A Progressive Image Compression and Transmission Method, Device, Medium and Product

Abstract

A progressive image compression transmission method, device, medium and product relate to the field of image processing. By adopting the present application, the progressive image compression transmission device performs multi-level compression on the original image and sub-packets the compressed original image, thereby reducing the amount of data for image transmission, ensuring image quality and enabling large-size images to be efficiently transmitted through the bandwidth-limited Beidou short message channel.

Description

Technical Field

[0001] This application relates to the field of image processing, and particularly to a progressive image compression and transmission method, apparatus, medium and product. Background Art

[0002] With the rapid development of Internet of Things technology, the demand for data transmission in remote areas or field environments is increasing day by day. Especially in scenarios such as geological exploration, field scientific research, and emergency rescue, it is necessary to transmit the image data collected on site to the command center in a timely manner for analysis and decision-making. As a global satellite navigation system independently developed by China, the Beidou-3 satellite navigation system's short message communication function provides an important communication means for data transmission in remote areas or field environments.

[0003] Currently, when using Beidou short messages to transmit image data, a direct compression and transmission method is usually adopted, that is, first compress the original image, and then send the compressed original image through the Beidou short message channel. This method can achieve the basic image transmission function and has been applied in some simple application scenarios.

[0004] However, in practical applications, due to the bandwidth limitation and large transmission delay of the Beidou short message channel, the direct compression and transmission method often results in low image transmission efficiency. Especially when transmitting large-size images, even after compression, the amount of data transmitted at one time is still large, which is likely to cause communication congestion. Summary of the Invention

[0005] This application provides a progressive image compression and transmission method, apparatus, medium and product for improving image transmission efficiency.

[0006] In a first aspect, this application provides a progressive image compression and transmission method, which is applied to a progressive image compression and transmission apparatus. The method includes: converting the width value and height value of the original image into width and height data, and the storage data amount of the width and height data is a preset first byte; performing JPEG quality compression on the original image to obtain a first compressed image; determining whether the storage data amount of the first compressed image is greater than a preset second byte; if so, performing image size compression and JPEG quality adjustment on the first compressed image to obtain a second compressed image, and the storage data amount of the second compressed image is less than that of the first compressed image; performing JXL compression on the second compressed image to obtain a third compressed image, and the storage data amount of the third compressed image is a preset third byte, and the preset third byte is less than the preset second byte; dividing the third compressed image into packets according to a preset fourth byte to obtain a plurality of image data packets, and the preset fourth byte is less than the preset third byte; encapsulating the width and height data, the image data packets and JSON other information to obtain a packet to be transmitted; sending the packet to be transmitted through the Beidou-3 short message channel.

[0007] By adopting the above technical scheme, the progressive image compression and transmission device performs multi-level compression on the original image and packets the compressed original image, thereby reducing the amount of data for image transmission, ensuring the image quality and enabling large-size images to be efficiently transmitted through the bandwidth-limited Beidou short message channel.

[0008] In combination with some embodiments of the first aspect, in some embodiments, JPEG quality compression is performed on the original image to obtain a first compressed image, which specifically includes: taking the JPEG compression quality parameter as a loop variable, looping the following steps until the JPEG compression quality parameter is equal to the minimum JPEG compression quality parameter or the storage data amount of the compressed image is less than a preset second byte, then determining the compressed image as the first compressed image; performing JPEG quality compression on the original image with the JPEG compression quality parameter to obtain a compressed image; gradually reducing the JPEG compression quality parameter according to a preset rule, and determining the adjusted JPEG compression quality parameter as the JPEG compression quality parameter.

[0009] By adopting the above technical solution, the progressive image compression transmission device uses the JPEG compression quality parameter as a loop variable, and gradually reduces the compression quality while ensuring the image quality, until the JPEG compression quality parameter is equal to the minimum JPEG compression quality parameter or the storage data volume of the compressed image is less than the preset second byte. This adaptive compression parameter adjustment method can retain image detail information to the greatest extent while meeting the data volume requirements. Compared with fixed compression parameters, it can better balance the compression rate and image quality, avoid image distortion caused by over-compression, and avoid excessive data volume caused by insufficient compression.

[0010] In combination with some embodiments of the first aspect, in some embodiments, image size compression and JPEG quality adjustment are performed on the first compressed image to obtain a second compressed image, which specifically includes: taking the number of image size compression times as a loop variable, looping the following steps until the number of image size compression times is equal to a preset number or the amount of storage data of the compressed sub-image is less than a preset second byte, then determining the compressed sub-image as the second compressed image; performing image size compression on the first image to obtain a compressed parent image, and recording the number of image size compression times; performing JPEG compression on the compressed parent image with a fixed JPEG compression quality parameter to obtain a compressed sub-image.

[0011] By adopting the above technical solution, the progressive image compression and transmission device adopts a dual compression mechanism in terms of image size compression and JPEG quality adjustment. That is, first, the progressive image compression and transmission device performs image size compression on the first compressed image to obtain a compressed parent image. Then, the progressive image compression and transmission device performs secondary compression on the compressed parent image by fixing the JPEG compression quality parameter to obtain a compressed sub-image. This process will be carried out cyclically until the number of times of image size compression is equal to the preset number or the stored data volume of the compressed sub-image is less than the preset second byte. This progressive compression method can significantly reduce the data volume while maintaining the main content of the image. Compared with pure quality compression, combining size compression can more effectively reduce the image data volume, and the compression effect is more controllable and stable.

[0012] Combined with some embodiments of the first aspect, in some embodiments, JXL compression is performed on the second compressed image to obtain a third compressed image, which specifically includes: dividing the second compressed image into multiple super-blocks of the same preset first size; performing discrete cosine transform on each super-block to obtain the frequency domain coefficients corresponding to each super-block respectively, and the frequency domain coefficients are used to represent the clarity contribution value; sorting the frequency domain coefficients to obtain a frequency domain coefficient list; retaining a preset number of target frequency domain coefficients with the largest values in the frequency domain coefficient list, and constructing a low-frequency frequency domain coefficient matrix of a preset second size based on the target frequency domain coefficients, and the preset second size is smaller than the preset first size; performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain a third compressed image.

[0013] By adopting the above technical solution, first, the progressive image compression and transmission device divides the second compressed image into super-blocks of the same size, and converts the spatial domain information into frequency domain coefficients through discrete cosine transform. These frequency domain coefficients reflect the clarity contribution value of each super-block to the image. Then, the progressive image compression and transmission device sorts the frequency domain coefficients, retains a preset number of target frequency domain coefficients with the largest values in the frequency domain coefficient list to construct a low-frequency frequency domain coefficient matrix. Finally, the progressive image compression and transmission device performs entropy coding compression processing on the low-frequency frequency domain coefficient matrix. This method makes full use of the characteristic that the human eye is insensitive to high-frequency information, effectively removes redundant information through frequency domain screening. Compared with traditional compression methods, it not only maintains the main visual features of the image, but also significantly reduces the data volume. Especially when dealing with complex textures and details, it can better balance the compression ratio and image quality.

[0014] In some embodiments in combination with some embodiments of the first aspect, before the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image, the method further includes: extracting features from historical image samples to obtain historical image feature vectors; using the historical image feature vectors as inputs and the corresponding historical edge detail data as outputs to train a predictor model; determining the difference between adjacent target frequency domain coefficients in the low-frequency frequency domain coefficient matrix as the DC residual; performing extended prediction on the DC residual through the predictor model to obtain edge detail data; and fusing the edge detail data with the low-frequency frequency domain coefficient matrix to obtain an enhanced low-frequency frequency domain coefficient matrix.

[0015] By adopting the above technical solution, the progressive image compression and transmission device introduces an edge detail enhancement technology based on machine learning, that is, by extracting features and training from historical image samples, a predictor model is established to predict edge detail information. During the compression process, the progressive image compression and transmission device analyzes the difference (DC residual) between adjacent target frequency domain coefficients in the low-frequency frequency domain coefficient matrix, uses the predictor model for detail expansion, and fuses the predicted edge detail data with the original low-frequency frequency domain coefficient matrix. This method not only improves the visual quality of the compressed image but also better preserves the edge and texture information of the image at a low bit rate. Compared with traditional compression methods, it can obtain higher subjective quality at the same compression ratio and is particularly suitable for application scenarios that require preserving edge details.

[0016] In some embodiments in combination with some embodiments of the first aspect, after the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image, the method further includes: calculating the compression ratio of the third compressed image relative to the second compressed image; if the compression ratio is lower than a preset compression ratio threshold, adjusting the preset first size according to the image features of the second compressed image; and re-executing the step of dividing the second compressed image into multiple superblocks of the same preset first size to the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image.

[0017] By adopting the above technical solution, the progressive image compression and transmission device dynamically adjusts the size parameter of the superblock by calculating the compression ratio before and after compression and comparing it with the preset compression ratio threshold. When the compression effect is not ideal, the progressive image compression and transmission device automatically adjusts the size parameter of the superblock according to the image features and re-performs the compression process. This feedback optimization mechanism ensures the stability and reliability of the compression effect. Compared with the compression method with fixed parameters, it can better adapt to the characteristics of different types of images and avoid the problem of poor compression effect caused by improper compression parameters.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of sending the data packet to be transmitted through the Beidou-3 short message channel, the method further includes: the receiving end extracts the width and height data from the data packet to be transmitted; the receiving end establishes an image reconstruction buffer area with a preset size according to the width and height data; the receiving end sequentially writes the image data in the data packet to be transmitted into the corresponding positions of the image reconstruction buffer area in the receiving order; the receiving end determines whether the image data in the image reconstruction buffer area meets the preset integrity requirement; if so, the receiving end performs a decompression operation on the image data in the image reconstruction buffer area to obtain the final reconstructed image.

[0019] By adopting the above technical solution, the receiving end establishes an image reconstruction buffer area with a preset size according to the width and height data, and then sequentially writes the image data in the data packet to be transmitted into the corresponding positions of the image reconstruction buffer area in the receiving order. The receiving end judges the data integrity to ensure that all necessary information has been received, and finally performs decompression and reconstruction. This mechanism not only supports progressive display, but also can effectively handle the situation of data packet loss or delay. Compared with the traditional one-time receiving and reconstruction method, it has better fault tolerance and user experience. Even in the case of unstable network conditions, it can ensure the reliable transmission and reconstruction of images, and is particularly suitable for communication environments with limited bandwidth.

[0020] In a second aspect, an embodiment of the present application provides a progressive image compression and transmission device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, and the computer program code includes computer instructions. The one or more processors call the computer instructions to cause the progressive image compression and transmission device to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product containing instructions. When the computer program product runs on the progressive image compression and transmission device, it causes the progressive image compression and transmission device to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, including instructions. When the instructions run on the progressive image compression and transmission device, it causes the progressive image compression and transmission device to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0023] It can be understood that the progressive image compression transmission device 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:

[0025] 1. By adopting the above technical solution, the progressive image compression and transmission device performs multi-level compression on the original image and sub-packets the compressed original image, thereby reducing the amount of data for image transmission, ensuring the image quality and enabling large-size images to be efficiently transmitted through the Beidou short message channel with limited bandwidth.

[0026] 2. By adopting the above technical solution, the progressive image compression transmission device uses the JPEG compression quality parameter as a loop variable, and gradually reduces the compression quality while ensuring the image quality, until the JPEG compression quality parameter is equal to the minimum JPEG compression quality parameter or the storage data volume of the compressed image is less than the preset second byte. This adaptive compression parameter adjustment method can retain image detail information to the greatest extent while meeting the data volume requirements. Compared with fixed compression parameters, it can better balance the compression rate and image quality, avoid image distortion caused by over-compression, and avoid excessive data volume caused by insufficient compression.

[0027] 3. By adopting the above technical solution, first, the progressive image compression and transmission device divides the second compressed image into super blocks of the same size, and converts the spatial domain information into frequency domain coefficients through discrete cosine transform. These frequency domain coefficients reflect the contribution value of each super block to the clarity of the image. Then, the progressive image compression and transmission device sorts the frequency domain coefficients, retains the preset number of target frequency domain coefficients with the largest values ​​in the frequency domain coefficient list to construct a low-frequency frequency domain coefficient matrix. Finally, the progressive image compression and transmission device performs entropy coding compression processing on the low-frequency frequency domain coefficient matrix. This method makes full use of the fact that the human eye is insensitive to high-frequency information, and effectively removes redundant information through frequency domain screening. Compared with traditional compression methods, it not only maintains the main visual features of the image, but also significantly reduces the amount of data. Especially when processing complex textures and details, it can better balance the compression rate and image quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flowchart of a progressive image compression transmission method in an embodiment of the present application;

[0029] Figure 2 is another flowchart of the progressive image compression transmission method in an embodiment of the present application;

[0030] Figure 3 It is a schematic structural diagram of an entity device of the progressive image compression and transmission device in the embodiments of the present application. Specific embodiments

[0031] 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 limit the present application. As used in the specification of the present application, the singular forms "a", "an", "the above", "the", and "this" are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0033] The following is a process description of the method provided in this embodiment. Please refer to Figure 1 , which is a schematic flowchart of a process of the progressive image compression and transmission method in the embodiments of the present application.

[0034] S101. Convert the width value and height value of the original image into width and height data, and the storage data volume of the width and height data is a preset first byte;

[0035] Wherein, the original image refers to an initial image file that has not undergone any compression processing, such as a photo taken by a camera, a scanned picture, etc.; the width value refers to the number of pixel points of the original image in the horizontal direction; the height value refers to the number of pixel points of the original image in the vertical direction; the width and height data refers to binary data organized by the width value and height value in a specific format; the preset first byte refers to a fixed number of bytes determined in advance for storing the width and height data, usually 4 bytes.

[0036] When the progressive image compression and transmission device receives the original image to be transmitted, it needs to extract and save the size information of the original image for subsequent reconstruction. Specifically, first, the progressive image compression and transmission device reads the metadata of the original image to obtain the width value and height value of the original image; then, the progressive image compression and transmission device converts these two decimal values into binary format; next, the progressive image compression and transmission device organizes the binary data into a fixed-length byte sequence with the high bits first and the low bits last; finally, the progressive image compression and transmission device stores this byte sequence as width and height data in a storage space with a preset first-byte size.

[0037] S102. Perform JPEG quality compression on the original image to obtain a first compressed image;

[0038] Among them, JPEG quality compression refers to using the lossy compression algorithm in the JPEG standard to compress the original image; the first compressed image is an image file obtained by JPEG-compressing the original image.

[0039] After the extraction and conversion of the image size information are completed, the progressive image compression and transmission device needs to perform preliminary compression on the original image to reduce the data volume. Specifically, first, the progressive image compression and transmission device sets an initial JPEG compression quality parameter. This JPEG compression quality parameter usually selects a relatively high value (such as 50) to ensure image quality. The JPEG compression quality parameter refers to the parameter value that controls the compression degree and is usually an integer from 0 to 100. Then, the progressive image compression and transmission device determines whether the storage data volume of the compressed original image is less than a preset second byte. The storage data volume refers to the number of bytes occupied by the compressed original image. If it is less, it means that the storage data volume of the compressed original image obtained by performing JPEG quality compression on the original image with the initial JPEG compression quality parameter meets the compression requirements, and the progressive image compression and transmission device can output the first compressed image; if it is greater, it means that the storage data volume of the compressed original image obtained by performing JPEG quality compression on the original image with the initial JPEG compression quality parameter does not meet the compression requirements, and the progressive image compression and transmission device needs to further compress. Next, the progressive image compression and transmission device sets a lower JPEG compression quality parameter (such as 40) to compress the original image and determines whether the storage data volume of the compressed original image is less than the preset second byte. And so on, until the JPEG compression quality parameter reaches the lowest JPEG compression quality parameter (such as 30) or the storage data volume of the compressed original image is less than the preset second byte. At this time, the progressive image compression and transmission device outputs the first compressed image.

[0040] Optionally, generally, JPEG quality compression is performed on the original image, and obtaining the first compressed image can be achieved in the following manner, which is not limited herein: Using the JPEG compression quality parameter as a loop variable, perform loop operations on the following steps until the JPEG compression quality parameter is equal to the lowest JPEG compression quality parameter or the stored data volume of the compressed image is less than the preset second byte, then determine the compressed image as the first compressed image; perform JPEG quality compression on the original image with the JPEG compression quality parameter to obtain a compressed image; gradually decrease the JPEG compression quality parameter according to a preset rule, and determine the adjusted JPEG compression quality parameter as the JPEG compression quality parameter.

[0041] The following lists two specific examples to illustrate the loop process of JPEG quality compression:

[0042] Example 1, assuming the initial conditions:

[0043] Size of the original image: 2MB (2048KB);

[0044] Initial JPEG compression quality parameter: 95;

[0045] Lowest JPEG compression quality parameter: 60;

[0046] Preset second byte (target size): 500KB;

[0047] Preset rule: Each time the JPEG compression quality parameter is decreased by 5;

[0048] Example of the loop process:

[0049] The 1st loop:

[0050] JPEG compression quality parameter = 95;

[0051] Size of the compressed image = 1200KB;

[0052] 1200KB > 500KB, continue the loop;

[0053] New JPEG compression quality parameter = 95 - 5 = 90;

[0054] The 2nd loop:

[0055] JPEG compression quality parameter = 90;

[0056] Size of the compressed image = 900KB;

[0057] 900KB > 500KB, continue the loop;

[0058] New JPEG compression quality parameter = 90 - 5 = 85;

[0059] The 3rd loop:

[0060] JPEG compression quality parameter = 85;

[0061] Size of the compressed image = 700KB;

[0062] 700KB > 500KB, continue the loop;

[0063] New JPEG compression quality parameter = 85 - 5 = 80;

[0064] The 4th loop:

[0065] JPEG compression quality parameter = 80;

[0066] Size of the compressed image = 480KB;

[0067] 480KB < 500KB, end the loop;

[0068] Final result: The size of the first compressed image is 480KB, the JPEG compression quality parameter used is 80, the compression rate reaches approximately 76.6%, and the image quality remains within an acceptable range.

[0069] Example 2, assume the initial conditions:

[0070] Size of the original image: 5MB (5120KB);

[0071] Initial JPEG compression quality parameter: 95;

[0072] Lowest JPEG compression quality parameter: 60;

[0073] Preset second byte (target size): 400KB;

[0074] Preset rule: Each time the JPEG compression quality parameter is reduced by 5;

[0075] Example of the loop process:

[0076] The 1st loop:

[0077] JPEG compression quality parameter = 95;

[0078] Size of the compressed image = 2800KB;

[0079] 2800KB > 400KB, continue the loop;

[0080] New JPEG compression quality parameter = 95 - 5 = 90;

[0081] The 2nd loop:

[0082] JPEG compression quality parameter = 90;

[0083] Compressed image size = 2100KB;

[0084] 2100KB > 400KB, continue the loop;

[0085] New JPEG compression quality parameter = 90 - 5 = 85;

[0086] …… (the middle loop is omitted) ……

[0087] The 7th loop:

[0088] JPEG compression quality parameter = 65;

[0089] Compressed image size = 850KB;

[0090] 850KB > 400KB, continue the loop;

[0091] New JPEG compression quality parameter = 65 - 5 = 60;

[0092] The 8th loop:

[0093] JPEG compression quality parameter = 60 (has reached the minimum limit);

[0094] Compressed image size = 750KB;

[0095] 750KB > 400KB, but the JPEG compression quality parameter has reached the minimum JPEG compression quality parameter, the loop ends;

[0096] Final result: The size of the first compressed image is 750KB, and the JPEG compression quality parameter used is 60. Although the JPEG compression quality parameter has reached the minimum JPEG compression quality parameter, the stored data volume of the first compressed image still exceeds the preset second byte. At this time, it is necessary to enter the next step of image size compression and JPEG quality adjustment.

[0097] S103. Determine whether the stored data volume of the first compressed image is greater than the preset second byte;

[0098] Among them, the preset second byte refers to the threshold of the maximum allowable image storage data volume for JPEG quality compression determined in advance, usually determined based on the bandwidth limit of the transmission channel; the stored data volume refers to the number of bytes actually occupied by the first compressed image.

[0099] After obtaining the first compressed image, the progressive image compression and transmission device needs to evaluate whether it meets the transmission requirements. Specifically, the progressive image compression and transmission device obtains the stored data volume of the first compressed image and compares this stored data volume with the preset second byte to determine whether the stored data volume of the first compressed image is greater than the preset second byte.

[0100] S104. If so, perform image size compression and JPEG quality adjustment on the first compressed image to obtain a second compressed image, and the storage data volume of the second compressed image is smaller than that of the first compressed image.

[0101] Among them, image size compression refers to the operation of reducing the data volume by lowering the image resolution; JPEG quality adjustment refers to the process of recompressing by resetting JPEG compression parameters; the second compressed image refers to the image file obtained after image size compression and JPRG quality adjustment.

[0102] When the storage data volume of the first compressed image exceeds the preset second byte, the progressive image compression and transmission device needs to perform deeper compression. Specifically, first, the progressive image compression and transmission device performs image size compression on the first compressed image. For example, each time it is reduced to 0.9 times of the previous one, and the maximum number of times of image size compression is 5 times. After each reduction, the progressive image compression and transmission device uses a fixed JPEG compression quality parameter (such as 50) to perform JPEG quality compression on the first compressed image after image size compression, and determines whether the storage data volume of the first compressed image after image size compression and JPEG quality adjustment is smaller than the preset second byte. And so on, until the number of times of image size compression reaches 5 times or the storage data volume of the first compressed image after image size compression and JPEG quality adjustment is smaller than the preset second byte. At this time, the progressive image compression and transmission device outputs the second compressed image.

[0103] Optionally, generally, performing image size compression and JPEG quality adjustment on the first compressed image to obtain a second compressed image can be achieved in the following way, which is not limited here: using the number of times of image size compression as a loop variable, performing loop operations on the following steps until the number of times of image size compression is equal to the preset number or the storage data volume of the compressed sub-image is smaller than the preset second byte, then determining the compressed sub-image as the second compressed image; performing image size compression on the first image to obtain a compressed parent image, and recording the number of times of image size compression; performing JPEG compression on the compressed parent image with a fixed JPEG compression quality parameter to obtain a compressed sub-image.

[0104] The following lists a loop example of image size compression and JPEG quality adjustment.

[0105] Assume the initial conditions:

[0106] Size of the first compressed image: 750 KB;

[0107] Size of the first compressed image: 2400×1800 pixels;

[0108] Preset second byte (target size): 400 KB;

[0109] Fix the JPEG compression quality parameter: 75;

[0110] Preset the number of compression times: 3;

[0111] The size compression ratio each time: Reduce by 50%;

[0112] Example of the loop process:

[0113] The 1st loop:

[0114] The current number of image size compression times = 1;

[0115] The size of the compressed parent image = 1200×900 pixels (both length and width are reduced by 50%);

[0116] The fixed JPEG compression quality parameter = 75;

[0117] The size of the compressed sub - image = 520KB;

[0118] 520KB > 400KB, continue the loop;

[0119] The 2nd loop:

[0120] The current number of image size compression times = 2;

[0121] The size of the compressed parent image = 600×450 pixels;

[0122] The fixed JPEG compression quality parameter = 75;

[0123] The size of the compressed sub - image = 380KB;

[0124] 380KB < 400KB, the loop ends;

[0125] Final result: The size of the second compressed image is 380KB, the final image size is 600×450 pixels, the actual number of times of using image size compression is 2 times (not reaching the preset number of compression times 3 times), the JPEG compression quality remains at 75, and the image size is successfully reduced below the target value through image size compression.

[0126] S105. Perform JXL compression on the second compressed image to obtain a third compressed image, and the stored data volume of the third compressed image is the preset third byte, and the preset third byte is less than the preset second byte;

[0127] Among them, JXL compression refers to the compression operation using the JPEG XL image compression standard, which is a new generation of image compression technology; the third compressed image refers to the image file obtained after JXL compression; the preset third byte refers to the predetermined target compression data volume, and the preset third byte needs to be less than the preset second byte to ensure further reduction of the data volume.

[0128] After the second compressed image is generated, the progressive image compression and transmission device needs to perform more efficient compression to further reduce the stored data volume. Specifically, first, the progressive image compression and transmission device divides the second compressed image into multiple superblocks according to a preset size. A superblock refers to a basic processing unit of a fixed size obtained by dividing the image. Then, the progressive image compression and transmission device performs DCT transformation on each superblock to obtain frequency domain coefficients representing different frequency components. The frequency domain coefficients represent the representation form of the image in the frequency domain. Next, the progressive image compression and transmission device sorts all the frequency domain coefficients according to their contribution degrees to the image clarity. The clarity contribution value refers to the influence degree of a certain frequency domain component on the visual quality of the image. After that, the progressive image compression and transmission device selects a certain number of frequency domain coefficients with the largest contribution degrees to construct a low-frequency coefficient matrix. Then, the progressive image compression and transmission device performs adaptive context modeling and entropy coding on the low-frequency coefficient matrix. Finally, the progressive image compression and transmission device generates a third compressed image with a size of the preset third byte. The whole process realizes efficient compression by removing high-frequency information that is insensitive to the human eye.

[0129] Optionally, generally, performing JXL compression on the second compressed image to obtain the third compressed image can be achieved in the following ways (not limited herein): dividing the second compressed image into multiple superblocks of the same preset first size; performing discrete cosine transformation on each superblock to obtain the frequency domain coefficients corresponding to each superblock respectively, and the frequency domain coefficients are used to represent the clarity contribution value; sorting the frequency domain coefficients to obtain a frequency domain coefficient list; retaining a preset number of target frequency domain coefficients with the largest values in the frequency domain coefficient list, and constructing a low-frequency frequency domain coefficient matrix of a preset second size based on the target frequency domain coefficients, and the preset second size is smaller than the preset first size; performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image.

[0130] The following lists a specific example of JXL compression:

[0131] Assume the initial conditions:

[0132] The size of the second compressed image: 600×450 pixels;

[0133] The preset first size (superblock size): 64×64 pixels;

[0134] Predetermined second dimension (size of low-frequency coefficient matrix in frequency domain): 32×32 pixels;

[0135] Predetermined number of reserved frequency domain coefficients: 512;

[0136] Example of compression process:

[0137] Divide super blocks:

[0138] In the horizontal direction of the image: 600÷64 = 9.375, rounded up to 10 blocks;

[0139] In the vertical direction of the image: 450÷64 = 7.031, rounded up to 8 blocks;

[0140] A total of 80 super blocks (10×8) are obtained;

[0141] Example of 2D-DCT transformation (taking a 64×64 super block as an example):

[0142] Input: Image data of 64×64 pixels;

[0143] Perform 2D-DCT transformation to obtain a frequency domain coefficient matrix of 64×64;

[0144] Assume the obtained partial frequency domain coefficient values (example):

[0145] DC component: 1024;

[0146] AC components: 512, 256, 128, 64, 32, 16, 8, 4, ……

[0147] Sorting of frequency domain coefficients (example values):

[0148] Sorted frequency domain coefficient list (in descending order):

[0149] 1024 (DC component);

[0150] 512 (main edge features);

[0151] 256 (secondary edge features);

[0152] 128 (detail features) … and so on;

[0153] Construct a low-frequency frequency domain coefficient matrix: Select the first 512 maximum values from the frequency domain coefficient list, rearrange these target frequency domain coefficients into a 32×32 low-frequency frequency domain coefficient matrix, and discard the remaining smaller frequency domain coefficients;

[0154] Entropy coding compression: Perform entropy coding on the 32×32 low-frequency frequency domain coefficient matrix. For example, assign shorter codes to frequently occurring frequency domain coefficient values and longer codes to rare frequency domain coefficient values, and use run-length coding to process consecutive zero values;

[0155] Final result:

[0156] Original superblock size: 64×64×8 bits = 32,768 bits;

[0157] Compressed size: approximately 8,192 bits (compression ratio 75%);

[0158] Overall image compression effect:

[0159] Second compressed image: 380 KB;

[0160] Third compressed image: estimated 95 KB;

[0161] Total compression ratio: 75%.

[0162] S106. Sub-packetize the third compressed image according to a preset fourth byte to obtain multiple image data packets, where the preset fourth byte is smaller than the preset third byte;

[0163] Among them, the preset fourth byte refers to the maximum allowable size of a single image data packet; the sub-packetizing operation refers to the process of dividing a larger data file into multiple smaller data packets; and the image data packet refers to the divided data unit.

[0164] After the third compressed image is generated, the progressive image compression and transmission device needs to divide it into image data packets suitable for transmission. Specifically, the progressive image compression and transmission device calculates the number of image data packets to be divided, which is equal to the size of the third compressed image divided by the preset fourth byte and rounded up. The progressive image compression and transmission device sub-packetizes the third compressed image according to the preset fourth byte and the number of image data packets to obtain multiple image data packets.

[0165] S107. Package the width and height data, image data packets, and other JSON information to obtain a data packet to be transmitted;

[0166] Among them, the width and height data refers to the size information of the original image obtained in step S101; the other JSON information refers to various metadata organized in JSON format, such as compression parameters, timestamps, etc.; packaging refers to organizing multiple types of data into a unified data structure according to a specific format; and the data packet to be transmitted refers to the complete data unit finally used for transmission.

[0167] When all components are ready, the progressive image compression transmission device needs to organize them into a standard format of data packets to be transmitted. Specifically, first, the progressive image compression transmission device constructs a protocol header, which contains information such as the data packet type and version number; then, the progressive image compression transmission device places the width and height data in a fixed position before the image data packet; then, the progressive image compression transmission device places the other JSON information in a fixed position after the image data packet; finally, the progressive image compression transmission device arranges the image data packets in a predetermined order.

[0168] S108. Send the data packet to be transmitted through the BeiDou-3 short message channel.

[0169] Among them, the Beidou-3 short message channel refers to the data transmission service provided by the Beidou-3 satellite navigation system; sending refers to the process of progressive image compression transmission device transmitting data through the Beidou-3 short message channel.

[0170] When the data packets to be transmitted are prepared, the progressive image compression transmission device needs to send data through the satellite channel. Specifically, first, the progressive image compression transmission device checks the availability status of the BeiDou-3 short message channel. Then, the progressive image compression transmission device sets the transmission parameters, such as transmission power, modulation mode, etc., according to the channel characteristics. Next, the progressive image compression transmission device sends the data packets to be transmitted to the satellite according to the preset transmission protocol. After that, the progressive image compression transmission device monitors the transmission process and records the transmission status. If a transmission error is detected, the retransmission mechanism is started. Finally, the progressive image compression transmission device confirms that all data packets to be transmitted have been successfully sent. This satellite-based transmission method provides long-distance, all-weather communication capabilities.

[0171] By adopting the above technical scheme, the progressive image compression and transmission device performs multi-level compression on the original image and packets the compressed original image, thereby reducing the amount of data for image transmission, ensuring the image quality and enabling large-size images to be efficiently transmitted through the bandwidth-limited Beidou short message channel.

[0172] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the progressive image compression transmission method in an embodiment of the present application.

[0173] S201, converting the width value and height value of the original image into width and height data, wherein the storage data amount of the width and height data is a preset first byte;

[0174] For details, please refer to step S101, which will not be described in detail here.

[0175] S202. Perform JPEG quality compression on the original image to obtain a first compressed image;

[0176] Specifically, refer to step S102, which will not be elaborated here.

[0177] S203. Determine whether the storage data volume of the first compressed image is greater than a preset second byte;

[0178] Specifically, refer to step S103, which will not be elaborated here.

[0179] S204. If so, perform image size compression and JPEG quality adjustment on the first compressed image to obtain a second compressed image, and the storage data volume of the second compressed image is less than that of the first compressed image;

[0180] Specifically, refer to step S104, which will not be elaborated here.

[0181] S205. Extract features from the historical image samples to obtain historical image feature vectors;

[0182] Among them, the historical image samples refer to a pre-collected representative image data set; feature extraction refers to extracting numerical descriptions that can characterize image characteristics from the historical image samples; image features include image attributes such as texture features, edge features, and color features; the historical image feature vectors refer to numerical sequences formed by organizing the extracted image features.

[0183] Specifically, first, the progressive image compression and transmission device loads the pre-prepared historical image samples from the database. Then, the progressive image compression and transmission device performs preprocessing on each historical image sample, including size unification and color space conversion. Next, the progressive image compression and transmission device uses various feature extraction operators, such as Gabor filters and HOG descriptors, to extract the texture features and edge features of the historical image samples. After that, the progressive image compression and transmission device normalizes the extracted image features. Finally, the progressive image compression and transmission device organizes the processed image features into historical image feature vectors with a fixed dimension.

[0184] S206. Use the historical image feature vectors as inputs and the corresponding historical edge detail data as outputs to train a predictor model;

[0185] Among them, the predictor model refers to a machine learning model used to predict image edge details; the historical edge detail data refers to the image edge information extracted from the historical image samples.

[0186] After the historical image feature vectors are prepared, the progressive image compression and transmission device needs to establish a mapping relationship from the image feature vectors to the edge detail data. Specifically, first, the progressive image compression and transmission device constructs a neural network structure suitable for edge prediction tasks, including an input layer, a hidden layer, and an output layer; then, the progressive image compression and transmission device divides the historical image feature vectors and the corresponding historical edge detail data into a training set and a validation set; next, the progressive image compression and transmission device sets training parameters, such as batch size, learning rate, etc.; after that, the progressive image compression and transmission device conducts multiple rounds of training, and updates the model parameters through the backpropagation algorithm in each round; finally, the progressive image compression and transmission device evaluates the model performance on the validation set, and adjusts the model structure or parameters if necessary to obtain a predictor model.

[0187] S207. Determine the difference between adjacent target frequency domain coefficients in the low-frequency frequency domain coefficient matrix as the DC residual;

[0188] Among them, the low-frequency frequency domain coefficient matrix refers to the transform domain data that retains the main frequency components; the target frequency domain coefficient refers to the important frequency domain coefficients retained after screening; the adjacent target frequency domain coefficients refer to the target frequency domain coefficients adjacent in position in the low-frequency frequency domain coefficient matrix; the DC residual refers to the difference value between adjacent target frequency domain coefficients.

[0189] When analyzing the frequency domain features, the progressive image compression and transmission device needs to calculate the relationship between the frequency domain coefficients. Specifically, the progressive image compression and transmission device first determines the spatial position relationship of the target frequency domain coefficients in the low-frequency frequency domain coefficient matrix, and then visits the adjacent target frequency domain coefficients in sequence according to a predetermined scanning order, such as zigzag scanning. Next, the progressive image compression and transmission device calculates the difference between each pair of adjacent target frequency domain coefficients, and then organizes these differences into a DC residual sequence. Finally, the progressive image compression and transmission device conducts statistical analysis on the DC residual sequence to determine the significance threshold.

[0190] S208. Perform extended prediction on the DC residual through the predictor model to obtain edge detail data;

[0191] Among them, extended prediction refers to the process of inferring complete edge details from limited residual information; edge detail data refers to the information describing the edge and detail structure of the image.

[0192] After obtaining the DC residuals, the progressive image compression and transmission device needs to use the trained predictor model to recover details. Specifically, first, the progressive image compression and transmission device converts the DC residuals into an input format acceptable to the predictor model; then, the progressive image compression and transmission device uses the predictor model to perform forward calculations on the input data; next, the progressive image compression and transmission device performs post-processing on the output of the predictor model, including scale recovery and range limitation; after that, the progressive image compression and transmission device evaluates the reliability of the prediction results and filters out high-confidence predictions; finally, the progressive image compression and transmission device organizes the prediction results into a standardized edge detail data format.

[0193] S209. Fuse the edge detail data with the low-frequency frequency domain coefficient matrix to obtain an enhanced low-frequency frequency domain coefficient matrix;

[0194] Among them, fusion refers to the process of reasonably combining two different types of data; the enhanced low-frequency frequency domain coefficient matrix refers to the improved version of the frequency domain data obtained after fusion.

[0195] After the prediction of the edge detail data is completed, the progressive image compression and transmission device needs to combine it with the original frequency domain information. Specifically, first, the progressive image compression and transmission device analyzes the correspondence between the edge detail data and the low-frequency frequency domain coefficient matrix; then, the progressive image compression and transmission device designs an adaptive fusion weight strategy, considering local image features and signal strength; next, the progressive image compression and transmission device gradually integrates the edge detail data into the low-frequency frequency domain coefficient matrix according to the set weights; after that, the progressive image compression and transmission device performs data consistency checks to ensure that the fusion does not introduce artifacts; finally, the progressive image compression and transmission device optimizes and adjusts the fusion result to obtain a low-frequency frequency domain coefficient matrix with enhanced detail performance. This fusion process supplements richer detail performance while maintaining the main low-frequency information.

[0196] S210. Perform JXL compression on the second compressed image to obtain a third compressed image, and the storage data volume of the third compressed image is a preset third byte, and the preset third byte is less than the preset second byte;

[0197] Specifically, refer to step S105, which will not be elaborated here.

[0198] S211. Calculate the compression ratio of the third compressed image relative to the second compressed image;

[0199] Among them, the compression ratio refers to the ratio of the change in the storage data volume before and after compression; calculating the compression ratio is generally obtained through division operations.

[0200] After the third compressed image is generated, the progressive image compression and transmission device needs to evaluate whether the compression effect meets the expectations. Specifically, first, the progressive image compression and transmission device obtains the file size information of the second compressed image and the third compressed image; then, the progressive image compression and transmission device uses the storage data volume of the second compressed image as the denominator and the storage data volume of the third compressed image as the numerator; next, the progressive image compression and transmission device performs a division operation to obtain the actual compression ratio of the third compressed image relative to the second compressed image.

[0201] S212. If the compression ratio is lower than the preset compression ratio threshold, adjust the preset first size according to the image features of the second compressed image;

[0202] Among them, the preset compression ratio threshold refers to the lowest compression effect; the image features refer to the characteristic values describing the image content and structure; the preset first size refers to the size parameter of the superblock.

[0203] When it is found that the compression effect is not ideal, the progressive image compression and transmission device needs to optimize the compression parameters. Specifically, first, the progressive image compression and transmission device analyzes the texture complexity, edge distribution and other features of the second compressed image; then, the progressive image compression and transmission device evaluates whether the size of the current superblock is appropriate according to these features; next, the progressive image compression and transmission device calculates new size parameters based on a predetermined adjustment strategy, with smaller sizes tending to be used in complex regions and larger sizes tending to be used in simple regions; after that, the progressive image compression and transmission device verifies the rationality of the new size parameters to ensure that they are within the effective range.

[0204] S213. Re-execute the steps of dividing the second compressed image into multiple superblocks of the same preset first size to the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image;

[0205] Among them, re-executing means repeating the step of performing JXL compression on the second compressed image to obtain the third compressed image using the new size parameters. Specifically, reference can be made to step S105, which will not be elaborated here.

[0206] S214. Sub-packetize the third compressed image according to the preset fourth byte to obtain multiple image data packets, and the preset fourth byte is smaller than the preset third byte;

[0207] Specifically, reference can be made to step S106, which will not be elaborated here.

[0208] S215. Package the width and height data, image data packets and other JSON information to obtain the data packet to be transmitted;

[0209] Specifically, reference can be made to step S107, which will not be elaborated here.

[0210] S216. Send the data packet to be transmitted through the short message channel of Beidou-3

[0211] Specifically, refer to step S108, which will not be elaborated here.

[0212] The progressive image compression and transmission device in the embodiment of the present invention application will be described from the perspective of hardware processing. Please refer to Figure 3 which is a schematic structural diagram of an entity device of the progressive image compression and transmission device in the embodiment of the present application.

[0213] It should be noted that Figure 3 the structure of the progressive image compression and transmission device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0214] As Figure 3 shown, the progressive image compression and transmission device includes a CPU 301, which can perform various appropriate actions and processes according to the program stored in the ROM 302 or the program loaded from the storage section 308 into the RAM 303, such as executing the method described in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. The I / O interface 305 is also connected to the bus 304.

[0215] 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), 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. The driver 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 driver 310 as needed so that the computer program read from it can be installed into the storage section 308 as needed.

[0216] 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 the network through the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the CPU 301, various functions defined in the present invention are executed.

[0217] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.

[0218] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings.

[0219] Specifically, the progressive image compression and transmission device of this embodiment includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the progressive image compression and transmission method provided in the above embodiment is implemented.

[0220] As another aspect, the present invention also provides a computer-readable storage medium, which may be included in the progressive image compression and transmission device described in the above embodiments; or may exist alone without being assembled into the progressive image compression and transmission device. The above storage medium carries one or more computer programs, and when the one or more computer programs are executed by a processor of the progressive image compression and transmission device, the progressive image compression and transmission device implements the progressive image compression and transmission method provided in the above embodiments.

[0221] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and 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.

[0222] As used in the above embodiments, according to the context, the term "when..." can be interpreted to mean "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, according to the context, the phrase "when determining..." or "if detecting (the stated condition or event)" can be interpreted to mean "if determining...", "in response to determining...", "when detecting (the stated condition or event)", or "in response to detecting (the stated condition or event)".

[0223] Those of ordinary skill in the art can understand all or part of the processes in the methods of the above embodiments. These processes can be completed by relevant hardware instructed by a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The foregoing storage medium includes various media that can store program codes, such as ROM or random access memory RAM, magnetic disks, or optical discs.

Claims

1. A progressive image compression transmission method, characterized in that: Applied to a progressive image compression transmission device, the method comprises: Convert the width and height of the original image into width and height data, wherein the storage data amount of the width and height data is a preset first byte; Performing JPEG quality compression on the original image to obtain a first compressed image; Determining whether the storage data amount of the first compressed image is greater than a preset second byte; If yes, performing image size compression and JPEG quality adjustment on the first compressed image to obtain a second compressed image, wherein the storage data volume of the second compressed image is smaller than the storage data volume of the first compressed image; Performing JXL compression on the second compressed image to obtain a third compressed image, wherein the storage data amount of the third compressed image is a preset third byte, and the preset third byte is smaller than the preset second byte; Packetizing the third compressed image according to a preset fourth byte to obtain a plurality of image data packets, wherein the preset fourth byte is smaller than the preset third byte; Encapsulate the width and height data, the image data packet and other JSON information to obtain a data packet to be transmitted; Send the data packet to be transmitted through the BeiDou-3 short message channel; The method of performing JXL compression on the second compressed image to obtain the third compressed image specifically includes: dividing the second compressed image into multiple super blocks of the same preset first size; performing discrete cosine transform on each of the super blocks to obtain frequency domain coefficients corresponding to each of the super blocks, wherein the frequency domain coefficients are used to represent clarity contribution values; sorting the frequency domain coefficients to obtain a frequency domain coefficient list; retaining a preset number of target frequency domain coefficients with the largest values ​​in the frequency domain coefficient list, and constructing a low-frequency frequency domain coefficient matrix of a preset second size based on the target frequency domain coefficients, wherein the preset second size is smaller than the preset first size; and performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image.

2. The method according to claim 1, characterized in that The performing JPEG quality compression on the original image to obtain a first compressed image specifically includes: Using the JPEG compression quality parameter as a loop variable, the following steps are looped until the JPEG compression quality parameter is equal to the minimum JPEG compression quality parameter or the amount of stored data of the compressed image is less than the preset second byte, and the compressed image is determined as the first compressed image; Performing JPEG quality compression on the original image using a JPEG compression quality parameter to obtain a compressed image; The JPEG compression quality parameter is gradually reduced according to a preset rule, and the adjusted JPEG compression quality parameter is determined as the JPEG compression quality parameter.

3. The method according to claim 1, characterized in that The step of compressing the image size and adjusting the JPEG quality of the first compressed image to obtain the second compressed image specifically includes: The number of times the image size is compressed is used as a loop variable, and the following steps are looped until the number of times the image size is compressed is equal to a preset number or the amount of stored data of the compressed sub-image is less than the preset second byte, and the compressed sub-image is determined as the second compressed image; Compress the image size of the first image to obtain a compressed parent image, and record the number of times the image size is compressed; The compressed parent image is JPEG compressed with a fixed JPEG compression quality parameter to obtain a compressed child image.

4. The method according to claim 1, characterized in that: Before the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image, the method further includes: Perform feature extraction on historical image samples to obtain historical image feature vectors; Training a predictor model using the historical image feature vector as input and the corresponding historical edge detail data as output; Determining the difference between adjacent target frequency domain coefficients in the low-frequency frequency domain coefficient matrix as a DC residual; Performing extended prediction on the DC residual by the predictor model to obtain edge detail data; The edge detail data is fused with the low-frequency frequency domain coefficient matrix to obtain an enhanced low-frequency frequency domain coefficient matrix.

5. The method according to claim 1, characterized in that After the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image, the method further includes: calculating a compression ratio of the third compressed image relative to the second compressed image; If the compression rate is lower than a preset compression rate threshold, adjusting the preset first size according to image features of the second compressed image; Re-execute the step of dividing the second compressed image into a plurality of super blocks of the same preset first size to the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain the third compressed image.

6. The method according to claim 1, characterized in that After the step of sending the data packet to be transmitted through the BeiDou-3 short message channel, the method further includes: The receiving end extracts the width and height data from the data packet to be transmitted; The receiving end establishes an image reconstruction buffer area of ​​a preset size according to the width and height data; The receiving end writes the image data in the data packet to be transmitted into the corresponding position of the image reconstruction buffer area in sequence according to the receiving order; The receiving end determines whether the image data in the image reconstruction buffer area meets a preset integrity requirement; If yes, the receiving end decompresses the image data in the image reconstruction buffer to obtain a final reconstructed image.

7. A progressive image compression transmission device, characterized in that: The progressive image compression and transmission device comprises: 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 comprises computer instructions, and the one or more processors call the computer instructions to enable the progressive image compression and transmission device to perform the method as described in any one of claims 1 to 6.

8. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a progressive image compression and transmission device, the progressive image compression and transmission device is enabled to execute the method according to any one of claims 1 to 6.

9. A computer program product, characterized in that When the computer program product runs on a progressive image compression transmission device, the progressive image compression transmission device is enabled to perform the method according to any one of claims 1 to 6.

Images