Unmanned aerial vehicle image data efficient compression and rapid transmission system

Abstract

The invention relates to the technical field of unmanned aerial vehicle data transmission systems, and provides an unmanned aerial vehicle image data efficient compression and rapid transmission system which comprises an unmanned aerial vehicle image data management terminal, a data compression terminal, a rapid transmission terminal and a transmission task management terminal. The unmanned aerial vehicle image data management terminal is used for managing a storage behavior, a deletion behavior and a calling behavior of image data in an unmanned aerial vehicle inspection process; the data compression terminal is used for carrying out preprocessing, multi-stage compression and final coding on the stored image data to generate final compressed data; the rapid transmission terminal is used for transmitting the final compressed data according to the requirements of the transmission task; the transmission task management terminal is used for receiving and executing the transmission task. The method has the effect of improving the image data transmission efficiency of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle data transmission systems, and in particular to a system for efficiently compressing and rapidly transmitting unmanned aerial vehicle image data. Background Art

[0002] Drone image data refers to image information captured by drone cameras, usually stored in digital format. Since drones are often used for high-resolution photography, image data files are usually large. Efficient compression means reducing the size of image files as much as possible while maintaining image quality. Fast transmission means shortening the time it takes to transmit image data from the drone to the receiving end.

[0003] Now many drone image data transmission systems have been developed. After a lot of searching and reference, we found that the drone image data transmission systems in the prior art include the drone image data transmission systems disclosed in publication numbers CN110040258A, CN105933653A, CN107483886A, EP3425904A1, US11792129B2, and JP2017224896A. These drone image data transmission systems generally include: drone image data retrieval terminal, data processing terminal, and data transmission terminal; the drone image data retrieval terminal is used to retrieve the image data taken by the drone camera; the data processing terminal is used to filter and compress the image data; the data transmission terminal is used to transmit the processed image data. Since the image data processing process and transmission process of the above-mentioned drone image data transmission system are relatively simple, if the image data of the drone is large and numerous, it is not convenient to complete the transmission in time, resulting in the defect of reduced efficiency of drone image data transmission. Summary of the invention

[0004] The purpose of the present invention is to propose a system for efficiently compressing and quickly transmitting drone image data in response to the shortcomings of the above-mentioned drone image data transmission system.

[0005] The present invention adopts the following technical solution:

[0006] A system for efficiently compressing and rapidly transmitting image data of unmanned aerial vehicles, comprising an image data management terminal for unmanned aerial vehicles, a data compression terminal, a rapid transmission terminal and a transmission task management terminal; the image data management terminal for unmanned aerial vehicles is used to manage the storage, deletion and calling of image data during the inspection process of unmanned aerial vehicles; the data compression terminal is used to perform preprocessing, multi-level compression and final encoding on the stored image data to generate final compressed data; the rapid transmission terminal is used to transmit the final compressed data according to the requirements of the transmission task; the transmission task management terminal is used to receive and execute the transmission task;

[0007] The data compression terminal includes an image preprocessing module, a multi-level compression module and a final encoding module; the image preprocessing module is used to perform noise reduction and smoothing processing on the stored image data; the multi-level compression module is used to perform multi-level compression on the preprocessed image data to generate multi-level compressed data; the final encoding module is used to perform encoding conversion operations on the multi-level compressed data to generate final encoded data.

[0008] Optionally, the multi-level compression module includes a primary compression submodule and a secondary compression submodule; the primary compression submodule is used to perform primary compression on the preprocessed image data, convert the image to the frequency domain to retain the low-frequency components, and quantize the image to generate primary compressed data; the secondary compression submodule is used to perform secondary compression on the primary compressed data, further decompose the image, retain important features, and generate multi-level compressed data.

[0009] Optionally, the final encoding module includes a pixel value occurrence frequency statistics submodule, a Huffman tree construction submodule, a Huffman code allocation submodule and a code conversion submodule; the pixel value occurrence frequency statistics submodule is used to count the occurrence frequency of each pixel value in the image in the multi-level compressed data; the Huffman tree construction submodule is used to construct a Huffman tree according to the pixel value occurrence frequency; the Huffman code allocation submodule is used to allocate Huffman codes to each pixel value in the image according to the Huffman tree; the code conversion submodule is used to convert the pixel values ​​of the image into the corresponding Huffman codes that have been allocated to generate final encoded data.

[0010] Optionally, the fast transmission terminal includes an adaptive transmission adjustment module, a hierarchical transmission scheduling module and a transmission execution module; the adaptive transmission adjustment module is used to adaptively adjust the transmission rate according to real-time changes in the transmission environment; the hierarchical transmission scheduling module is used to determine the transmission priority for the image in the final encoded data form; the transmission execution module is used to perform the transmission task according to the transmission priority and the adjusted transmission rate.

[0011] Optionally, the adaptive transmission adjustment module includes a transmission environment data acquisition submodule and a transmission rate calculation submodule; the transmission environment data acquisition submodule is used to acquire transmission environment data from a transmission environment monitoring device; the transmission rate calculation submodule is used to calculate the transmission rate for all final encoded data in the transmission task based on the transmission environment data.

[0012] Optionally, the hierarchical transmission scheduling module includes a transmission rate reading submodule, a transmission weight calculation submodule and a transmission priority calculation submodule; the transmission rate reading submodule is used to read the transmission rate of each final encoded data in the transmission task; the transmission weight calculation submodule is used to calculate the transmission weight according to the data type of the final encoded data in the transmission task and the data generation time; the transmission priority calculation submodule is used to calculate the corresponding transmission priority according to the transmission rate and transmission weight of the final encoded data.

[0013] A method for efficiently compressing and quickly transmitting drone image data is applied to a system for efficiently compressing and quickly transmitting drone image data as described above. The method for efficiently compressing and quickly transmitting drone image data includes:

[0014] S1, manages the storage, deletion and call of image data during drone inspection;

[0015] S2, preprocessing, multi-level compression and final encoding of the stored image data to generate final compressed data;

[0016] S3, receives and executes the transmission task;

[0017] S4, transmitting the final compressed data according to the requirements of the transmission task.

[0018] The beneficial effects achieved by the present invention are:

[0019] 1. The setting of UAV image data management terminal, data compression terminal, fast transmission terminal and transmission task management terminal improves the system's efficiency in retrieving UAV image data by managing the storage, deletion and call behavior of image data during the UAV inspection process. The system optimizes the image data processing process by preprocessing, multi-level compression and final encoding of the stored image data to generate the final compressed data. The transmission process is optimized by transmitting the final compressed data according to the requirements of the transmission task, which is conducive to improving the system's efficiency in retrieving, processing and transmission of UAV image data, thereby improving the quality and efficiency of UAV image data transmission;

[0020] 2. The setting of the image preprocessing module, the multi-level compression module and the final encoding module is beneficial to improving the compression effect and efficiency of the system on the image data, shortening the transmission time, and thus improving the transmission efficiency of the system for transmitting the UAV image data by preprocessing, multi-level compression and encoding conversion of the image data;

[0021] 3. The primary compression submodule and the secondary compression submodule are set up in conjunction with the primary compression algorithm and the secondary compression algorithm. By dividing the image into equal parts and then performing primary compression, the quality and efficiency of primary compression are improved. Then, by further decomposing the primary compressed data of the image into multi-resolution and multi-frequency domains, the system's compression effect on the image data is further improved, which is conducive to further shortening the transmission time, thereby improving the quality and efficiency of UAV image data transmission;

[0022] 4. The setting of the pixel value occurrence frequency statistics submodule, the Huffman tree construction submodule, the Huffman code allocation submodule and the code conversion submodule is conducive to improving the coding quality and efficiency by counting the occurrence frequency of each pixel value in the image in the multi-level compressed data, constructing the Huffman tree, allocating the Huffman code and converting the pixel value of the image into the corresponding Huffman code that has been allocated to generate the final coded data, thereby improving the coding quality and efficiency of the final coded data, and thus improving the quality and efficiency of the UAV image data transmission;

[0023] 5. The setting of adaptive transmission adjustment module, hierarchical transmission scheduling module and transmission execution module can adaptively adjust the transmission rate through real-time changes in the transmission environment and perform sequential transmission according to the transmission priority, which is conducive to improving the transmission quality and shortening the transmission time, thereby further improving the quality and efficiency of UAV image data transmission;

[0024] 6. The setting of the transmission environment data acquisition submodule and the transmission rate calculation submodule in conjunction with the transmission rate calculation algorithm is conducive to improving the calculation efficiency and accuracy of the transmission rate, thereby improving the quality and efficiency of UAV image data transmission;

[0025] 7. The settings of the transmission rate reading submodule, the transmission weight calculation submodule and the transmission priority calculation submodule cooperate with the transmission priority calculation algorithm to calculate the corresponding transmission priority through the transmission rate and transmission weight of the final encoded data, which is conducive to improving the accuracy and confirmation efficiency of the transmission priority, thereby improving the quality and efficiency of the UAV image data transmission;

[0026] 8. The compression effect evaluation submodule includes a compression ratio calculation unit, a compression efficiency calculation unit and a compression effect evaluation unit, which cooperate with the compression efficiency calculation algorithm and the compression ratio calculation algorithm. The compression efficiency is calculated by the total coding length and the total number of pixels in the final encoded data of the image data, and the compression ratio of the image data is generated by calculating the ratio of the data size before and after the image data is compressed. This is beneficial to improving the calculation efficiency of the compression efficiency and the compression ratio, and then improving the quality and efficiency of the compression effect evaluation, which is beneficial to improving the quality and efficiency of the UAV image data transmission.

[0027] To further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are only for reference and description and are not intended to limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0029] Figure 2 It is a structural schematic diagram of the multi-stage compression module in the present invention;

[0030] Figure 3 It is a structural schematic diagram of the final encoding module in the present invention;

[0031] Figure 4 It is a schematic diagram of the process of image processing one by one in the present invention;

[0032] Figure 5 It is a structural schematic diagram of the adaptive transmission adjustment module in the present invention;

[0033] Figure 6 It is a structural diagram of the hierarchical transmission scheduling module in the present invention;

[0034] Figure 7 A schematic diagram of a method flow of a method for efficient compression and rapid transmission of drone image data in the present invention;

[0035] Figure 8 Schematic diagram of the structure of a compression effect evaluation submodule in another embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following is an explanation of the embodiments of the present invention through specific embodiments. Those skilled in the art can understand the advantages and effects of the present invention from the contents disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and the details in this specification can also be modified and changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. In addition, the drawings of the present invention are only for simple schematic illustration and are not depicted according to actual dimensions. It is stated in advance. The following embodiments will further explain the relevant technical contents of the present invention in detail, but the disclosed contents are not intended to limit the scope of protection of the present invention.

[0037] Embodiment 1: This embodiment provides a system for efficiently compressing and quickly transmitting drone image data. Figure 1As shown, a system for efficient compression and rapid transmission of drone image data comprises a drone image data management terminal, a data compression terminal, a rapid transmission terminal and a transmission task management terminal; the drone image data management terminal is used to manage the storage, deletion and call behavior of image data during the drone inspection process; the data compression terminal is used to perform preprocessing, multi-level compression and final encoding on the stored image data to generate final compressed data; the rapid transmission terminal is used to transmit the final compressed data according to the requirements of the transmission task; the transmission task management terminal is used to receive and execute the transmission task;

[0038] The data compression terminal includes an image preprocessing module, a multi-level compression module and a final encoding module; the image preprocessing module is used to perform noise reduction and smoothing processing on the stored image data; the multi-level compression module is used to perform multi-level compression on the preprocessed image data to generate multi-level compressed data; the final encoding module is used to perform encoding conversion operations on the multi-level compressed data to generate final encoded data.

[0039] Optional, combined Figure 2 As shown, the multi-level compression module includes a primary compression submodule and a secondary compression submodule; the primary compression submodule is used to perform primary compression on the pre-processed image data, convert the image to the frequency domain to retain the low-frequency components, and quantize the image to generate primary compressed data; the secondary compression submodule is used to perform secondary compression on the primary compressed data, further decompose the image, retain important features, and generate multi-level compressed data.

[0040] Specifically, when the primary compression submodule is working, the image is first divided into equal parts and then the image is converted into the frequency domain to generate primary compression data using the following formula:

[0041]

[0042] Among them, F(u,v) represents the point of the image in the two-dimensional frequency domain after primary compression, and also represents the primary compressed data of the image; u and v represent the horizontal and vertical frequency indexes in the frequency domain respectively; f(x,y) represents the pixel value of the point (x,y) in the spatial domain in the original image data; x and y represent the coordinates of the pixel in the image block respectively; N represents the number of image blocks into which the image is equally divided, generally, N=8; α(u) and α(v) both represent normalization coefficients; the formula calculates F(u,v) in the frequency domain by weighted summation of each pixel value f(x,y) in the image block, where the role of the cosine function is to convert the data in the spatial domain to the frequency domain; since most of the energy of the image is concentrated in the low-frequency part of the frequency domain, that is, where u and v are small, the high-frequency part, that is, where u and v are large, can be quantized and compressed through the transformation process of the formula, thereby reducing the amount of data. Through the inverse transformation of the formula, the frequency domain data can be converted back to spatial domain data to achieve image restoration. The above formula transformation process is reversible, which means that under ideal circumstances, the original image can be restored losslessly.

[0043] When the secondary compression submodule is working, the primary compressed data of the image is further decomposed into multi-resolution and multi-frequency domains, satisfying the following formula:

[0044]

[0045] Among them, F q (u,v) represents the primary compressed data after quantization; Q(u,v) represents the standard quantization matrix, which the administrator can directly call or modify based on empirical data and experimental results for reuse; F(u,v) represents the point of the image in the two-dimensional frequency domain after primary compression, and also represents the primary compressed data of the image; W 1 (u,v) represents the multi-level compressed data of the corresponding image; F(t) represents F q (u, v) The data after inverse transformation, which converts the quantized primary compressed data from the frequency domain to the spatial domain, so as to facilitate the correlation parameter t and perform integration processing; By convolving a signal or image with a localized waveform, i.e., the mother wavelet function, the information of the signal at different scales and positions is obtained, thereby achieving secondary compression; A represents the scale parameter, which is set by the administrator based on experience; B represents the translation parameter, which is set by the administrator based on experience; t represents the time variable in the spatial domain; φ(x) represents the mother wavelet function, This formula means that the quantized primary compressed data is inversely transformed and then convolved with the mother wavelet function. By controlling A and B, the image data can be decomposed into multi-resolution and multi-frequency domains. This process can capture the local features of the image or signal, thereby further compressing the data.

[0046] Optional, combined Figure 3 As shown, the final encoding module includes a pixel value occurrence frequency statistics submodule, a Huffman tree construction submodule, a Huffman code allocation submodule and a code conversion submodule; the pixel value occurrence frequency statistics submodule is used to count the occurrence frequency of each pixel value in the image in the multi-level compressed data; the Huffman tree construction submodule is used to build a Huffman tree according to the pixel value occurrence frequency; the Huffman code allocation submodule is used to allocate Huffman code to each pixel value in the image according to the Huffman tree; the code conversion submodule is used to convert the pixel value of the image into the corresponding Huffman code that has been allocated to generate the final encoded data.

[0047] For example, combined with Figure 4 As shown, the process of image processing one by one is used as an example to illustrate:

[0048] A1, read image data.

[0049] A2, calculate the frequency of occurrence of pixel values, and count the frequency of occurrence of each pixel value in the image data; in this embodiment, the image data is multi-level compressed data.

[0050] Specifically, the multi-level compressed data contains the following pixel values ​​and their occurrence times:

[0051] {(0,1000),(1,2000),(2,500),(3,2500)};

[0052] Calculated frequencies: f(0) = 0.167, f(1) = 0.333, f(2) = 0.083; f(3) = 0.417.

[0053] A3, construct a Huffman tree, and use the frequency of occurrence of pixel values ​​to construct a Huffman tree.

[0054] Specifically, the initialization node set is: {(0,0.167),(1,0.333),(2,0.083),(3,0.417)}, and after merging the nodes it becomes: {((((0,2),1),3),1.0)}.

[0055] A4, assign Huffman codes, assign unique binary codes to each symbol according to the Huffman tree.

[0056] Specifically, the example encoding is: 0:110, 1:10, 2:111, 3:0.

[0057] A5, compressing image data, using Huffman coding to perform secondary compression on multi-level compressed data to generate final encoded data.

[0058] Example: The multi-level compressed data is: {0,1,3,2,1,3}, and the final encoded data after compression is:

[0059] {110,10,0,111,10,0}.

[0060] Optionally, the fast transmission terminal includes an adaptive transmission adjustment module, a hierarchical transmission scheduling module and a transmission execution module; the adaptive transmission adjustment module is used to adaptively adjust the transmission rate according to real-time changes in the transmission environment; the hierarchical transmission scheduling module is used to determine the transmission priority for the image in the final encoded data form; the transmission execution module is used to perform the transmission task according to the transmission priority and the adjusted transmission rate.

[0061] Optional, combined Figure 5 As shown, the adaptive transmission adjustment module includes a transmission environment data acquisition submodule and a transmission rate calculation submodule; the transmission environment data acquisition submodule is used to obtain transmission environment data from a transmission environment monitoring device; the transmission rate calculation submodule is used to calculate the transmission rate for all final encoded data in the transmission task based on the transmission environment data.

[0062] Specifically, when the transmission rate calculation submodule calculates the transmission rate for all final encoded data in the transmission task, the following formula is satisfied:

[0063]

[0064] Among them, R represents the transmission rate of the picture in the final coded data form; b represents the bandwidth in the transmission environment data; S represents the signal power in the transmission environment data, that is, the signal energy of the signal sent by the transmitter; M represents the noise power in the transmission environment data. The transmission rate unit is bits per second, the bandwidth unit is hertz, the signal power unit is watts, and the noise power unit is also watts.

[0065] Optional, combined Figure 6 As shown, the hierarchical transmission scheduling module includes a transmission rate reading submodule, a transmission weight calculation submodule and a transmission priority calculation submodule; the transmission rate reading submodule is used to read the transmission rate of each final encoded data in the transmission task; the transmission weight calculation submodule is used to calculate the transmission weight according to the data type of the final encoded data in the transmission task and the data generation time; the transmission priority calculation submodule is used to calculate the corresponding transmission priority according to the transmission rate and transmission weight of the final encoded data.

[0066] Specifically, when the transmission priority calculation submodule is working, the following formula is satisfied:

[0067]

[0068] Among them, P iW represents the transmission priority of the final coded data of the i-th image in all the final coded data of the transmission task; i represents the transmission weight score of the final coded data of the i-th image in all the final coded data of the transmission task; I represents the total number of all the final coded data of the transmission task; R i represents the transmission rate of the final coded data of the i-th image in all the final coded data of the transmission task; w i Indicates the weighted reference score assigned by the drone. The allocation rule may be, but is not limited to, according to the image capacity. For example, when the image capacity is less than 1Mb, the weighted reference score is 0.08. When the image capacity is greater than or equal to 1Mb and less than 3Mb, the weighted reference score is 0.1. When the image capacity is greater than or equal to 3Mb and less than 10Mb, the weighted reference score is 0.2. When the image capacity is greater than or equal to 10Mb, the weighted reference score is 0.3. kind indicates the key image classification value determined by the drone. The judgment rule may be, but is not limited to, according to whether the object in the image contains the object required by the inspection task. For example, if the drone determines that the image contains the object required by the inspection task, then kind is 3. If the drone determines that the image contains the object required by the inspection task, then kind is 1. If the drone cannot determine whether the image contains the object required by the inspection task, then kind is 2. Y indicates the resolution of the original image corresponding to the final encoded data. Before executing the corresponding transmission task, the transmission priority of all the final encoded data related to the transmission task is calculated first, and then the transmission is carried out in descending order of transmission priority. It should be noted that when the transmission priority is the same, the images with the same transmission priority are sorted and transmitted in descending order according to the generation time of the original image.

[0069] In summary, the setting of the above system improves the system's efficiency in retrieving drone image data by managing the storage, deletion and calling behaviors of image data during drone inspections, optimizes the system's processing of image data by preprocessing, multi-level compression and final encoding of stored image data to generate final compressed data, and optimizes the transmission process by transmitting the final compressed data according to the requirements of the transmission task; preprocessing, multi-level compression and encoding conversion of image data are beneficial to improving the system's compression effect and efficiency of image data, and are beneficial to shortening the transmission time; the quality and efficiency of primary compression are improved by dividing the image into equal parts and then performing primary compression, and then the primary compressed data of the image is further decomposed into multi-resolution and multi-frequency domains. , further improving the system's compression effect on image data, which is conducive to further shortening the transmission time; by counting the occurrence frequency of each pixel value in the image in the multi-level compressed data, constructing the Huffman tree, assigning the Huffman code and converting the pixel value of the image into the corresponding Huffman code that has been assigned to generate the final encoded data, it is conducive to improving the encoding quality and efficiency, and improving the encoding quality and efficiency of the final encoded data; adaptively adjusting the transmission rate through real-time changes in the transmission environment and transmitting sequentially according to the transmission priority, which is conducive to improving the transmission quality and shortening the transmission time; calculating the corresponding transmission priority through the transmission rate and transmission weight of the final encoded data is conducive to improving the accuracy and confirmation efficiency of the transmission priority, thereby helping to improve the quality and efficiency of UAV image data transmission.

[0070] A method for efficiently compressing and quickly transmitting drone image data, applied to a system for efficiently compressing and quickly transmitting drone image data as described above, combined with Figure 7 As shown, the method for efficient compression and rapid transmission of drone image data includes:

[0071] S1, manages the storage, deletion and call of image data during drone inspection;

[0072] S2, preprocessing, multi-level compression and final encoding of the stored image data to generate final compressed data;

[0073] S3, receives and executes the transmission task;

[0074] S4, transmitting the final compressed data according to the requirements of the transmission task.

[0075] Embodiment 2: This embodiment includes all the contents of Embodiment 1, and provides a system for efficiently compressing and rapidly transmitting drone image data. Figure 8As shown, the final encoding module also includes a compression effect evaluation submodule; the compression effect evaluation submodule is used to evaluate the compression effect according to the final encoded data; the compression effect evaluation submodule includes a compression ratio calculation unit, a compression efficiency calculation unit and a compression effect evaluation unit; the compression ratio calculation unit is used to perform ratio calculation according to the data size before and after compression of the image data, and generate the compression ratio of the image data; the compression efficiency calculation unit is used to calculate the compression efficiency according to the total encoding length and the total number of pixels in the final encoded data of the image data; the compression effect evaluation unit is used to evaluate the compression effect according to the compression ratio and the compression efficiency, and output the evaluation result information.

[0076] When the compression efficiency calculation unit is working, the following formula is satisfied:

[0077]

[0078] Among them, L total Indicates the total encoding length when the corresponding image data is compressed into the final encoded data; g(o i ) represents the occurrence frequency of the i-th symbol in the corresponding final coded data; l(o i ) represents the encoding length of the i-th symbol in the corresponding final encoded data; n represents the total number of symbols in the corresponding final encoded data; L average Indicates the average code length, i.e., compression efficiency;

[0079] When the compression ratio calculation unit is working, the following formula is satisfied:

[0080]

[0081] Compressed Size = L total ;

[0082] Among them, R Z Indicates the compression ratio of the corresponding image data; Original Size indicates the data size of the image data in the original image form; Compressed Size indicates the data size of the image data in the final encoded data form;

[0083] When L average ≥J 1 When or when R Z ≤J 2 When L average <J 1 When R Z >J 2 When the compression effect evaluation unit outputs evaluation result information indicating that the target is met; 1 and J 2They represent the reference value of compression efficiency and the reference value of compression ratio, respectively, and are set and adjusted by the administrator based on experience. When the evaluation result information indicates that the standard is not met, the administrator can take the following measures to improve the compression quality, but is not limited to: improve the compression ratio, optimize through more efficient parameters; perform multi-level compression on the image to further reduce the amount of data; perform area selection compression, perform low compression rate processing on important image areas, and perform high compression rate processing on unimportant areas.

[0084] To sum up, the compression effect evaluation submodule includes the settings of the compression ratio calculation unit, the compression efficiency calculation unit and the compression effect evaluation unit, which cooperate with the compression efficiency calculation algorithm and the compression ratio calculation algorithm. The compression efficiency is calculated by the total coding length and the total number of pixels in the final encoded data of the image data, and the compression ratio of the image data is generated by calculating the ratio of the data size before and after the image data is compressed. This is beneficial to improving the calculation efficiency of the compression efficiency and the compression ratio, and then improving the quality and efficiency of the compression effect evaluation, which is beneficial to improving the quality and efficiency of the UAV image data transmission.

[0085] The contents disclosed above are only preferred feasible embodiments of the present invention, and do not limit the protection scope of the present invention. Therefore, all equivalent technical changes made using the contents of the present invention description and drawings are included in the protection scope of the present invention. In addition, the elements therein can be updated as technology develops.

Claims

1. A system for efficiently compressing and rapidly transmitting drone image data, characterized in that: It includes a UAV image data management terminal, a data compression terminal, a fast transmission terminal and a transmission task management terminal; the UAV image data management terminal is used to manage the storage, deletion and call behavior of image data during the UAV inspection process; the data compression terminal is used to pre-process, multi-level compress and finally encode the stored image data to generate the final compressed data; The fast transmission terminal is used to transmit the final compressed data according to the requirements of the transmission task; the transmission task management terminal is used to receive and execute the transmission task; The data compression terminal includes an image preprocessing module, a multi-stage compression module and a final encoding module; the image preprocessing module is used to perform noise reduction and smoothing processing on the stored image data; The multi-level compression module is used to perform multi-level compression on the pre-processed image data to generate multi-level compressed data; The final encoding module is used to perform encoding conversion operations on multi-level compressed data to generate final encoded data.

2. The system for efficiently compressing and rapidly transmitting drone image data according to claim 1, characterized in that: The multi-stage compression module includes a primary compression submodule and a secondary compression submodule; The primary compression submodule is used to perform primary compression on the pre-processed image data, convert the image into the frequency domain to retain the low-frequency components, and quantize the image to generate primary compressed data; The secondary compression submodule is used to perform secondary compression on the primary compressed data, further decompose the image, retain important features and generate multi-level compressed data.

3. The system for efficiently compressing and rapidly transmitting drone image data as claimed in claim 2, characterized in that: The final coding module includes a pixel value occurrence frequency statistics submodule, a Huffman tree construction submodule, a Huffman code allocation submodule and a coding conversion submodule; the pixel value occurrence frequency statistics submodule is used to count the occurrence frequency of each pixel value in the image in the multi-level compressed data; the Huffman tree construction submodule is used to construct a Huffman tree according to the pixel value occurrence frequency; the Huffman code allocation submodule is used to allocate Huffman code to each pixel value in the image according to the Huffman tree; The encoding conversion submodule is used to convert the pixel values ​​of the image into the corresponding Huffman codes that have been allocated to generate final encoding data.

4. The system for efficiently compressing and rapidly transmitting drone image data as claimed in claim 3, characterized in that: The fast transmission terminal includes an adaptive transmission adjustment module, a hierarchical transmission scheduling module and a transmission execution module; the adaptive transmission adjustment module is used to adaptively adjust the transmission rate according to the real-time changes of the transmission environment; the hierarchical transmission scheduling module is used to determine the transmission priority for the image in the final coded data form; The transmission execution module is used to execute the transmission task according to the transmission priority and the adjusted transmission rate.

5. The system for efficiently compressing and rapidly transmitting drone image data as claimed in claim 4, characterized in that: The adaptive transmission adjustment module includes a transmission environment data acquisition submodule and a transmission rate calculation submodule; the transmission environment data acquisition submodule is used to acquire transmission environment data from a transmission environment monitoring device; the transmission rate calculation submodule is used to calculate the transmission rate for all final encoded data in the transmission task based on the transmission environment data.

6. The system for efficient compression and rapid transmission of drone image data as claimed in claim 5, characterized in that: The hierarchical transmission scheduling module includes a transmission rate reading submodule, a transmission weight calculation submodule and a transmission priority calculation submodule; the transmission rate reading submodule is used to read the transmission rate of each final encoded data in the transmission task; The transmission weight calculation submodule is used to calculate the transmission weight according to the data type of the final encoded data in the transmission task and the data generation time; The transmission priority calculation submodule is used to calculate the corresponding transmission priority according to the transmission rate and transmission weight of the final encoded data.

7. A method for efficiently compressing and quickly transmitting drone image data, applied to a system for efficiently compressing and quickly transmitting drone image data as claimed in claim 6, characterized in that: The method for efficiently compressing and quickly transmitting drone image data includes: S1, manages the storage, deletion and call of image data during drone inspection; S2, preprocessing, multi-level compression and final encoding of the stored image data to generate final compressed data; S3, receives and executes the transmission task; S4, transmitting the final compressed data according to the requirements of the transmission task.

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