Progressive image compression transmission method and device, medium and product

Abstract

The invention discloses a progressive image compression transmission method and device, a medium and a product, and relates to the field of image processing. Through adoption of the progressive image compression transmission device, the original image is subjected to multi-stage compression, and the compressed original image is subpackaged, so that the data volume of image transmission is reduced, the image quality is ensured, and a large-size image can be efficiently transmitted through a Beidou short message channel with a limited bandwidth.

Description

Technical Field

[0001] The present application relates to the field of image processing, and in particular to a progressive image compression transmission method, device, medium and product. Background Art

[0002] With the rapid development of Internet of Things technology, the demand for data transmission in remote areas or wild environments is growing. 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 my country, the Beidou-3 satellite navigation system, with its short message communication function, provides an important communication means for data transmission in remote areas or wild environments.

[0003] At present, when using Beidou short messages to transmit image data, direct compression transmission is usually adopted, that is, the original image is first compressed, and then the compressed original image is sent through the Beidou short message channel. This method can realize basic image transmission functions and has been applied in some simple application scenarios.

[0004] However, in practical applications, due to the bandwidth limitation and large transmission delay of Beidou short message channel, direct compression transmission often leads to low image transmission efficiency. Especially when transmitting large-size images, even after compression, the amount of data transmitted in a single transmission is still large, which can easily cause communication congestion. Summary of the invention

[0005] The present application provides a progressive image compression transmission method, device, medium and product for improving image transmission efficiency.

[0006] In a first aspect, the present application provides a progressive image compression and transmission method, which is applied to a progressive image compression and transmission device, and the method includes: converting 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; performing JPEG quality compression on the original image to obtain a first compressed image; judging whether the storage data volume 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 volume of the second compressed image is less than the storage data volume of the first compressed image; performing JPEG 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; packetizing the third compressed image according to a preset fourth byte to obtain multiple image data packets, and the preset fourth byte is less than the preset third byte; encapsulating the width and height data, the image data packet and other JSON information to obtain a data packet to be transmitted; and sending the data 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 compresses the image size of the first compressed image to obtain a compressed parent image, and 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 child image. This process will be repeated until the number of image size compressions is equal to the preset number of times or the amount of stored data of the compressed child image is less than the preset second byte. This progressive compression method can significantly reduce the amount of data while maintaining the main content of the image. Compared with simple quality compression, combined with size compression, it can more effectively reduce the amount of image data, and the compression effect is more controllable and stable.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the second compressed image is JXL compressed to obtain a third compressed image, specifically including: 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 frequency domain coefficients corresponding to each super block, 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, the preset second size being 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 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.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain a third compressed image, the method also includes: performing feature extraction on historical image samples to obtain a historical image feature vector; using the historical image feature vector as input and the corresponding historical edge detail data as output to train a predictor model; 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 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 the edge detail enhancement technology based on machine learning, that is, by extracting and training the features of historical image samples, a predictor model is established to predict the 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 to expand the details, and merges 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 maintains 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 rate, which is particularly suitable for application scenarios where edge details need to be maintained.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain a third compressed image, the method also 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 characteristics of the second compressed image; re-executing the step of dividing the second compressed image into multiple super blocks of the same preset first size until 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 transmission device dynamically adjusts the size parameters of the super block 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 transmission device automatically adjusts the size parameters of the super block according to the image characteristics and re-compresses the image. 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 also includes: the receiving end extracts width and height data from the data packet to be transmitted; the receiving end establishes an image reconstruction buffer of a preset size based on the width and height data; the receiving end writes the image data in the data packet to be transmitted into the corresponding positions of the image reconstruction buffer in sequence according to the receiving order; the receiving end determines whether the image data in the image reconstruction buffer meets the preset completeness requirement; if so, the receiving end decompresses the image data in the image reconstruction buffer to obtain the final reconstructed image.

[0019] By adopting the above technical solution, the receiving end establishes an image reconstruction buffer of a preset size based on the width and height data, and then writes the image data in the data packet to be transmitted into the corresponding position of the image reconstruction buffer in sequence according to the receiving order. The receiving end determines the integrity of the data, ensures that all necessary information has been received, and finally decompresses and reconstructs it. This mechanism not only supports progressive display, but also effectively handles packet loss or delay. Compared with the traditional one-time reception and reconstruction method, it has better fault tolerance and user experience. Even in the case of unstable network conditions, it can ensure reliable transmission and reconstruction of images, which 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 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 described in the first aspect and any possible implementation manner of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the above-mentioned computer program product runs on a progressive image compression and transmission device, the above-mentioned progressive image compression and transmission device executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the above instructions are executed on a progressive image compression and transmission device, the above progressive image compression and transmission device executes the method described in the first aspect and any possible implementation method of 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: 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.

[0025] 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.

[0026] 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

[0027] Figure 1 It is a flowchart of a progressive image compression transmission method in an embodiment of the present application; Figure 2 is another flowchart of the progressive image compression transmission method in an embodiment of the present application; Figure 3It is a schematic diagram of a physical device structure of a progressive image compression transmission device in an embodiment of the present application. DETAILED DESCRIPTION

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

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

[0030] The following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of the progressive image compression transmission method in an embodiment of the present application.

[0031] S101, 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; Among them, the original image refers to the 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 pixels in the original image in the horizontal direction; the height value refers to the number of pixels in the original image in the vertical direction; the width and height data refers to binary data that organizes the width and height values ​​in a specific format; the preset first byte refers to a predetermined fixed number of bytes used to store the width and height data, usually 4 bytes.

[0032] 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 and height values ​​of the original image; then, the progressive image compression and transmission device converts these two decimal values ​​into binary format; then, the progressive image compression and transmission device organizes the binary data into a fixed-length byte sequence in the manner of high bits first and low bits last; finally, the progressive image compression and transmission device stores the byte sequence as width and height data in a storage space of a preset first byte size.

[0033] S102, performing JPEG quality compression on the original image to obtain a first compressed image; The JPEG quality compression refers to compressing the original image using a lossy compression algorithm in the JPEG standard; the first compressed image is an image file obtained after the original image is compressed by JPEG.

[0034] After the extraction and conversion of the image size information is completed, the progressive image compression and transmission device needs to perform preliminary compression on the original image to reduce the amount of data. Specifically, first, the progressive image compression and transmission device sets the initial JPEG compression quality parameter. The JPEG compression quality parameter usually selects a higher value (such as 50) to ensure the image quality. The JPEG compression quality parameter refers to the parameter value that controls the degree of compression, which is usually an integer of 0-100. Then, the progressive image compression and transmission device determines whether the storage data volume of the compressed original image is less than the preset second byte. The storage data volume refers to the number of bytes occupied by the compressed original image. If it is less than, it means that the original image is compressed with JPEG quality using the initial JPEG compression quality parameter, and the storage data volume of the compressed original image meets the compression requirements, and the progressive image compression and transmission device can output the first compressed image; if it is greater than, it means that the original image is compressed with JPEG quality using the initial JPEG compression quality parameter, and the storage data volume of the compressed original image does not meet the compression requirements, and the progressive image compression and transmission device needs to further compress. Next, the progressive image compression transmission device sets a lower JPEG compression quality parameter (e.g., 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. This continues until the JPEG compression quality parameter reaches the lowest JPEG compression quality parameter (e.g., 30) or the storage data volume of the compressed original image is less than the preset second byte, at which point the progressive image compression transmission device outputs the first compressed image.

[0035] Optionally, in general, performing JPEG quality compression on the original image to obtain a first compressed image can be achieved in the following manner, which is not limited here: using a JPEG compression quality parameter as a loop variable, and looping the following steps until the JPEG compression quality parameter is equal to the minimum JPEG compression quality parameter or the amount of storage data of the compressed image is less than a preset second byte, then the compressed image is determined 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.

[0036] The following two specific examples illustrate the JPEG quality compression cycle: Example 1, assuming the initial conditions: Original image size: 2MB (2048KB); Initial JPEG compression quality parameter: 95; Minimum JPEG compression quality parameter: 60; Default second byte (target size): 500KB; Default rule: Each time the JPEG compression quality parameter is reduced by 5; Example of a loop process: First cycle: JPEG compression quality parameter = 95; Compressed image size = 1200KB; 1200KB>500KB, continue the cycle; New JPEG compression quality parameter = 95-5 = 90; Second cycle: JPEG compression quality parameter = 90; Compressed image size = 900KB; 900KB>500KB, continue the cycle; New JPEG compression quality parameter = 90-5 = 85; 3rd cycle: JPEG compression quality parameter = 85; Compressed image size = 700KB; 700KB>500KB, continue the cycle; New JPEG compression quality parameter = 85-5 = 80; 4th cycle: JPEG compression quality parameter = 80; Compressed image size = 480KB; 480KB<500KB, the loop ends; Final result: The size of the first compressed image is 480KB, the JPEG compression quality parameter used is 80, the compression ratio reaches about 76.6%, and the image quality remains within an acceptable range.

[0037] Example 2, assuming the initial conditions: Original image size: 5MB (5120KB); Initial JPEG compression quality parameter: 95; Minimum JPEG compression quality parameter: 60; Default second byte (target size): 400KB; Default rule: Each time the JPEG compression quality parameter is reduced by 5; Example of a loop process: First cycle: JPEG compression quality parameter = 95; Compressed image size = 2800KB; 2800KB>400KB, continue the cycle; New JPEG compression quality parameter = 95-5 = 90; Second cycle: JPEG compression quality parameter = 90; Compressed image size = 2100KB; 2100KB>400KB, continue the cycle; New JPEG compression quality parameter = 90-5 = 85; ...(the middle loop is omitted)... 7th cycle: JPEG compression quality parameter = 65; Compressed image size = 850KB; 850KB>400KB, continue the cycle; New JPEG compression quality parameter = 65-5 = 60; 8th cycle: JPEG compression quality parameter = 60 (minimum limit reached); Compressed image size = 750KB; 750KB>400KB, but the JPEG compression quality parameter has reached the minimum JPEG compression quality parameter, and the loop ends; 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 reaches the minimum JPEG compression quality parameter, the storage data volume of the first compressed image still exceeds the preset second byte. At this time, it is necessary to proceed to the next step of image size compression and JPEG quality adjustment.

[0038] S103, determining whether the storage data volume of the first compressed image is greater than a preset second byte; The preset second byte refers to a predetermined threshold value of the maximum allowed image storage data volume for JPEG quality compression, which is usually determined based on the bandwidth limitation of the transmission channel; the storage data volume refers to the number of bytes actually occupied by the first compressed image.

[0039] After obtaining the first compressed image, the progressive image compression transmission device needs to evaluate whether it meets the transmission requirements. Specifically, the progressive image compression transmission device obtains the storage data volume of the first compressed image, and compares the storage data volume with the preset second byte to determine whether the storage data volume of the first compressed image is greater than the preset second byte.

[0040] S104, if yes, compress the image size and adjust the JPEG quality of the first compressed image to obtain a second compressed image, wherein the storage data amount of the second compressed image is less than the storage data amount of the first compressed image; Among them, image size compression refers to the operation of reducing the amount of data by lowering the image resolution; JPEG quality adjustment refers to the process of resetting JPEG compression parameters for compression; the second compressed image refers to the image file obtained after image size compression and JPEG quality adjustment.

[0041] When the amount of storage data of the first compressed image exceeds the preset second byte, the progressive image compression and transmission device needs to perform a deeper level of compression. Specifically, the progressive image compression and transmission device first compresses the image size of the first compressed image, for example, each time it is reduced to 0.9 times of the previous size, and the number of image size compressions is at most 5 times. After each reduction, the progressive image compression and transmission device uses a fixed JPEG compression quality parameter (for example, 50) to perform JPEG quality compression on the first compressed image after image size compression, and determines whether the amount of storage data of the first compressed image after image size compression and JPEG quality adjustment is less than the preset second byte. And so on, until the number of image size compressions reaches 5 times or the amount of storage data of the first compressed image after image size compression and JPEG quality adjustment is less than the preset second byte, at this time, the progressive image compression and transmission device outputs the second compressed image.

[0042] Optionally, in general, performing image size compression and JPEG quality adjustment on the first compressed image to obtain the second compressed image can be achieved in the following manner, which is not limited here: using 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 fixed JPEG compression quality parameters to obtain a compressed sub-image.

[0043] The following is an example of a loop that performs image resizing and JPEG quality adjustment.

[0044] Assume initial conditions: Size of the first compressed image: 750KB; The size of the first compressed image: 2400×1800 pixels; Default second byte (target size): 400KB; Fixed JPEG compression quality parameter: 75; Preset compression times: 3; Each size compression ratio: reduce by 50%; Example of a loop process: First cycle: Current image size compression times = 1; The size of the compressed parent image = 1200 × 900 pixels (length and width are reduced by 50%); Fixed JPEG compression quality parameter = 75; The size of the compressed sub-image = 520KB; 520KB>400KB, continue the cycle; Second cycle: Current image size compression times = 2; The size of the compressed parent image = 600 × 450 pixels; Fixed JPEG compression quality parameter = 75; The size of the compressed sub-image = 380KB; 380KB<400KB, the loop ends; Final result: The size of the second compressed image is 380KB, the final image size is 600×450 pixels, the actual number of image size compressions is 2 times (does not reach the preset compression number of 3 times), the JPEG compression quality remains at 75, and the image size is successfully reduced to below the target value through image size compression.

[0045] S105, 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; 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 compressed data volume, and the preset third byte needs to be smaller than the preset second byte to ensure further reduction of the data volume.

[0046] After the second compressed image is generated, the progressive image compression and transmission device needs to perform more efficient compression to further reduce the amount of stored data. Specifically, first, the progressive image compression and transmission device divides the second compressed image into multiple super blocks according to a preset size, and the super block refers to a basic processing unit of a fixed size for dividing the image. Then, the progressive image compression and transmission device performs DCT transformation on each super block to obtain frequency domain coefficients representing different frequency components, and the frequency domain coefficients represent the representation of the image in the frequency domain. Next, the progressive image compression and transmission device sorts all frequency domain coefficients according to their contribution to the image clarity, and the clarity contribution value refers to the degree of influence of a certain frequency domain component on the visual quality of the image. After that, the progressive image compression and transmission device selects several frequency domain coefficients with the largest contribution 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 a preset third byte. The whole process achieves efficient compression by removing high-frequency information that is not sensitive to the human eye.

[0047] Optionally, in general, performing JXL compression on the second compressed image to obtain the third compressed image can be achieved in the following manner, which is not limited here: 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 frequency domain coefficients corresponding to each super block, 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, the preset second size being 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.

[0048] The following is a specific example of JXL compression: Assume initial conditions: The size of the second compressed image: 600×450 pixels; Default first size (super block size): 64×64 pixels; Preset second size (low-frequency domain coefficient matrix size): 32×32 pixels; The number of frequency domain coefficients retained by default: 512; Example of compression process: Divide super block: Image horizontal direction: 600÷64=9.375, rounded up to 10 blocks; Image vertical direction: 450÷64=7.031, rounded up to 8 blocks; A total of 80 super blocks (10×8) are obtained; DCT transform example (taking a 64×64 super block as an example): Input: 64×64 pixel image data; Perform 2D-DCT transformation to obtain a 64×64 frequency domain coefficient matrix; Assume that some of the obtained frequency domain coefficient values ​​(example): DC component: 1024; AC components: 512, 256, 128, 64, 32, 16, 8, 4, ... Frequency domain coefficient ordering (example values): Sorted list of frequency domain coefficients (descending order): 1024 (DC component); 512 (primary edge features); 256 (minor edge features); 128 (detailed features)...etc. 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; Entropy coding compression: Entropy coding is performed on the 32×32 low-frequency frequency domain coefficient matrix, for example, shorter codes are assigned to frequently occurring frequency domain coefficient values, longer codes are assigned to rare frequency domain coefficient values, and run-length coding is used to process continuous zero values; Final result: Original superblock size: 64×64×8 bits = 32,768 bits; Compressed size: about 8,192 bits (compression rate 75%); Overall image compression effect: Second compressed image: 380KB; Third compressed image: estimated 95KB; Total compression ratio: 75%.

[0049] S106, 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; The preset fourth byte refers to the maximum allowed size of a single image data packet; the packetization 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.

[0050] After the third compressed image is generated, the progressive image compression transmission device needs to divide it into image data packets suitable for transmission. Specifically, the progressive image compression transmission device calculates the number of image data packets that need 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 transmission device divides the third compressed image into packets according to the preset fourth byte and the number of image data packets to obtain multiple image data packets.

[0051] S107, encapsulating the width and height data, the image data packet and other JSON information to obtain a data packet to be transmitted; Among them, the width and height data refer to the size information of the original image obtained in step S101; JSON other information refers to various metadata organized in JSON format, such as compression parameters, timestamps, etc.; encapsulation refers to organizing multiple types of data into a unified data structure according to a specific format; the data packet to be transmitted refers to the complete data unit ultimately used for transmission.

[0052] 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.

[0053] S108. Send the data packet to be transmitted through the BeiDou-3 short message channel.

[0054] 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.

[0055] 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.

[0056] 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.

[0057] 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.

[0058] 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; For details, please refer to step S101, which will not be described in detail here.

[0059] S202, performing JPEG quality compression on the original image to obtain a first compressed image; For details, please refer to step S102, which will not be described in detail here.

[0060] S203, determining whether the storage data volume of the first compressed image is greater than a preset second byte; For details, please refer to step S103, which will not be described in detail here.

[0061] S204: If yes, perform 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 less than the storage data volume of the first compressed image; For details, please refer to step S104, which will not be described in detail here.

[0062] S205, extracting features from historical image samples to obtain historical image feature vectors; Among them, historical image samples refer to representative image data sets collected in advance; feature extraction refers to extracting numerical descriptions that can characterize image characteristics from historical image samples; image features include image attributes such as texture features, edge features, and color features; historical image feature vectors refer to numerical sequences organized into extracted image features.

[0063] Specifically, first, the progressive image compression and transmission device loads pre-prepared historical image samples from a database, and then, the progressive image compression and transmission device pre-processes each historical image sample, including size unification and color space conversion; then, the progressive image compression and transmission device uses a variety of feature extraction operators, such as Gabor filters, HOG descriptors, etc. to extract texture features and edge features of the historical image samples; then, 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 a historical image feature vector of a fixed dimension.

[0064] S206, training a predictor model using the historical image feature vector as input and the corresponding historical edge detail data as output; 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 historical image samples.

[0065] When the historical image feature vector is prepared, the progressive image compression and transmission device needs to establish a mapping relationship from the image feature vector 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 vector and the corresponding historical edge detail data into a training set and a validation set; then, the progressive image compression and transmission device sets training parameters, such as batch size, learning rate, etc.; then, the progressive image compression and transmission device performs multiple rounds of training, and updates the model parameters in each round through the back propagation algorithm; 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.

[0066] S207, determining the difference between adjacent target frequency domain coefficients in the low-frequency frequency domain coefficient matrix as a DC residual; 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 coefficients refer to the important frequency domain coefficients retained after screening; the adjacent target frequency domain coefficients refer to the target frequency domain coefficients that are adjacent in the low-frequency frequency domain coefficient matrix; the DC residual refers to the difference between adjacent target frequency domain coefficients.

[0067] When it is necessary to analyze the frequency domain characteristics, 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 sequentially accesses the adjacent target frequency domain coefficients 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 performs statistical analysis on the DC residual sequence to determine the significance threshold.

[0068] S208, performing extended prediction on the DC residual through a predictor model to obtain edge detail data; 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.

[0069] After obtaining the DC residual, the progressive image compression and transmission device needs to use the trained predictor model to restore the details. Specifically, first, the progressive image compression and transmission device converts the DC residual 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; then, the progressive image compression and transmission device performs post-processing on the output of the predictor model, including scale recovery and range limitation; then, the progressive image compression and transmission device evaluates the reliability of the prediction results and selects predictions with high confidence; finally, the progressive image compression and transmission device organizes the prediction results into a standardized edge detail data format.

[0070] S209, fusing the edge detail data with the low-frequency frequency domain coefficient matrix to obtain an enhanced low-frequency frequency domain coefficient matrix; Among them, fusion refers to the process of rationally 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.

[0071] When the edge detail data prediction 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, taking into account local image features and signal strength; then, 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; then, the progressive image compression and transmission device performs a data consistency check to ensure that the fusion does not introduce artifacts; finally, the progressive image compression and transmission device optimizes and adjusts the fusion results to obtain a low-frequency frequency domain coefficient matrix with enhanced detail performance. This fusion process maintains the main low-frequency information while supplementing richer detail performance.

[0072] S210, 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; For details, please refer to step S105, which will not be described in detail here.

[0073] S211, calculating the compression ratio of the third compressed image relative to the second compressed image; The compression ratio refers to the ratio of the change in the amount of stored data before and after compression; the compression ratio is generally calculated through division operations.

[0074] After the third compressed image is generated, the progressive image compression and transmission device needs to evaluate whether the compression effect reaches the expected result. 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; then, 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.

[0075] S212: 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; Among them, the preset compression rate threshold refers to the minimum compression effect; the image feature refers to the feature value describing the image content and structure; and the preset first size refers to the size parameter of the super block.

[0076] When it is found that the compression effect is not ideal, the progressive image compression transmission device needs to optimize the compression parameters. Specifically, first, the progressive image compression transmission device analyzes the texture complexity, edge distribution and other characteristics of the second compressed image; then, the progressive image compression transmission device evaluates whether the size of the current super block is appropriate based on these characteristics; then, the progressive image compression transmission device calculates new size parameters based on a predetermined adjustment strategy, and complex areas tend to use smaller sizes, and simple areas tend to use larger sizes; then, the progressive image compression transmission device verifies the rationality of the new size parameters to ensure that they are within the effective range.

[0077] S213, re-performing the step of dividing the second compressed image into a plurality of super blocks of the same preset first size to performing entropy coding compression processing on the low-frequency frequency domain coefficient matrix to obtain a third compressed image; Here, re-execution refers to repeatedly performing JXL compression on the second compressed image using new size parameters to obtain a third compressed image. For details, please refer to step S105, which will not be repeated here.

[0078] S214, 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; For details, please refer to step S106, which will not be described in detail here.

[0079] S215, encapsulating the width and height data, the image data packet and other JSON information to obtain a data packet to be transmitted; For details, please refer to step S107, which will not be described in detail here.

[0080] S216. Send the data packet to be transmitted through the BeiDou-3 short message channel.

[0081] For details, please refer to step S108, which will not be described in detail here.

[0082] The following describes the progressive image compression transmission device in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of a progressive image compression transmission device in an embodiment of the present application.

[0083] It should be noted that Figure 3 The structure of the progressive image compression transmission device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0084] like Figure 3 As shown, the progressive image compression 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 part 308 to the RAM 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, the ROM 302 and the RAM 303 are connected to each other through a bus 304. The I / O interface 305 is also connected to the bus 304.

[0085] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0086] 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 part 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.

[0087] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0088] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0089] Specifically, the progressive image compression transmission device of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the progressive image compression transmission method provided by the above embodiment is implemented.

[0090] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the progressive image compression transmission device described in the above embodiment; or may exist independently without being assembled into the progressive image compression transmission device. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the progressive image compression transmission device, the progressive image compression transmission device implements the progressive image compression transmission method provided in the above embodiment.

[0091] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0092] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0093] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A 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; The data packet to be transmitted is sent through the BeiDou-3 short message channel.

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: The performing JXL compression on the second compressed image to obtain a third compressed image specifically includes: Dividing the second compressed image into a plurality of 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 a clarity contribution value; Sorting the frequency domain coefficients to obtain a frequency domain coefficient list; Retain a preset number of target frequency domain coefficients with the largest values ​​in the frequency domain coefficient list, and construct 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; The low-frequency frequency domain coefficient matrix is ​​subjected to entropy coding compression processing to obtain the third compressed image.

5. The method according to claim 4, 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.

6. The method according to claim 4, 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.

7. 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.

8. 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 execute the method as described in any one of claims 1-7.

9. 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 7.

10. A computer program product, characterized in that When the computer program product runs on a progressive image compression and transmission device, the progressive image compression and transmission device is enabled to perform the method according to any one of claims 1 to 7.

Images