CN117993029A - Satellite information and training data warehouse network safety protection method and system - Google Patents
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Abstract
The invention discloses a satellite information and training data warehouse network safety protection method and system, wherein the satellite information is a satellite remote sensing image, the training data is a topography image of a training field, and the method comprises the following steps: taking the satellite remote sensing image and the topographic image as original images, acquiring pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block; and respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing.
Description
Technical Field
The invention belongs to the technical field of data safety protection, and particularly relates to a satellite information and training data warehouse network safety protection method and system.
Background
Image processing technology is continually evolving and evolving, involving multiple fields. The following are some of the current state of the art image processing:
deep learning and Convolutional Neural Network (CNN):
deep learning has achieved significant success in the field of image processing. Convolutional Neural Networks (CNNs) are the dominant method that is excellent in tasks such as image classification, object detection, segmentation, and the like.
A pre-trained deep learning model (such as the model on ImageNet) can be used for transfer learning, speeding up the training and execution of many image processing tasks.
Image generation and GAN (generation antagonism network):
Generating a countermeasure network (GAN) is a powerful technique that can be used for image generation, style conversion, and image enhancement. GAN can generate realistic images and can even be used to create artwork.
Super resolution:
super-resolution techniques aim to improve image quality by increasing the spatial resolution of the image. The deep learning method has made an important progress in this respect, making it possible to generate a high-resolution image from a low-resolution image.
However, there is no technical solution in the prior art, which can process the image and increase the security of image storage.
Disclosure of Invention
In order to solve the technical problems, the invention provides a satellite information and training data warehouse network safety protection method, wherein the satellite information is a satellite remote sensing image, the training data is a topography image of a training field, and the method comprises the following steps:
Taking the satellite remote sensing image and the topographic image as original images, acquiring pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
And respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing.
Further, the image cutting model includes:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,For the length of the image block,/>For the original image at coordinates/>The pixel value at which it is located,To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>In coordinates in the original imageAn image correction function at.
Further, the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
Further, the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
Further, the original image is at the coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
The invention also provides a satellite information and training data warehouse network safety protection system, the satellite information is a satellite remote sensing image, the training data is a topography image of a training field, and the system comprises:
The image acquisition module is used for taking the satellite remote sensing image and the topographic image as original images, acquiring pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
And the safety module is used for respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a safety level for each storage area, carrying out safety verification with the safety level of a user, and extracting the image blocks in the storage areas after the safety verification is passed.
Further, the image cutting model includes:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,For the length of the image block,/>For the original image at coordinates/>The pixel value at which it is located,To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>In coordinates in the original imageAn image correction function at.
Further, the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
Further, the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
Further, the original image is at the coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
The method comprises the steps of taking the satellite remote sensing image and the topographic image as original images, obtaining pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block; and respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing. According to the technical scheme, the image can be segmented and stored in different storage areas respectively, so that the safety capability is improved.
Drawings
FIG. 1 is a flow chart of the method of embodiment 1 of the present invention;
Fig. 2 is a system configuration diagram of embodiment 2 of the present invention.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
The method provided by the invention can be implemented in a terminal environment, wherein the terminal can comprise one or more of the following components: processor, storage medium, and display screen. Wherein the storage medium has stored therein at least one instruction that is loaded and executed by the processor to implement the method described in the embodiments below.
The processor may include one or more processing cores. The processor connects various parts within the overall terminal using various interfaces and lines, performs various functions of the terminal and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the storage medium, and invoking data stored in the storage medium.
The storage medium may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (ROM). The storage medium may be used to store instructions, programs, code sets, or instructions.
The display screen is used for displaying the interactive interface of each application program.
All subscripts in the formula of the invention are only used for distinguishing parameters and have no practical meaning.
In addition, it will be appreciated by those skilled in the art that the structure of the terminal described above is not limiting and that the terminal may include more or fewer components, or may combine certain components, or a different arrangement of components. For example, the terminal further includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and the like, which are not described herein.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a method for protecting satellite information and a training data warehouse network, where the satellite information is a satellite remote sensing image, and the training data is a topography image of a training field, and the method includes:
Step 101, taking the satellite remote sensing image and the topographic image as original images, obtaining pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
Specifically, the image cutting model includes:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,For the length of the image block,/>For the original image at coordinates/>The pixel value at which it is located,To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>In coordinates in the original imageAn image correction function at.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
Specifically, the original image is represented by coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
Step 102, storing the cut image blocks in a plurality of storage areas of the cloud respectively, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing the security verification.
Example 2
As shown in fig. 2, the embodiment of the present invention further provides a system for protecting satellite information and a training data warehouse network, where the satellite information is a satellite remote sensing image, the training data is a topography image of a training field, and the system includes:
The image acquisition module is used for taking the satellite remote sensing image and the topographic image as original images, acquiring pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
Specifically, the image cutting model includes:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,For the length of the image block,/>For the original image at coordinates/>The pixel value at which it is located,To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>In coordinates in the original imageAn image correction function at.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
Specifically, the original image is represented by coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
And the safety module is used for respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a safety level for each storage area, carrying out safety verification with the safety level of a user, and extracting the image blocks in the storage areas after the safety verification is passed.
Example 3
The embodiment of the invention also provides a storage medium which stores a plurality of instructions for realizing the satellite information and training data warehouse network safety protection method, wherein the satellite information is a satellite remote sensing image.
Alternatively, in this embodiment, the storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.
Alternatively, in the present embodiment, the storage medium is configured to store program code for performing the steps of: step 101, taking the satellite remote sensing image and the topographic image as original images, obtaining pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
Specifically, the image cutting model includes:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,For the length of the image block,/>For the original image at coordinates/>The pixel value at which it is located,To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>In coordinates in the original imageAn image correction function at.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
Specifically, the original image is represented by coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
Step 102, storing the cut image blocks in a plurality of storage areas of the cloud respectively, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing the security verification.
Example 4
The embodiment of the invention also provides electronic equipment, which comprises a processor and a storage medium connected with the processor, wherein the storage medium stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute a satellite information and training data warehouse network security protection method, and the satellite information is a satellite remote sensing image.
Specifically, the electronic device of the present embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.
The storage medium can be used for storing software programs and modules, such as a satellite information and training data warehouse network security protection method in the embodiment of the invention, the satellite information is a satellite remote sensing image, the corresponding program instructions/modules, and the processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, so that the satellite information and training data warehouse network security protection method is realized. The storage medium may include a high-speed random access storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage medium. In some examples, the storage medium may further include a storage medium remotely located with respect to the processor, and the remote storage medium may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor may invoke the information stored in the storage medium and the application program through the transmission system to perform the steps of: step 101, taking the satellite remote sensing image and the topographic image as original images, obtaining pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
Specifically, the image cutting model includes:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,For the length of the image block,/>For the original image at coordinates/>The pixel value at which it is located,To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>In coordinates in the original imageAn image correction function at.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
Specifically, the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
Specifically, the original image is represented by coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
Step 102, storing the cut image blocks in a plurality of storage areas of the cloud respectively, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing the security verification.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed technology may be implemented in other manners. The system embodiments described above are merely exemplary, and for example, the division of the units is merely a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or partly in the form of a software product or all or part of the technical solution, which is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random-access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, etc., which can store program codes.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.
Claims (10)
1. The satellite information is a satellite remote sensing image, and the training data is a topography image of a training field, and the method is characterized by comprising the following steps:
Taking the satellite remote sensing image and the topographic image as original images, acquiring pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
And respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a security level for each storage area, and carrying out security verification with the security level of the user, wherein the image blocks in the storage areas can be extracted after passing.
2. The method for protecting satellite intelligence and training data warehouse network as claimed in claim 1, wherein the image cutting model comprises:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,/>For the length of the image block,/>For the original image at coordinates/>Pixel value at/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>For the original image at coordinates/>An image correction function at.
3. The method of claim 2, wherein the offset is on the horizontal axis of the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
4. The method of claim 2, wherein the offset is on the horizontal axis of the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
5. The method for protecting satellite intelligence and training data warehouse network as claimed in claim 2, wherein the original image is at coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
6. A satellite intelligence and training data warehouse network safety protection system, the satellite intelligence is satellite remote sensing image, the training data is topography image of training field, characterized in that includes:
The image acquisition module is used for taking the satellite remote sensing image and the topographic image as original images, acquiring pixels of the original images, setting an image cutting model, cutting the original images according to the length and the height of the pixels of the original images and preset cut image blocks, and generating a plurality of cut image blocks and pixel values of each image block;
And the safety module is used for respectively storing the cut image blocks in a plurality of storage areas of the cloud, setting a safety level for each storage area, carrying out safety verification with the safety level of a user, and extracting the image blocks in the storage areas after the safety verification is passed.
7. The satellite intelligence and training data warehouse network security system as claimed in claim 6, wherein the image cutting model comprises:
，
Wherein, For the cut image block at coordinates/>Pixel value at/>For the width of the image block,/>For the length of the image block,/>For the original image at coordinates/>Pixel value at/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Interpolation function of/>To offset/>, on the horizontal axis of the original imageVertical axis offset/>Adaptive weights of/>For the original image at coordinates/>An image correction function at.
8. The satellite intelligence and training data warehouse network security system as claimed in claim 7, wherein the horizontal axis offset in the original imageVertical axis offset/>Interpolation function/>Comprising the following steps:
，
Wherein, Is a control factor for the interpolated shape.
9. The satellite intelligence and training data warehouse network security system as claimed in claim 7, wherein the horizontal axis offset in the original imageVertical axis offset/>Adaptive weights/>Comprising the following steps:
，
Wherein, For the original image at coordinates/>A gradient is provided at the point of the gradient,For the original image at coordinates/>Gradient at/>As an adjustment factor for adjusting the width of the weight distribution,/>For another horizontal axis offset,/>Is another vertical axis offset.
10. The satellite intelligence and training data warehouse network security system as claimed in claim 7, wherein the original image is at coordinatesImage correction function at/>Comprising the following steps:
，
Wherein, Is an adjustment factor for controlling the degree of correction of the image.
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