Low-altitude unmanned flight image transmission platform

Abstract

The invention relates to the field of image transmission platforms, in particular to a low-altitude unmanned flight image transmission platform. An image used by a current civil unmanned aerial vehicle for shooting is transmitted through a camera directly installed above the unmanned aerial vehicle and a simple signal transmitting device. A user has a requirement on the quality or transmission delay of an image shot by an unmanned aerial vehicle, the image transmission above the unmanned aerial vehicle is often used for carrying out simple processing or carrying out secondary processing on the image data after the image data is received, so that the quality of the obtained image is not high and a fault is easy to occur. According to the low-altitude unmanned flight image transmission platform provided by the invention, early-stage shot images and post-stage processed images are integrated in one system, so that the stability of the quality of the shot images is ensured; and meanwhile, the transmission module installed on the unmanned aerial vehicle is used for carrying out data compression processing on the image data and then sending the image data to the processing system located on the ground for further processing, so that the possible increased burden of the integrated system on the unmanned aerial vehicle is avoided on the premise of ensuring the integrity of the system.

Description

Technical Field

[0001] The present invention relates to the field of image transmission platforms, and in particular to a low-altitude unmanned flying image transmission platform. Background Art

[0002] At present, drone technology has developed greatly. Drones are widely used in transportation, military, and aerial photography with their flexibility and terrain-crossing capabilities. However, due to the limitations of existing technology and hardware, the civilian use of drones is currently limited to shooting within a limited range. On the other hand, the image transmission used by current civilian drones for shooting is a camera directly installed on the top of the drone and a simple signal sending device. However, civilian drones cannot guarantee stability in terms of signals and wireless transmission. If users have requirements for the image quality or transmission delay of drone photos, they often rely on the image transmission above the drone for simple processing or secondary processing of the image data after receiving it. The former will increase the burden on the image transmission and increase the possibility of problems with the image transmission, while the image data obtained by the latter has already undergone a data conversion. Once the image data is too distorted, there is a lack of means to restore the distortion of the image data. The current civilian image transmission equipment on the market is still limited to simple cameras with data sending functions. Not only is the quality of the images obtained not high, but they are also prone to malfunctions.

[0003] In this case, an image transmission platform is needed that can perform shooting and image processing at the same time. At the same time, the image platform can separate the shooting device from the image processing device. The shooting device is installed on the drone for real-time transmission of the captured images, and the image processing device is installed on the ground to process the first-hand images received according to user needs. Summary of the invention

[0004] In order to achieve the above-mentioned purpose, the present invention proposes a low-altitude unmanned aerial image transmission platform, including the following contents: A low-altitude unmanned flying image transmission platform, characterized in that the image transmission platform comprises: Front-end acquisition module: uses drones to take optical images that meet user needs, converts the taken optical images into image data that can be transmitted, stores them, and sends them to the data transmission module; Data transmission module: compresses and encodes the received image data in different ways according to different requirements, sends the compressed and encoded image data to the mid-end processing module through wireless transmission, and receives instructions transmitted from the mid-end processing module; Mid-end processing module: decodes the received image data and reduces noise to restore the original image data, further corrects the restored image data according to the temporal continuity of the image data, performs secondary processing on the corrected image data according to user requirements, and adjusts the data processing method of the data transmission module and the optical image shooting method of the front-end acquisition module according to user requirements for images; Back-end interactive module: restores the processed image data to an optical image, displays the optical image taken by the drone after error correction in real time through the display device, identifies the target object in the optical image based on image recognition technology, and sends the user's image requirements to the mid-end processing module.

[0005] Furthermore, the front-end acquisition module uses a high-definition camera installed on the drone to shoot objects around the drone. The front-end acquisition module determines the clarity of the optical image taken and its orientation relative to the drone by adjusting the high-definition camera, and reduces the impact of environmental factors on the quality of the optical image, so that the quality of the final optical image meets the requirements.

[0006] Furthermore, the method for converting the optical image into image data capable of being transmitted is: after sampling the optical image, quantizing the grayscale value of the optical image; The principle of image sampling is: The optical image is converted into continuous pixel points and then discretized and sampled. The discretization sampling interval is determined by the demand. The smaller the discretization sampling interval, the higher the resolution of the generated image data. The discretization formula is: in, is the pixel point at each position in the discretized image, is the required optical image length, is the required width of the optical image, is the pixel point at each position in the optical image, is the length of the optical image, is the width of the optical image; The optical image uses pixels as the basic measurement unit; The principle of gray value quantization is: After the optical image is discretized and sampled, the grayscale values ​​of the quantized pixels are extracted and the grayscale values ​​are graded according to the user's requirements for the image, and the graded mapped grayscale values ​​are further compressed; The formula expressing the quantitative relationship is: in Represents the gray value mapped after each pixel is graded. The number of bits representing the optical image, Represents the number of grades, Represents the quantized gray value of each pixel. Represents a fuzzy value parameter; After image sampling and gray value quantization, the optical image is converted into gray value data, namely the image data, after being compressed without substantial distortion.

[0007] Furthermore, the selection of different methods for compressing and encoding the received image data according to different methods based on the difference in requirements is affected by the surrounding environment and the user's requirements for images, and the difference between different methods lies in the impact on the image quality and transmission delay, and the image quality is proportional to the transmission delay; when the surrounding environment is poor and the user's requirements for image quality are higher, the data transmission module will improve the image quality and the transmission delay, and when the surrounding environment is good and the user's requirements for image transmission delay are lower, the data transmission module will reduce the image quality and the transmission delay.

[0008] Furthermore, the compression coding compresses the volume of the image data by coding under the premise of ensuring that the accuracy of the image data is not significantly affected, and the compression coding method is divided into lossless coding and lossy coding; Lossless coding: By writing each symbol in the image data into codewords of different lengths according to the information entropy, the volume of the image data is greatly compressed. The formula representing the principle of lossless coding is: in is the coding entropy. The lower the coding entropy, the better the compression effect. is the total number of symbols in the image data, is the total information entropy of the image data, is the code length corresponding to different symbols, The number of bits representing the optical image; Through repeated calculations, the minimum value of the coding entropy is finally found. At this time, the lossless compression effect is optimal, and the code length corresponding to different symbols also reaches the optimal length; Lossy coding: Using DCT discrete transformation, the image data is converted into a continuous curve by discarding the high-frequency components in the image data. The formula representing the lossy coding principle is: in, is the transformed curve function, is the correlation coefficient, is the length of the image data, is the width of the image data, is the gray value of different positions of the image data, is a specific number of rows of image data, , is the specific number of columns of image data, The number of bits representing the optical image, represents the horizontal coordinate of the curve function, The ordinate represents the curve function; The compression coding meets the user's demand for images by using lossless coding and compression coding. The lossless coding and compression coding use the same wireless transmission method.

[0009] Furthermore, the mid-end processing module adopts decoding corresponding to the compression code used, performs noise reduction processing on the decoded compression code after decoding, obtains the decompressed image data, sorts the decompressed image data in the order of generated frame numbers, compares the image data of adjacent frames, and modifies specific problematic data in the image data.

[0010] Furthermore, the specific method of error correction is: S1. specifying that for the image data of a specific frame, a specific number of other frames of the image data adjacent thereto are specified as references; S2. Setting a comparison threshold, and comparing all reference objects with the image data of a specific frame, and screening out all positions in the image data of a specific frame that differ from the reference object by more than the comparison threshold; S3. extract the data from all references according to the selected positions, further compare and lower the comparison threshold, select the majority reference, and repeat this process until the only reference is selected; S4. For the image data of a specific frame, average the image data of the previous frame, the image data of the next frame and the grayscale value of the unique reference object at the filtered position, and use the average grayscale value to replace the grayscale value of the image data of the specific frame at the filtered position.

[0011] Furthermore, the mid-end processing module can also record the image data of the specific object that needs to be identified uploaded by the user through the interactive module. The mid-end processing module can determine whether the specific object exists in the optical image and determine the position of the specific object in the optical image by comparing the image data of the specific object with the error-corrected image data, and mark the position of the specific object on the optical image with a box when the back-end interactive module displays the optical image. The mid-end processing module is also used to store the image data.

[0012] Furthermore, the back-end interaction module includes a physical display device that can interact with the user, which is used to restore the image data into the optical image according to the change of grayscale value for display and allow the user to change the user's image requirements in real time. The user's image requirements include requirements for image quality, shooting brightness and transmission delay.

[0013] Furthermore, the front-end acquisition module and the data transmission module are installed on the drone, and the mid-end processing module is separated from the back-end interaction module and the drone for user use. When the data transmission module loses contact with the mid-end processing module, the data transmission module temporarily stores the processed image data. When the front-end acquisition module fails, the data transmission module sends fault information to the mid-end processing module and shuts down the front-end acquisition module.

[0014] Beneficial effects: 1. The pre-shot images and post-processed images are concentrated in one system to ensure the stability of the captured image quality. At the same time, the image data is compressed and processed by the transmission module installed on the drone and then sent to the processing system on the ground for further processing. Under the premise of ensuring the integrity of the system, the burden that the integrated system may add to the drone is avoided; 2. By separating and modularizing the various functions in the image transmission platform, the drone can continue to shoot and store images even when wireless transmission fails. It also provides users with the authority to adjust the various functions in the image transmission platform, allowing users to adjust the working mode and working parameters of each module in real time according to their needs, and quickly obtain images that meet their needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a structural diagram of the low-altitude unmanned flying image transmission platform of the present invention; Figure 2 The present invention is a flowchart of the low-altitude unmanned aerial image transmission platform. DETAILED DESCRIPTION

[0016] In order to achieve the above-mentioned purpose, the present invention proposes a low-altitude unmanned aerial image transmission platform, including the following contents: like Figure 1 As shown, a low-altitude unmanned flying image transmission platform includes: Front-end acquisition module: uses drones to take optical images that meet the user's image requirements, converts the taken optical images into image data that can be transmitted, stores them, and sends them to the data transmission module; The front-end acquisition module uses a high-definition camera installed on the drone to shoot objects around the drone. The front-end acquisition module determines the clarity of the optical image and its relative position to the drone by adjusting the high-definition camera, and reduces the impact of environmental factors on the quality of the optical image, so that the quality of the final optical image meets the requirements.

[0017] The method of converting the optical image into image data capable of being transmitted is as follows: after sampling the optical image, the grayscale value of the optical image is quantified; The principle of image sampling is: The optical image is converted into continuous pixel points and then discretized and sampled. The discretization sampling interval is determined by the demand. The smaller the discretization sampling interval, the higher the resolution of the generated image data. The discretization formula is: in, is the pixel point at each position in the discretized image, is the required optical image length, is the required width of the optical image, is the pixel point at each position in the optical image, is the length of the optical image, is the width of the optical image; Optical images use pixels as the basic unit of measurement; The principle of gray value quantization is: After the optical image is discretized and sampled, the grayscale values ​​of the pixels are extracted and quantified, and the grayscale values ​​are graded according to the user's requirements for the image, and the graded mapped grayscale values ​​are further compressed; The formula expressing the quantitative relationship is: in Represents the gray value mapped after each pixel is graded. The number of bits representing the optical image, Represents the number of grades, Represents the quantized gray value of each pixel. Represents a fuzzy value parameter; After image sampling and grayscale value quantization, the optical image is converted into grayscale value data, namely image data, after the volume is compressed.

[0018] The front-end acquisition module is divided into a camera and a converter. The camera of the front-end acquisition module has the ability to rotate at an angle and can adjust the shooting angle and focal length of the camera. The converter is used to convert optical images into image data. The converter is installed inside the camera to reduce the probability of damage and reduce the size of the front-end acquisition module.

[0019] Data transmission module: compresses and encodes the received image data in different ways according to different requirements, sends the compressed and encoded image data to the mid-end processing module through wireless transmission, and receives instructions transmitted from the mid-end processing module; The received image data is compressed and encoded according to different methods, wherein the selection of different methods is affected by the surrounding environment and user needs, and the difference between different methods lies in the impact on image quality and transmission delay, and the image quality is proportional to the transmission delay; when the surrounding environment is poor and the user's demand for image quality is high, the data transmission module will improve the image quality and transmission delay, and when the user's demand for transmission delay is low, the data transmission module will reduce the image quality and transmission delay; Compression coding compresses the volume of image data by coding under the premise of ensuring that the accuracy of image data is not significantly affected. Compression coding methods are divided into lossless coding and lossy coding. Lossless coding: by writing each symbol in the image data into codewords of different lengths according to the information entropy, the volume of image data is greatly compressed. The formula representing the principle of lossless coding is: in is the coding entropy. The lower the coding entropy, the better the compression effect. is the total number of symbols in the image data, is the total information entropy of the image data, is the code length corresponding to different symbols, The number of bits representing the optical image; Through repeated calculations, the minimum value of the coding entropy is finally found. At this time, the lossless compression effect is optimal, and the code length corresponding to different symbols also reaches the optimal length; Lossy coding: Using DCT discrete transform, the image data is converted into a continuous curve by discarding the high-frequency components in the image data. The formula representing the lossy coding principle is: in, is the transformed curve function, is the correlation coefficient, is the length of the image data, is the width of the image data, is the gray value of different positions of the image data, is a specific number of rows of image data, , is the specific number of columns of image data, The number of bits representing the optical image, represents the horizontal coordinate of the curve function, The ordinate represents the curve function; Compression coding meets user needs by using lossless coding and compression coding. Lossless coding and compression coding use the same wireless transmission method, and the wireless transmission method is directly affected by the external environment. Compression coding is more resistant to external environmental interference than lossless coding.

[0020] The data transmission module is also responsible for the compression and transmission of image data, which directly affects the delay speed of users receiving images and directly affects the user experience. On the other hand, the transmitted image data will inevitably be distorted during the transmission process. Due to structural problems, the mid-end processing module cannot improve the quality of the received image data and repair some details, that is, the processing of the data transmission module has an irreversible impact on the image quality and details received by the user. Therefore, the transmission method has both indirect and direct effects on the image quality and delay; after completing the compression of the image data, the wireless transmission method of the data module is adjusted accordingly according to the changes in the environment. In order to match the low-altitude flight of the drone, the wireless transmission methods used by the data module include: Bluetooth, WIFI, 4G / / 5G, ZigBee. From left to right, the transmission speed and image quality also decrease, while the anti-interference ability increases. The data transmission module meets the needs of users and offsets the interference caused by the wireless transmission environment by adjusting the wireless transmission method used.

[0021] Mid-end processing module: decodes the received image data and reduces noise to restore the original image data, further corrects the restored image data according to the temporal continuity of the image data, performs secondary processing on the corrected image data according to user requirements, and adjusts the data processing method of the data transmission module and the optical image shooting method of the front-end acquisition module according to user needs; The mid-end processing module adopts decoding corresponding to the compression code used, performs noise reduction processing on the decoded compression code after decoding, obtains decompressed image data, sorts the decompressed image data in the order of generated frame numbers, compares the image data of adjacent frames, and modifies the problem data in specific image data.

[0022] The specific methods of error correction are: S1. For a specific frame of image data, a specific number of other frames of image data adjacent thereto are specified as references; S2. Setting a comparison threshold, and comparing all reference objects with the image data of a specific frame, and screening out all positions in the image data of the specific frame whose differences with all reference objects exceed the comparison threshold; S3. extract the data from all references according to the selected positions, further compare and lower the comparison threshold, select the majority reference, and repeat this process until the only reference is selected; S4. For the image data of a specific frame, the grayscale values ​​of the image data of the previous frame, the image data of the next frame and the unique reference object at the selected position are averaged, and the grayscale value of the image data of the specific frame at the selected position is replaced by the average grayscale value.

[0023] like Figure 2 As shown, the mid-end processing module can also record the image data of the specific object that needs to be identified uploaded by the user through the interactive module. The mid-end processing module can determine whether the specific object exists in the optical image and determine the position of the specific object in the corresponding optical image by comparing the image data of the specific object with the image data after error correction, and mark the position of the specific object on the optical image with a box when the back-end interactive module displays the optical image. The mid-end processing module is also used to store image data.

[0024] After decompressing the received compressed image data, before processing the image data, the mid-end processing module also performs noise reduction processing on the decompressed image data to reduce image distortion caused by interference during transmission. Since the data transmission module selects a suitable wireless transmission method, the image data is subject to limited interference from the external environment. Therefore, the mid-end processing module does not use noise reduction processing with too good an effect to avoid over-noise reduction. According to the user's demand for image quality, mean filtering or bilateral filtering is used, where the formula for mean filtering is: in, is the pixel value after filtering, () represents the formula for converting grayscale value into pixel value. Represents the grayscale value of different positions in the image, Represents the size of the filter.

[0025] Through fast conversion, the mean transform can quickly reduce the noise of the grayscale values ​​at different positions in the image data and convert them into pixel values ​​that can be observed by users. The smaller the filter size, the better the filtering effect, and the correspondingly slower the filtering speed. Users can change the filter size through the back-end interactive module according to their needs to balance the quality and conversion speed of the optical image of the mid-end processing module.

[0026] Back-end interactive module: restores the processed image data to an optical image, displays the optical image taken by the drone after error correction in real time through the display device, identifies the target object in the optical image based on image recognition technology, and sends user requirements to the mid-end processing module.

[0027] The back-end interaction module includes a physical display device that can interact with the user, which is used to restore the image data into an optical image according to the change of grayscale value for display and for the user to change in real time according to user needs. The user needs include the needs for image quality, the needs for shooting brightness and the needs for transmission delay. The user decides through the back-end interaction module whether to receive a single-frame optical image or a continuous optical image video.

[0028] The back-end interaction module is used to send commands and receive data, and is connected to the interrupt processing module through wired or wireless connections. The back-end interaction module can also remotely connect to the user's audio and video equipment, allowing the user to remotely read the image displayed in the back-end interaction module. At the same time, the back-end interaction module can also connect to the drone control system to display the images taken by the drone in the drone control system, forming a more integrated drone system and realizing dual control of the drone and the image transmission device.

[0029] The front-end acquisition module and the data transmission module are installed on the drone, and the mid-end processing module is separated from the back-end interaction module and the front-end acquisition module and the drone for user use. When the data transmission module loses contact with the mid-end processing module, the data transmission module temporarily stores the processed image data. When the front-end acquisition module fails, the data transmission module sends a fault message to the mid-end processing module and shuts down the front-end acquisition module.

[0030] The above-mentioned embodiments only express the preferred implementation modes of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person skilled in the art, several modifications, improvements and substitutions can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the attached claims.

Claims

1. A low-altitude unmanned aerial image transmission platform, characterized in that: The image transmission platform includes: Front-end acquisition module: uses drones to take optical images that meet user needs, converts the taken optical images into image data that can be transmitted, stores them, and sends them to the data transmission module; Data transmission module: compresses and encodes the received image data in different ways according to different requirements, sends the compressed and encoded image data to the mid-end processing module through wireless transmission, and receives instructions transmitted from the mid-end processing module; Mid-end processing module: decodes the received image data and reduces noise to restore the original image data, further corrects the restored image data according to the temporal continuity of the image data, performs secondary processing on the corrected image data according to user requirements, and adjusts the data processing method of the data transmission module and the optical image shooting method of the front-end acquisition module according to user requirements for images; Back-end interactive module: restores the processed image data to an optical image, displays the optical image taken by the drone after error correction in real time through the display device, identifies the target object in the optical image based on image recognition technology, and sends the user's image requirements to the mid-end processing module.

2. A low-altitude unmanned aerial image transmission platform according to claim 1, characterized in that: The front-end acquisition module uses a high-definition camera installed on the drone to shoot the objects around the drone. The front-end acquisition module determines the clarity of the optical image taken and its orientation relative to the drone by adjusting the high-definition camera, and reduces the impact of environmental factors on the quality of the optical image, so that the quality of the optical image finally obtained meets the requirements.

3. A low-altitude unmanned aerial image transmission platform according to claim 2, characterized in that: Said The method of converting the optical image into image data capable of being transmitted is: after sampling the optical image, quantizing the gray value of the optical image; The principle of image sampling is: The optical image is converted into continuous pixel points and then discretized and sampled, wherein the discretized sampling interval is determined by demand. The smaller the discretized sampling interval, the higher the resolution of the generated image data. The discretization formula is: in, is the pixel point at each position in the discretized image, is the required optical image length, is the required width of the optical image, is the pixel point at each position in the optical image, is the length of the optical image, is the width of the optical image; The optical image uses pixels as the basic measurement unit; The principle of gray value quantization is: After the optical image is discretized and sampled, the grayscale values ​​of the quantized pixels are extracted and the grayscale values ​​are graded according to the user's requirements for the image, and the graded mapped grayscale values ​​are further compressed; The formula expressing the quantitative relationship is: in Represents the gray value mapped after each pixel is graded. The number of bits representing the optical image, Represents the number of grades, Represents the quantized gray value of each pixel. Represents a fuzzy value parameter; After image sampling and gray value quantization, the optical image is converted into gray value data, namely the image data, after being compressed without substantial distortion.

4. A low-altitude unmanned aerial image transmission platform according to claim 3, characterized in that: The selection of different methods for compression encoding of received image data according to different requirements is affected by the surrounding environment and the user's requirements for images. The difference between different methods lies in the impact on the image quality and transmission delay, and the image quality is proportional to the transmission delay; when the surrounding environment is poor and the user's requirements for image quality are high, the data transmission module will improve the image quality and the transmission delay, and when the surrounding environment is good and the user's requirements for image transmission delay are low, the data transmission module will reduce the image quality and the transmission delay.

5. The low-altitude unmanned aerial image transmission platform according to claim 4, characterized in that: The compression coding compresses the volume of the image data by coding under the premise of ensuring that the accuracy of the image data is not significantly affected. The compression coding method is divided into lossless coding and lossy coding; Lossless coding: By writing each symbol in the image data into codewords of different lengths according to the information entropy, the volume of the image data is greatly compressed. The formula representing the principle of lossless coding is: in is the coding entropy. The lower the coding entropy, the better the compression effect. is the total number of symbols in the image data, is the total information entropy of the image data, is the code length corresponding to different symbols, The number of bits representing the optical image; Through repeated calculations, the minimum value of the coding entropy is finally found. At this time, the lossless compression effect is optimal, and the code length corresponding to different symbols also reaches the optimal length; Lossy coding: Using DCT discrete transformation, the image data is converted into a continuous curve by discarding the high-frequency components in the image data. The formula representing the lossy coding principle is: in, is the transformed curve function, is the correlation coefficient, is the length of the image data, is the width of the image data, is the gray value of different positions of the image data, is a specific number of rows of image data, , is the specific number of columns of image data, The number of bits representing the optical image, represents the horizontal coordinate of the curve function, The ordinate represents the curve function; The compression coding meets the user's demand for images by using lossless coding and compression coding. The lossless coding and compression coding use the same wireless transmission method.

6. A low-altitude unmanned aerial image transmission platform according to claim 5, characterized in that: The mid-end processing module adopts decoding corresponding to the compression code used, performs noise reduction processing on the decoded compression code after decoding, obtains the decompressed image data, sorts the decompressed image data in the order of the number of generated frames, compares the image data of adjacent frames, and modifies the problem data in specific image data.

7. A low-altitude unmanned aerial image transmission platform according to claim 6, characterized in that: The specific method of error correction is: S1. specifying that for the image data of a specific frame, a specific number of other frames of the image data adjacent thereto are specified as references; S2. Setting a comparison threshold, and comparing all reference objects with the image data of a specific frame, and screening out all positions in the image data of a specific frame that differ from the reference object by more than the comparison threshold; S3. extract the data from all references according to the selected positions, further compare and lower the comparison threshold, select the majority reference, and repeat this process until the only reference is selected; S4. For the image data of a specific frame, average the image data of the previous frame, the image data of the next frame and the grayscale value of the unique reference object at the filtered position, and use the average grayscale value to replace the grayscale value of the image data of the specific frame at the filtered position.

8. The low-altitude unmanned aerial image transmission platform according to claim 7, characterized in that: Said The mid-end processing module can also record the image data of the specific object that needs to be identified uploaded by the user through the interactive module. The mid-end processing module can determine whether the specific object exists in the optical image and determine the position of the specific object in the corresponding optical image by comparing the image data of the specific object with the image data after error correction, and mark the position of the specific object on the optical image with a box when the back-end interactive module displays the optical image. The mid-end processing module is also used to store the image data.

9. The low-altitude unmanned aerial image transmission platform according to claim 8, characterized in that: The back-end interaction module includes a physical display device that can interact with the user, which is used to restore the optical image according to the change of grayscale value of the image data for display and provide real-time changes to the user's image requirements, which include requirements for image quality, shooting brightness and transmission delay.

10. The low-altitude unmanned aerial image transmission platform according to claim 9, characterized in that: The front-end acquisition module and the data transmission module are installed on the drone, and the mid-end processing module is separated from the back-end interaction module and the drone for user use. When the data transmission module loses contact with the mid-end processing module, the data transmission module temporarily stores the processed image data. When the front-end acquisition module fails, the data transmission module sends fault information to the mid-end processing module and shuts down the front-end acquisition module.

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