shooting and the smooth progress of the task, the system needs to adjust the shooting parameters according to the real-time environment and task requirements. The purpose of step S213 is to apply these parameters to the drone's aerial survey camera after the operator confirms the shooting parameters. First, the system will pop up a shooting parameter setting box on the display terminal (as described in step S212), and the operator can view, adjust and confirm these parameters. After confirmation, the display terminal will send a confirmation instruction and shooting parameters to the drone system. This communication process is usually completed through a wireless communication module (such as Wi-Fi, 4G / 5G network). After receiving the confirmation instruction and shooting parameters, the drone system will parse these data and apply the new shooting parameters to the aerial survey camera. For example, if the new shooting parameters include an exposure time of 1 / 200 seconds, an ISO value of 400, and an aperture of f / 11, the system will set these parameters to the camera through a camera control interface (such as an API or a dedicated control protocol).

[0091] S214: Calculate the flight time required to complete the remaining flight missions according to the historical mission execution time and the current flight mission progress of the UAV.

[0092] Specifically, in a UAV aerial survey system, accurately predicting the time required for the remaining flight mission can help optimize mission planning and resource management. The purpose of this step is to calculate the time required to complete the remaining flight mission based on the historical mission execution time and the current mission progress.

[0093] First, the system analyzes the historical data of the drone performing similar tasks, including the time consumption of each task node, which is usually stored in the task database or log file. Next, the system obtains the progress information of the drone's current flight mission, such as the current waypoint, flight speed and altitude. Combining this data, the system can estimate the time required to complete the remaining tasks. For example, if historical data shows that it takes an average of 15 minutes for the drone to travel from the current waypoint to the next shooting point, and the current task has been executed for 10 minutes, the system can infer that it will take another 5 minutes to complete the current task. The system will summarize these estimates and calculate the total time to complete the entire remaining task.

[0094] S215, calculating the power consumption of the task within the flight time.

[0095] Specifically, in the UAV aerial survey system, accurately calculating the power required for the flight mission is the key to ensure the successful completion of the mission. The purpose of step S215 is to predict the power consumption required during the mission based on the calculated remaining flight time. First, the system estimates the power consumption based on the remaining flight time calculated in step S214, combined with the battery performance data of the UAV and the mission environment parameters. The battery performance data of the UAV usually includes battery capacity (such as mAh or Wh), discharge curve and efficiency, which can be obtained from the specification sheet provided by the battery manufacturer. Next, the system considers the specific requirements of the flight mission, including factors such as flight speed, altitude, ambient temperature and wind speed, because these factors will affect power consumption. For example, in a high wind speed environment, the aircraft needs more energy to maintain stability, thereby increasing power consumption. The system will calculate through a power consumption model, which can be a linear model based on empirical data or a more complex simulation model. For example, if the remaining flight time is 30 minutes, and historical data shows that the power consumption rate is 5Wh per minute under similar conditions, the total power consumption is expected to be 150Wh.

[0096] S216: If the current power of the drone is lower than the power consumption of the mission, a warning message is sent to the display terminal for display.

[0097] Specifically, in the UAV aerial survey system, power management is crucial because the completion of the flight mission depends on sufficient power supply. The purpose of this step is to send a warning message to the operator in time when the system detects that the current power of the UAV is lower than the power required to complete the remaining mission, so as to prevent the mission from being interrupted or the UAV from losing contact. First, the system will monitor the power of the UAV battery in real time and obtain data such as the current voltage, current and remaining power through the battery management system (BMS). At the same time, the system will compare the task power consumption calculated in the previous step (S215) with the current power. If the current power is lower than the expected task power consumption, the system will trigger the warning mechanism. The warning information includes the current power, the expected power consumption, the remaining flight time and the recommended countermeasures (such as returning home immediately or replacing the battery). This information will be sent to the operator's display terminal, such as a ground control station, a tablet computer or a smart phone, through a wireless communication module. After receiving the warning information, the display terminal will pop up a prompt box or notification on the interface to ensure that the operator can see it in time and take necessary measures. For example, if the current power of the UAV is 20%, and it is estimated that 30% of the power is required to complete the remaining mission, the system will send a warning message to suggest that the operator return home immediately or land in a safe area.

[0098] S217, obtaining historical shooting parameters of the aerial survey camera, and counting the most frequently used user shooting parameters, wherein the user shooting parameters include exposure time, aperture size, and ISO sensitivity.

[0099] Specifically, in the UAV aerial survey system, optimizing the shooting parameter settings can significantly improve image quality and task efficiency. The purpose of this step is to analyze the historical shooting parameters of the aerial survey camera and count the most frequently used user shooting parameters to provide reference for subsequent tasks. First, the system extracts the historical shooting data of the aerial survey camera from the database. These data usually record the specific parameters of each shooting, including exposure time, aperture size, and ISO sensitivity. Then, the system performs statistical analysis on these data to calculate the frequency of use of each shooting parameter. For example, if the settings of exposure time of 1 / 100 second, aperture size of f / 8, and ISO sensitivity of 400 are used most frequently in past tasks, then these parameter combinations will be marked as the most commonly used user shooting parameters. Statistical analysis can be achieved through data mining techniques, such as SQL query, data aggregation, and frequency analysis. The system stores these most commonly used shooting parameters as a parameter set for reference and quick setting of subsequent tasks. The results of this step can not only help operators quickly select appropriate shooting parameters and improve task efficiency, but also ensure the consistency of image quality.

[0100] S218: Generate the user shooting parameter into a first user mode.

[0101] Specifically, in the drone aerial survey system, in order to simplify the operator's workflow, the system can save commonly used shooting parameters as user modes for quick call. The purpose of this step is to generate the most commonly used user shooting parameters counted in step S217 as the first user mode. First, the system will package these shooting parameters (such as exposure time, aperture size, and ISO sensitivity) into a parameter set. Then, the system will provide an option in the user interface or control software for the operator to save this parameter set as a user mode. This user mode can be identified by a simple name, such as "default mode" or "high light mode". The process of saving the user mode can be implemented through the software interface, and the operator can complete it with just a few clicks. For example, in the settings menu of the drone control software, the operator can select "Save current settings as user mode", then enter a name and confirm. The system will save the current shooting parameters to the memory or database for quick call of subsequent tasks.

[0102] S219: Display the predicted shooting parameters on the display terminal.

[0103] In the UAV aerial survey system, timely display of predicted shooting parameters helps operators quickly evaluate and adjust task settings. The purpose of this step is to display the shooting parameters predicted by the system on the display terminal for the operator's reference and confirmation. In the specific implementation process, first, the system will calculate the optimal shooting parameters, including exposure time, aperture size, and ISO sensitivity, based on task requirements, environmental conditions, and historical data. Then, these parameters are transmitted to the ground control station or other display terminals, such as tablets or smartphones, through the wireless communication module.

[0104] In the interface design of the display terminal, there should be a dedicated area or pop-up window for displaying these predicted shooting parameters. This area includes detailed descriptions of the parameters and visualization tools (such as sliders and value input boxes) so that operators can intuitively view and adjust the parameters. For example, the interface can display information such as "exposure time: 1 / 200 seconds", "aperture: f / 8", "ISO: 400", and provide appropriate controls for operators to fine-tune.

[0105] S220: If it is detected that there is no operation response from the display terminal within a preset time period, the predicted shooting parameter on the display terminal is hidden.

[0106] In the UAV aerial survey system, in order to avoid the interface being too crowded and the operator being overloaded with information, the system needs to hide unnecessary information in certain situations. The purpose of this step is to automatically hide the predicted shooting parameters when the display terminal detects that the operator has no operational response within a preset time period, so as to keep the interface simple and clear.

[0107] During the specific implementation process, first, the system sets a predefined time period without operation response (for example, 30 seconds or 1 minute). On the display terminal, when the predicted shooting parameters are displayed, the system starts a timer. If the operator does not perform any operation (such as clicking, sliding or input) during this time period, the timer will continue to count. If the timer reaches the preset time limit and still no operation response is detected, the system will trigger the hiding function.

[0108] The implementation of the hidden function can be accomplished in a variety of ways. For example, the system can use animation effects to fade out the predicted shooting parameter area, or directly minimize the parameter window to a corner of the screen. The hidden parameters are not deleted, but remain in the background, and the operator can redisplay them through specific operations (such as clicking a button or hovering the mouse).

[0109] The following describes the drone aerial survey system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of a physical device structure of the UAV aerial survey system in an embodiment of the present application.

[0110] It should be noted that Figure 3 The structure of the UAV aerial survey system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0111] like Figure 3 As shown, the drone aerial survey system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0112] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0113] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0114] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0116] Specifically, the drone aerial survey system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the drone image transmission screen general aerial survey camera information display method provided in the above embodiment is implemented.

[0117] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the unmanned aerial survey system described in the above embodiment; or may exist independently without being assembled into the unmanned aerial survey system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the unmanned aerial survey system, the unmanned aerial survey system implements the method for displaying information of the unmanned aerial survey camera provided in the above embodiment.

[0118] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0119] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0120] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for displaying information of drone image transmission images and aerial survey cameras. It is characterized in that Applied to a UAV aerial survey system, the method comprises: Acquire a current display screen of an aerial survey camera, and monitor the current display screen to obtain a plurality of continuous frames of the current display screen, wherein the aerial survey camera is placed on a drone; Calculating the picture similarity between the previous frame and the next frame in the plurality of continuous frames; If the picture similarity is lower than a preset similarity threshold, the next frame of the picture is analyzed to obtain picture parameters; Matching corresponding predicted shooting parameters in a preset picture parameter-shooting parameter mapping table according to the picture parameters; Popping up a shooting parameter setting box on the display terminal and sending a prompt message, wherein the shooting parameter setting box includes predicted shooting parameters, and the prompt message is used to ask the user whether to use the predicted shooting parameters; After receiving the confirmation instruction sent by the display terminal, the predicted shooting parameters are applied to the aerial survey camera.

2. The method according to claim 1, It is characterized in that The step of calculating the picture similarity between the previous frame and the next frame in the plurality of continuous frames specifically comprises: Extracting key point features of the previous frame and the next frame based on a feature point detection algorithm to obtain a first key point feature corresponding to the previous frame and a second key point feature corresponding to the next frame; Matching the first key point feature with the second key point feature to obtain a matching feature point; The ratio of the total number of feature points in the previous frame to the number of matching feature points is calculated to obtain the picture similarity between the previous frame and the next frame.

3. The method according to claim 1 or 2, It is characterized in that After the step of applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal, the method further includes: Obtaining the current flight mission of the UAV in the flight route; Calculate the task execution time point of the next flight task according to the historical task execution time and the current flight task progress of the UAV; At the task execution time, a shooting parameter setting box pops up on the display terminal; After receiving the confirmation instruction sent by the display terminal, the predicted shooting parameters are applied to the aerial survey camera.

4. The method according to claim 3, It is characterized in that After the step of applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal, the method further includes: Calculate the flight time required to complete the remaining flight missions based on the historical mission execution time and the current flight mission progress of the UAV; Calculate the power consumption of the task required within the flight time; If the current power of the drone is lower than the power consumption of the mission, a warning message is sent to the display terminal for display.

5. The method according to claim 1, It is characterized in that After the step of applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal, the method further includes: Obtain historical shooting parameters of the aerial survey camera, and count the most frequently used user shooting parameters, wherein the user shooting parameters include exposure time, aperture size, and ISO sensitivity; generating the user shooting parameter as a first user mode; When a first user mode selection instruction sent by the display terminal is received, the user shooting parameter is applied to the aerial survey camera.

6. The method according to claim 1, It is characterized in that After the step of applying the predicted shooting parameters to the aerial survey camera after receiving the confirmation instruction sent by the display terminal, the method further includes: Displaying the predicted shooting parameters on the display terminal; If it is detected that there is no operation response from the display terminal within a preset time period, the predicted shooting parameters on the display terminal are hidden.

7. The method according to claim 1, It is characterized in that After the step of calculating the picture similarity between the previous frame and the next frame in the plurality of continuous frames, the method further comprises: If the picture similarity is not lower than a preset similarity threshold, the current shooting parameters are sent to the display terminal so that the current shooting parameters are displayed on the display terminal.

8. A drone aerial survey system, It is characterized in that The UAV aerial survey system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the UAV aerial survey system to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, It is characterized in that When the instruction is executed on the UAV aerial survey system, the UAV aerial survey system is caused to execute the method as described in any one of claims 1-7.

10. A computer program product, It is characterized in that When the computer program product runs on a UAV aerial survey system, the UAV aerial survey system is enabled to perform the method according to any one of claims 1 to 7.

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