Satellite service-based air disaster recovery image storage method, storage medium and equipment

Abstract

The invention discloses an air disaster recovery image storage method based on satellite service, a storage medium and equipment, and the method comprises the steps: a satellite transmitting end transmits an image disaster recovery instruction to a machine room receiving end, and the machine room receiving end determines an image to be backed up according to the image disaster recovery instruction; classifying the to-be-backed-up images according to service types, and determining return priorities of the classified images according to service weights; according to a channel between the satellite transmitting end and the machine room receiving end, channel characteristic evaluation is carried out, an evaluation score is matched with a return priority, an image to be backed up is coded, and the coded image is returned to the satellite transmitting end through the matched channel; and decoding the image transmitted back to the satellite transmitting end, performing image quality reconstruction, and storing the image subjected to quality reconstruction in the satellite. According to the invention, the image data is backed up to the satellite, the disaster influence is avoided, the image data recovery speed is improved, and the image return quality is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of aerial disaster recovery image storage, and in particular to an aerial disaster recovery image storage method, storage medium and device based on satellite service. Background Art

[0002] In the digital age, image data is often closely related to the core business of enterprises. For example, in the medical field, patient imaging data is an important basis for diagnosis and treatment; in the security field, surveillance images are key evidence for event tracing and crime investigation. Once these data are lost or damaged due to disasters, failures or human errors, it will cause immeasurable losses to enterprises or institutions. Therefore, disaster recovery storage of image data is crucial to ensure the continuity of enterprise business. Disaster recovery storage can provide complete and available data recovery solutions in the event of loss or damage of original data, thereby ensuring the security of image data.

[0003] Currently, disaster recovery storage can use cloud backup or disaster recovery all-in-one backup to store image data in an off-site data center, which has high security. However, when a disaster occurs, data needs to be restored from an off-site storage center, but the recovery speed may be slow due to network bandwidth limitations, insufficient storage device performance, or improper recovery strategies, affecting the rapid recovery of business and resulting in poor quality of the returned images. Even when the disaster covers a wide area, it may cause abnormalities in the off-site data center, resulting in interruption of data recovery. Summary of the invention

[0004] In response to the problems existing in the prior art, the present invention provides an aerial disaster recovery image storage method, storage medium and device based on satellite services, which back up image data to satellites to avoid the impact of disasters, improve the image data recovery speed and ensure the quality of image transmission.

[0005] To achieve the above technical objectives, the present invention adopts the following technical solution: a method for storing aerial disaster recovery images based on satellite services, specifically comprising the following steps:

[0006] Step S1, the satellite transmitting end sends the image disaster recovery instruction to the receiving end in the computer room;

[0007] Step S2: The receiving end in the computer room determines the image to be backed up according to the image disaster recovery instruction;

[0008] Step S3: classify the images to be backed up according to the business type, and determine the return priority of the classified images according to the business weight;

[0009] Step S4: According to the channel between the satellite transmitting end and the receiving end in the equipment room, the channel characteristic evaluation is performed, the evaluation score is matched with the return priority, the image to be backed up is encoded, and the image is returned to the satellite transmitting end through the matching channel;

[0010] Step S5: decode the image transmitted back to the satellite transmitting end, reconstruct the image quality, and store the reconstructed image in the satellite.

[0011] Furthermore, the return priorities of the classified images in step S3 are divided into: highest priority, second highest priority, second lowest priority and lowest priority.

[0012] Furthermore, the specific process of performing channel characteristic evaluation in step S3 is: judging the availability of each channel, if it is unavailable, not performing channel characteristic evaluation; otherwise, determining the channel capacity, channel bandwidth and transmission rate of the channel, evaluating the bit error rate and noise level of the channel, and determining the evaluation score of the channel characteristics according to the channel capacity, channel bandwidth, transmission rate, bit error rate and noise level.

[0013] Furthermore, the calculation process of the evaluation score F of the channel characteristic is:

[0014] F=αF1+βF2+γF3+δF4+εF5

[0015] Among them, F1 represents the score of channel capacity, α represents the weight of F1; F2 represents the score of channel bandwidth, β represents the weight of F2; F3 represents the channel transmission rate, γ represents the weight of F3; F4 represents the score of the channel bit error rate, δ represents the weight of F4; F5 represents the score of the channel noise level, ε represents the weight of F5; α+β+γ+δ+ε=1.

[0016] Furthermore, in step S4, the specific process of matching the evaluation score with the return priority is as follows: the channels are divided into four categories according to the evaluation scores of the channel characteristics, wherein the channel with an evaluation score of (0.75, 1] ​​is a primary channel, the channel with an evaluation score of (0.5, 0.75] is a secondary channel, the channel with an evaluation score of (0.25, 0.5] is a tertiary channel, and the channel with an evaluation score of [0, 0.25] is a quaternary channel, the primary channel is used for the highest priority image return, the secondary channel is used for the second highest priority image return, the tertiary channel is used for the second lowest priority image return, and the quaternary channel is used for the lowest priority image return.

[0017] Furthermore, step S5 includes the following sub-steps:

[0018] Step S5.1, decoding the image transmitted back to the satellite transmitting end to form an image;

[0019] Step S5.2: Use the Sobel operator to calculate the image gradient, construct a gradient histogram, find the pixel maximum gradient, and calculate the standard deviation of the pixel maximum gradient. Where n represents the total number of pixels in the image, i represents the index of n, and H i represents the image gradient of the i-th pixel, H max Represents the maximum pixel gradient;

[0020] Step S5.3: set double thresholds according to the pixel maximum gradient and the pixel maximum gradient standard deviation, perform binarization on the image, obtain a clear image, and store it in the satellite.

[0021] Furthermore, the dual threshold setting process in step S5.3 is as follows:

[0022] T h =H max +τ·σ max

[0023] T l = k·T h

[0024] Among them, T h represents the high threshold, τ represents the adjustment factor, T l represents the low threshold, and k represents the proportional coefficient of the high threshold to the low threshold.

[0025] Furthermore, the process of binarizing the image in step S5.3 is: setting pixels in the image that are greater than the upper threshold to 255, and setting pixels in the image that are less than the lower threshold to 0.

[0026] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the satellite service-based aerial disaster recovery image storage method.

[0027] Furthermore, the present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the satellite service-based aerial disaster recovery image storage method is implemented.

[0028] Compared with the prior art, the present invention has the following beneficial effects: the aerial disaster recovery image storage method based on satellite service of the present invention stores the disaster recovery image in the satellite to avoid the impact of disasters, and can improve the business recovery efficiency when a disaster occurs; in order to achieve this purpose, when the image to be backed up is transmitted back to the satellite, the channel characteristics are evaluated, and the channel with excellent channel characteristics is used for high-priority image transmission, thereby improving the reliability of image transmission; and, since part of the signal may be lost during the channel transmission and decoding process, resulting in poor image quality uploaded to the satellite, the present invention reconstructs the image quality by setting a double threshold, accurately reconstructs the foreground and background parts, and ensures image clarity. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flow chart of the aerial disaster recovery image storage method based on satellite service of the present invention;

[0030] Figure 2 This is a flow chart of image quality reconstruction in the present invention. DETAILED DESCRIPTION

[0031] The technical solution of the present invention is further explained below in conjunction with the accompanying drawings.

[0032] like Figure 1 The flowchart of the method for storing aerial disaster recovery images based on satellite services of the present invention is as follows:

[0033] Step S1, the satellite transmitting end sends the image disaster recovery instruction to the receiving end in the computer room;

[0034] Step S2: The receiving end in the computer room determines the image to be backed up according to the image disaster recovery instruction;

[0035] Step S3, classify the images to be backed up according to the business type, and determine the return priority of the classified images according to the business weight. The higher the business weight priority, the higher the return priority of the image; specifically, the return priority of the classified images is divided into: highest priority, second highest priority, second lowest priority and lowest priority.

[0036] Step S4: Based on the channel between the satellite transmitter and the receiving end in the computer room, the channel characteristics are evaluated, the evaluation score is matched with the return priority, the image to be backed up is encoded, and the image is returned to the satellite transmitter through the matching channel. Through the channel characteristics evaluation, the channel with excellent channel characteristics is used for high-priority image transmission to improve the reliability of image transmission.

[0037] The specific process of evaluating the channel characteristics in the present invention is as follows: the availability of each channel is judged. If it is unavailable, the channel characteristics evaluation is not performed; otherwise, the channel capacity, channel bandwidth and transmission rate of the channel are determined, the bit error rate and noise level of the channel are evaluated, and the evaluation score of the channel characteristics is determined according to the channel capacity, channel bandwidth, transmission rate, bit error rate and noise level. The channel capacity indicates the maximum information rate that the channel can transmit, the channel bandwidth determines the maximum amount of data or frequency range that the channel can transmit, the transmission rate is the speed at which the image is transmitted in the channel, the bit error rate measures the frequency of errors occurring during the image transmission process, and the noise level reflects the degree of interference signals in the channel. Through comprehensive analysis of these indicators, the channel characteristics can be comprehensively and accurately evaluated.

[0038] The calculation process of the evaluation score F of the channel characteristics in the present invention is:

[0039] F=αF1+βF2+γF3+δF4+εF5

[0040] Among them, F1 represents the score of channel capacity, α represents the weight of F1; F2 represents the score of channel bandwidth, β represents the weight of F2; F3 represents the channel transmission rate, γ represents the weight of F3; F4 represents the score of the channel bit error rate, δ represents the weight of F4; F5 represents the score of the channel noise level, ε represents the weight of F5; α+β+γ+δ+ε=1.

[0041] The specific process of matching the evaluation score with the return priority in the present invention is: the channels are divided into four categories according to the evaluation scores of the channel characteristics, wherein the channel with an evaluation score of (0.75, 1] ​​is a primary channel, the channel with an evaluation score of (0.5, 0.75] is a secondary channel, the channel with an evaluation score of (0.25, 0.5] is a tertiary channel, and the channel with an evaluation score of [0, 0.25] is a quaternary channel. The primary channel is used for the highest priority image return, the secondary channel is used for the second highest priority image return, the tertiary channel is used for the second lowest priority image return, and the quaternary channel is used for the lowest priority image return. The higher the evaluation score of the channel characteristics, the higher the transmission reliability of the channel. Using it for high priority image transmission can improve the reliability of image transmission.

[0042] Step S5: Since part of the signal may be lost during the channel transmission and decoding process, resulting in poor image quality uploaded to the satellite, the image transmitted back to the satellite transmitting end is decoded and image quality is reconstructed to accurately reconstruct the foreground and background parts to ensure image clarity, and the quality reconstructed image is stored in the satellite, which specifically includes the following sub-steps:

[0043] Step S5.1, decoding the image transmitted back to the satellite transmitting end to form an image;

[0044] Step S5.2: Use the Sobel operator to calculate the image gradient, construct a gradient histogram, find the pixel maximum gradient, and calculate the standard deviation of the pixel maximum gradient. Where n represents the total number of pixels in the image, i represents the index of n, and H i represents the image gradient of the i-th pixel, H max Represents the maximum pixel gradient;

[0045] Step S5.3, set a double threshold value according to the pixel maximum gradient and the pixel maximum gradient standard deviation:

[0046] T h =H max +τ·σ max

[0047] T l = k·T h

[0048] Among them, T h represents the high threshold, τ represents the adjustment factor, T l represents the low threshold, k represents the ratio coefficient between the high threshold and the low threshold;

[0049] The image is binarized. Specifically, the pixels in the image that are greater than the high threshold are set to 255, and the pixels in the image that are less than the low threshold are set to 0. This can reduce the discontinuity of the contour edge of the foreground image or the failure to detect some targets due to the difference in the grayscale changes of the local image, and retain more detailed information in the image to obtain a clear image and store it in the satellite.

[0050] The satellite service-based aerial disaster recovery image storage method of the present invention backs up image data to a satellite, avoids the impact of disasters, improves the image data recovery speed, and ensures the image return quality.

[0051] In a technical solution of the present invention, a computer-readable storage medium is also provided, storing a computer program, wherein the computer program enables a computer to execute the satellite service-based aerial disaster recovery image storage method.

[0052] In a technical solution of the present invention, an electronic device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the satellite service-based aerial disaster recovery image storage method is implemented.

[0053] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0054] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0055] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A method for storing aerial disaster recovery images based on satellite services, characterized in that: The specific steps include: Step S1, the satellite transmitting end sends the image disaster recovery instruction to the receiving end in the computer room; Step S2: The receiving end in the computer room determines the image to be backed up according to the image disaster recovery instruction; Step S3: classify the images to be backed up according to the business type, and determine the return priority of the classified images according to the business weight; Step S4: According to the channel between the satellite transmitting end and the receiving end in the equipment room, the channel characteristic evaluation is performed, the evaluation score is matched with the return priority, the image to be backed up is encoded, and the image is returned to the satellite transmitting end through the matching channel; Step S5: decode the image transmitted back to the satellite transmitting end, reconstruct the image quality, and store the reconstructed image in the satellite.

2. The method for storing aerial disaster recovery images based on satellite services according to claim 1, characterized in that: The return priorities of the classified images in step S3 are divided into: highest priority, second highest priority, second lowest priority and lowest priority.

3. The method for storing aerial disaster recovery images based on satellite services according to claim 2, characterized in that: The specific process of performing channel characteristic evaluation in step S3 is: judging the availability of each channel, if it is unavailable, not performing channel characteristic evaluation; otherwise, determining the channel capacity, channel bandwidth and transmission rate of the channel, evaluating the bit error rate and noise level of the channel, and determining the evaluation score of the channel characteristics according to the channel capacity, channel bandwidth, transmission rate, bit error rate and noise level.

4. The method for storing aerial disaster recovery images based on satellite services according to claim 3, characterized in that: The calculation process of the evaluation score F of the channel characteristic is: F=αF1+βF2+γF3+δF4+εF5 Among them, F1 represents the score of channel capacity, α represents the weight of F1; F2 represents the score of channel bandwidth, β represents the weight of F2; F3 represents the channel transmission rate, γ represents the weight of F3; F4 represents the score of the channel bit error rate, δ represents the weight of F4; F5 represents the score of the channel noise level, ε represents the weight of F5; α+β+γ+δ+ε=1.

5. The method for storing aerial disaster recovery images based on satellite services according to claim 4, characterized in that: The specific process of matching the evaluation score with the return priority in step S4 is: the channels are divided into four categories according to the evaluation scores of the channel characteristics, wherein the channel with an evaluation score of (0.75, 1] ​​is a primary channel, the channel with an evaluation score of (0.5, 0.75] is a secondary channel, the channel with an evaluation score of (0.25, 0.5] is a tertiary channel, and the channel with an evaluation score of [0, 0.25] is a quaternary channel. The primary channel is used for the highest priority image return, the secondary channel is used for the second highest priority image return, the tertiary channel is used for the second lowest priority image return, and the quaternary channel is used for the lowest priority image return.

6. The method for storing aerial disaster recovery images based on satellite services according to claim 5, characterized in that: Step S5 includes the following sub-steps: Step S5.1, decoding the image transmitted back to the satellite transmitting end to form an image; Step S5.2: Use the Sobel operator to calculate the image gradient, construct a gradient histogram, find the pixel maximum gradient, and calculate the standard deviation of the pixel maximum gradient. Where n represents the total number of pixels in the image, i represents the index of n, and H i represents the image gradient of the i-th pixel, H max Represents the maximum pixel gradient; Step S5.3: set double thresholds according to the pixel maximum gradient and the pixel maximum gradient standard deviation, perform binarization on the image, obtain a clear image, and store it in the satellite.

7. The method for storing aerial disaster recovery images based on satellite services according to claim 6, characterized in that: The process of setting the dual threshold in step S5.3 is: T h =H max +t·s max T l =k·T h Among them, T h represents the high threshold, τ represents the adjustment factor, T l represents the low threshold, and k represents the proportional coefficient of the high threshold to the low threshold.

8. The method for storing aerial disaster recovery images based on satellite services according to claim 1, characterized in that: The process of binarizing the image in step S5.3 is as follows: pixels in the image that are greater than the upper threshold are set to 255, and pixels in the image that are less than the lower threshold are set to 0.

9. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the aerial disaster recovery image storage method based on satellite service as described in any one of claims 1-8.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for storing aerial disaster recovery images based on satellite services as described in any one of claims 1 to 8 is implemented.

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