CN117992992B - Extensible satellite information data cloud platform safe storage method and system - Google Patents
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Abstract
The invention discloses a safe storage method and a safe storage system for an extensible satellite information data cloud platform, wherein the method comprises the following steps: extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, and respectively storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform; acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching the plurality of satellite remote sensing image blocks according to color values of pixels, and mapping the satellite remote sensing image blocks to satellite remote sensing images with the feature stitching; setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
Description
Technical Field
The invention belongs to the technical field of satellite information secure storage, and particularly relates to an expandable satellite information data cloud platform secure storage method and system.
Background
Image stitching is the process of combining multiple images into one larger image. This process has wide application in the fields of computer vision, photography, geographic Information Systems (GIS), and the like. The following are some current state of the art and common methods of image stitching:
Panorama-based method: panorama stitching: this approach typically uses panoramic cameras or by taking multiple images and then stitching them into one panorama using panorama stitching software (e.g., photomerge functions in Adobe Photoshop).
The deep learning method comprises the following steps: convolutional Neural Network (CNN): the deep learning approach has also met with some success in image stitching. CNNs can learn features in images and provide satisfactory results in image stitching tasks.
Generating a countermeasure network (GAN): GAN can generate realistic images and thus can be used to generate missing parts, thereby achieving image stitching.
However, the image stitching technology in the prior art does not consider the problem of data security, and the stitching precision is not ideal.
Disclosure of Invention
In order to solve the technical problems, the invention provides an extensible satellite information data cloud platform safe storage method, which comprises the following steps:
Extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, respectively storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform, and expanding the cloud platform according to the satellite remote sensing image blocks;
Acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching the plurality of satellite remote sensing image blocks according to color values of pixels, and mapping the satellite remote sensing image blocks to satellite remote sensing images with the feature stitching;
Setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
Further, the satellite remote sensing image stitching model based on feature classification comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image.
Further, the satellite remote sensing image stitching model based on color comprises:
，
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a).
Further, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient.
Further, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant.
The invention also provides an extensible satellite information data cloud platform safe storage system, which comprises:
The cutting module is used for extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, respectively storing the plurality of satellite remote sensing image blocks in a plurality of areas of the cloud platform, and expanding the cloud platform according to the satellite remote sensing image blocks;
The splicing module is used for acquiring the feature classification of each position in the satellite remote sensing image blocks, setting a satellite remote sensing image splicing model based on the feature classification, splicing images belonging to the same feature classification in the plurality of satellite remote sensing image blocks, setting a satellite remote sensing image splicing model based on colors, splicing the plurality of satellite remote sensing image blocks according to the color values of pixels, and mapping the satellite remote sensing image blocks to the satellite remote sensing images with the feature splicing;
The security module is used for setting the user security level, distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
Further, the satellite remote sensing image stitching model based on feature classification comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image.
Further, the satellite remote sensing image stitching model based on color comprises:
，
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a).
Further, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient.
Further, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
The method comprises the steps of extracting satellite remote sensing images in satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, and storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform respectively; acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching the plurality of satellite remote sensing image blocks according to color values of pixels, and mapping the satellite remote sensing image blocks to satellite remote sensing images with the feature stitching; setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is. According to the technical scheme, satellite information data can be spliced, the user security level is set, and the number which can be spliced is distributed for users with different security levels, so that the aim of data security is achieved.
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 a user 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 secure storage method for an extensible satellite information data cloud platform, including:
Step 101, extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, respectively storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform, and expanding the cloud platform according to the satellite remote sensing image blocks;
Step 102, acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching the plurality of satellite remote sensing image blocks according to pixel color values, and mapping the satellite remote sensing image blocks to satellite remote sensing images with the feature stitching;
specifically, the satellite remote sensing image stitching model based on feature classification comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image.
Specifically, the satellite remote sensing image stitching model based on color comprises:
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a).
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient.
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant.
And 103, setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
Example 2
As shown in fig. 2, the embodiment of the present invention further provides an expandable satellite information data cloud platform secure storage system, including:
The cutting module is used for extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, respectively storing the plurality of satellite remote sensing image blocks in a plurality of areas of the cloud platform, and expanding the cloud platform according to the satellite remote sensing image blocks;
The splicing module is used for acquiring the feature classification of each position in the satellite remote sensing image blocks, setting a satellite remote sensing image splicing model based on the feature classification, splicing images belonging to the same feature classification in the plurality of satellite remote sensing image blocks, setting a satellite remote sensing image splicing model based on colors, splicing the plurality of satellite remote sensing image blocks according to the color values of pixels, and mapping the satellite remote sensing image blocks to the satellite remote sensing images with the feature splicing;
specifically, the satellite remote sensing image stitching model based on feature classification comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image.
Specifically, the satellite remote sensing image stitching model based on color comprises:
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a).
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient.
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant.
The security module is used for setting the user security level, distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
Example 3
The embodiment of the invention also provides a storage medium which stores a plurality of instructions for realizing the expandable satellite information data cloud platform safe storage method.
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, extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, and respectively storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform;
Step 102, acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching the plurality of satellite remote sensing image blocks according to pixel color values, and mapping the satellite remote sensing image blocks to satellite remote sensing images with the feature stitching;
specifically, the satellite remote sensing image stitching model based on feature classification comprises:
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image.
Specifically, the satellite remote sensing image stitching model based on color comprises:
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a).
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient.
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant.
And 103, setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
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 an extensible satellite information data cloud platform safe storage method.
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 an expandable satellite information data cloud platform safe storage method in the embodiment of the invention, 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, namely the expandable satellite information data cloud platform safe storage 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, extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, and respectively storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform;
Step 102, acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching the plurality of satellite remote sensing image blocks according to pixel color values, and mapping the satellite remote sensing image blocks to satellite remote sensing images with the feature stitching;
specifically, the satellite remote sensing image stitching model based on feature classification comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image.
Specifically, the satellite remote sensing image stitching model based on color comprises:
，
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a).
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient.
Specifically, satellite remote sensing image blockIn coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant.
And 103, setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
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 (2)
1. An extensible satellite intelligence data cloud platform secure storage method is characterized by comprising the following steps:
Extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, respectively storing the satellite remote sensing image blocks in a plurality of areas of a cloud platform, and expanding the cloud platform according to the satellite remote sensing image blocks;
Acquiring feature classification of each position in a satellite remote sensing image block, setting a satellite remote sensing image stitching model based on the feature classification, stitching images belonging to the same feature classification in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image stitching model based on color, stitching a plurality of satellite remote sensing image blocks according to color values of pixels, and mapping the satellite remote sensing image stitching model to a satellite remote sensing image with the feature stitching, wherein the satellite remote sensing image stitching model based on the feature classification comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstClassifying pixel values of the image by the features;
the satellite remote sensing image stitching model based on the color comprises the following steps:
，
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a);
Satellite remote sensing image block In coordinates ofColor value of pixelThe processing functions of (1) include:
，
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient;
Satellite remote sensing image block In coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant;
Setting a user security level, and distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
2. An expandable satellite intelligence data cloud platform secure storage system, comprising:
The cutting module is used for extracting satellite remote sensing images in the satellite information data, cutting the satellite remote sensing images to generate a plurality of satellite remote sensing image blocks, respectively storing the plurality of satellite remote sensing image blocks in a plurality of areas of the cloud platform, and expanding the cloud platform according to the satellite remote sensing image blocks;
The system comprises a splicing module, a characteristic classification module and a characteristic classification module, wherein the characteristic classification module is used for acquiring characteristic classifications of each position in a satellite remote sensing image block, setting a satellite remote sensing image splicing model based on the characteristic classifications, splicing images belonging to the same characteristic classifications in a plurality of satellite remote sensing image blocks, setting a satellite remote sensing image splicing model based on colors, splicing the plurality of satellite remote sensing image blocks according to pixel color values, and mapping the satellite remote sensing image blocks onto satellite remote sensing images with the characteristic classifications, wherein the satellite remote sensing image splicing model based on the characteristic classifications comprises:
，
Wherein, Is in coordinatesThe department belongs to the firstThe image of each feature class completes the pixel value after feature stitching,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For satellite remote sensing image blocksMiddle in coordinatesThe department belongs to the firstThe gradient of pixel values for each feature class,For a gradient adjustment factor for controlling gradient similarity,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstThe individual features classify the pixel values of the image,For satellite remote sensing image blocksIn coordinates ofThe department belongs to the firstClassifying pixel values of the image by the features;
the satellite remote sensing image stitching model based on the color comprises the following steps:
,
Wherein, Is in coordinatesThe color value of the pixel after the color stitching is completed,In order to adjust the weight of the weight,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the processing function of (a),For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs a processing function of (a);
Satellite remote sensing image block In coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
,
Wherein, Is the direction of the color gradient,For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksAn adjustment factor for the color gradient;
Satellite remote sensing image block In coordinates ofColor value of pixelIs a processing function of (2)Comprising the following steps:
，
Wherein, For satellite remote sensing image blocksIn coordinates ofColor value of pixelIs used for the gradient of (a),For satellite remote sensing image blocksThe average value of the color values is calculated,For satellite remote sensing image blocksThe adjustment factor of the color gradient is set,Is a positive constant;
The security module is used for setting the user security level, distributing the number of blocks of the satellite remote sensing image blocks which can be spliced to the user according to the user security level, wherein the higher the user security level is, the more the number of blocks of the satellite remote sensing image blocks which can be spliced is.
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