CN113032604B - Remote sensing image processing method and device, electronic equipment and storage medium - Google Patents
Remote sensing image processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a method and a device for processing remote sensing images, electronic equipment and a storage medium, and relates to the technical field of image processing. The method comprises the steps of receiving script codes written by a user and an interesting area of an original image appointed by the user; generating a syntax tree according to the script codes; partitioning the region of interest by using a partitioning algorithm to obtain row and column number hierarchical parameters of the tiles; obtaining an image block by utilizing the row-column number hierarchical parameters of the tiles; and executing the syntax tree to calculate the image block and obtain a calculation result, wherein in the method, a user can define an operator by himself, and the remote sensing image processing, analysis and visualization which can be programmed on line are realized, thereby solving the problem that the real-time block parallel calculation can not be carried out by taking a file as input in the existing method.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to a method and an apparatus for processing a remote sensing image, an electronic device, and a storage medium.
Background
The existing remote sensing image processing method generally adopts a data processing tool set mode, processing software carries out function expansion through a reserved plug-in interface, and the processing capacity of the processing software is limited by the types of plug-ins in a plug-in library. And the remote sensing data processing and analyzing algorithm is packaged into a basic interface and deployed at a server, a user writes a script through a webpage end and calls a server execution program to realize processing and analysis, but the user cannot insert a custom algorithm.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for processing a remote sensing image, an electronic device, and a storage medium, which enable a user to customize an operator and implement real-time processing and analysis of an online programmable remote sensing image, thereby solving a problem that a real-time block parallel computation cannot be performed by using a file as an input in the existing method.
The embodiment of the application provides a remote sensing image processing method, which comprises the following steps:
receiving script codes written by a user and an interesting area of an original image appointed by the user;
generating a syntax tree according to the script codes;
partitioning the region of interest by using a partitioning algorithm to obtain row and column number hierarchical parameters of tiles;
obtaining an image block by utilizing the row-column number hierarchical parameters of the tiles;
and executing the syntax tree to calculate the image block and obtain a calculation result.
In the implementation process, real-time analysis, processing and visual display can be realized through chain type calculation, and the existing algorithm or user-defined algorithm (script code input by a user) in an algorithm library can be inserted into any calculation link through a flexible and elastic calculation process, so that the remote sensing image processing, analysis and visual display capable of being programmed on line can be realized, and the problem that the block parallel calculation cannot be carried out by taking a file as input in the existing method is solved.
Further, the generating a syntax tree according to the script code includes:
constructing a corresponding sub-syntax tree by using the function type, name and parameter information of the operator function;
and taking the sub-syntax tree of the previous operator function as an input parameter of the next operator function according to the operator function chain calling sequence to construct the syntax tree of the script code.
In the implementation process, the syntax tree is generated by compiling the script code written by the user, so that the background can analyze and execute the syntax tree conveniently.
Further, the partitioning the region of interest by using a partitioning algorithm to obtain a tile rank number hierarchical parameter includes:
calculating the image resolution of the original image;
obtaining a closest level of the image resolution from a globally subdivided level based on tile resolution;
calculating the range of tile row-column numbers of the closest hierarchy.
In the implementation process, the block calculation of the original image is realized by calculating the range of the row number and the column number of the n-th-level tile.
Further, said calculating a range of tile row-column numbers for the closest hierarchy includes:
calculating the geographical range of the original image, converting the geographical range of the original image into a projection range under a web mercator reference system, and calculating the projection coordinates of the angular points to obtain a corresponding coordinate range;
calculating the projection width and the tile resolution of a single tile;
and calculating a tile row and column number range according to the projection width and the tile resolution.
In the implementation process, the corresponding coordinate ranges of the four corner points of the original image are calculated according to the projection coordinates of the four corner points, so that the tile row-column number range of the tile at the nth level is calculated according to the coordinate ranges.
Further, obtaining an image block using tile row and column number level parameters, comprising:
and searching in the original image by using the tile row and column number level parameters to obtain a corresponding image block.
In the implementation process, the corresponding image block data can be acquired from the cloud storage through the row and column number hierarchical information, and the corresponding image block can be acquired according to the row and column number hierarchical information because the partitioned row and column number hierarchical information is acquired by partitioning the region of interest of the user in advance.
Further, the invoking an existing algorithm or a user-defined algorithm to calculate the image block to obtain a calculation result includes:
calling an existing algorithm or analyzing the syntax tree to form a user requirement algorithm;
and performing chain processing on the image blocks by using the user demand algorithm.
In the implementation process, the algorithm required by the user is combined by calling the algorithm library algorithm or the function expressions of various remote sensing algorithms, and then the remote sensing image is calculated, analyzed and the result is output and displayed.
The embodiment of the present application further provides a remote sensing image processing apparatus, the apparatus includes:
the receiving module is used for receiving script codes written by a user and an interesting area of an original image appointed by the user;
the syntax tree module is used for generating a syntax tree according to the script code;
the blocking module is used for blocking the region of interest by using a blocking algorithm to obtain a tile rank number hierarchical parameter;
the image block acquisition module is used for acquiring an image block by utilizing the row-column number level parameters of the tiles;
and the computing module is used for executing the syntax tree to compute the image block and obtain a computing result.
In the implementation process, real-time analysis, processing and visual display can be realized through chain type calculation, and the existing algorithm or user-defined algorithm of an algorithm library can be inserted into any calculation link through a flexible and elastic calculation process, so that the remote sensing image processing, analysis and visual display capable of being programmed on line can be realized, and the problem that the block parallel calculation cannot be carried out by taking a file as input in the conventional method is solved.
Further, the syntax tree module includes:
the construction module is used for constructing a corresponding sub-syntax tree by utilizing the function type, the name and the parameter information of the operator function;
and the syntax tree construction module is used for taking the sub-syntax tree of the previous operator function as the input parameter of the next operator function according to the operator function chain calling sequence so as to construct the syntax tree of the script code.
In the implementation process, the syntax tree is generated by compiling the script code written by the user, so that the background can analyze and execute the syntax tree conveniently.
An embodiment of the present application further provides an electronic device, where the electronic device includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute any one of the remote sensing image processing methods described above.
An embodiment of the present application further provides a readable storage medium, where computer program instructions are stored, and when the computer program instructions are read and executed by a processor, the method for processing remote sensing images according to any one of the foregoing embodiments is executed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a flowchart of a method for processing a remote sensing image according to an embodiment of the present disclosure;
fig. 2 is a specific flowchart of a remote sensing image processing method capable of being programmed on line according to an embodiment of the present application;
FIG. 3 is a flow chart of generating a syntax tree according to an embodiment of the present application;
FIG. 4 is a flow chart of a grid construction function generating syntax tree according to an embodiment of the present application;
FIG. 5 is a flow chart of generating a syntax tree for a multiplication function according to an embodiment of the present application;
FIG. 6 is a flowchart of obtaining tile row and column number level parameters according to an embodiment of the present application;
FIG. 7 is a flow chart of a tile pyramid construction provided by an embodiment of the present application;
FIG. 8 is a flowchart of the calculation of a range of tile row and column numbers near the hierarchy according to an embodiment of the present application;
fig. 9 is a flowchart for computing an image block according to an embodiment of the present application;
FIG. 10 is a flowchart of a computing method for an insert operator in any computing process according to an embodiment of the present disclosure;
FIG. 11 is a flowchart of a process for estimating chlorophyll level in Taihu lake region according to the algorithm provided in the embodiments of the present application;
fig. 12 is a block diagram illustrating a configuration of a remote sensing image processing apparatus according to an embodiment of the present disclosure;
fig. 13 is a block diagram illustrating an overall configuration of a remote sensing image processing apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
Referring to fig. 1, fig. 1 is a flowchart of a method for processing a remote sensing image according to an embodiment of the present disclosure. The method is an online programmable remote sensing image processing method, and specifically comprises the following steps:
step S100: receiving script codes written by a user and an interesting area of an original image appointed by the user;
the original image is stored in the cloud, and a user can obtain a data range needing to be processed by specifying the region of interest.
Step S200: generating a syntax tree according to the script codes;
as shown in fig. 2, a specific flowchart of the method for processing remotely sensed images that can be programmed online is shown. The compiling process of the script code is to construct a syntax tree which is a language-independent syntax tree in the JSON format through a chain calling process. As shown in fig. 3, a flowchart for generating a syntax tree specifically includes the following steps:
step S201: constructing a corresponding sub-syntax tree by using the function type, name and parameter information of the operator function;
step S202: and taking the sub-syntax tree of the previous operator function as an input parameter of the next operator function according to the operator function chain calling sequence to construct the syntax tree of the script code.
Illustratively, taking a multiplication function in grid calculation as an example, the function is composed of a grid construction function and a multiplication function, wherein a syntax tree of the grid construction function is composed of a function type, a function name and a parameter, and the multiplication function is composed of a function type, a function name and a parameter.
As shown in FIG. 4, a flow diagram for generating a syntax tree for a trellis construction function. As shown in fig. 5, a flow diagram for generating a syntax tree for a multiplication function. The multiplication function comprises two parameters of P1 and P2, wherein P1 is from the grid construction function, and P2 is the parameter of the multiplication function; taking the grid structure function syntax tree as an input parameter P1 of the multiplication function, and generating the multiplication function syntax tree by combining the function type, name and parameter P2 of the multiplication function; the resulting syntax tree is passed in the form of a JSON string, where the syntax tree stores the function type, name and parameters.
Step S300: partitioning the region of interest by using a partitioning algorithm to obtain row and column number hierarchical parameters of tiles;
as shown in fig. 6, a flowchart for obtaining tile row and column number hierarchical parameters specifically includes the following steps:
step S310: calculating the image resolution of the original image;
step S320: obtaining a closest level of the image resolution from a globally subdivided level based on tile resolution;
step S330: calculating the range of tile row-column numbers of the closest hierarchy.
Tile resolution is determined by tile level, tile size. The tile size is typically 256 x 256 pixels, and the nth level tile resolution is the perimeter of the earth divided by (2)nX 256) of the tile pyramid, as shown in fig. 7, is a flow chart for constructing the tile pyramid.
As shown in fig. 8, a flowchart for calculating a tile row-column number range close to a hierarchy may specifically include the following steps:
step S331: calculating the geographical range of the original image, converting the geographical range of the original image into a projection range under a web mercator reference system, and calculating the projection coordinates of the angular points to obtain a corresponding coordinate range;
step S332: calculating the projection width and the tile resolution of a single tile;
dividing the perimeter of the earth by the n power of 2 to obtain the projection width of the nth-level tile; the tile projection width is divided by 256 to obtain an nth level of tile resolution.
Step S333: and calculating a tile row and column number range according to the projection width and the tile resolution.
The coordinates of the projection starting point of the web mercator map are (-20037508.342789243, 20037508.342789243), the coordinates of a certain point of the map are assumed to be (x, y), the line number of the point is (x- (-20037508.342789243) + tile resolution)/tile projection width, and the result is rounded downwards; similarly, the column number of the point is (y-20037508.342789243+ tile resolution)/tile projection width, and the result is rounded down. And respectively carrying out the calculation on the geographic coordinate ranges of the 4 points of the tile to obtain the numerical results of the starting row, the ending row, the starting column and the ending column of the tile.
Step S400: obtaining an image block by utilizing the row-column number hierarchical parameters of the tiles;
transmitting the syntax tree in the JSON format to a back end for analysis through a dynamic backtracking process, taking the hierarchical information of the row and column numbers of the tiles as parameter execution codes by the back end, and returning an operation result:
specifically, configuration information of each server in the cluster is obtained, the memory and other configuration information of each server are determined, and calculation tasks are reasonably distributed according to the complexity of an algorithm; and transmitting the syntax tree to a back end for analysis, executing codes on the distributed computing nodes by the back end by taking the tile row and column number hierarchical information as parameters, and returning an operation result.
And searching in the original image by using the tile row and column number level parameters to obtain the corresponding image block.
Since the original image is divided into a plurality of blocks in advance, each block corresponds to different tile row-column number hierarchical parameters, and therefore the corresponding image block can be found through the tile row-column number hierarchical parameters.
Step S500: and executing the syntax tree to calculate the image block and obtain a calculation result.
As shown in fig. 9, which is a flowchart for calculating an image block, the step may specifically include:
step S501: calling an existing algorithm or analyzing the syntax tree to form a user requirement algorithm;
step S502: and performing chain processing on the image blocks by using the user demand algorithm.
Calling an algorithm library algorithm or function expressions of various remote sensing algorithms, or analyzing the syntax tree to obtain a user-defined algorithm, combining a user demand algorithm, performing calculation analysis on the remote sensing image by using the user demand algorithm, outputting and displaying an analysis result, wherein the calculation result may be various according to different algorithms, for example, if the calculation result is a waveband calculation algorithm, the result is an image pixel block; in case of a statistical algorithm, the calculation result may be a statistical value, as shown in fig. 10, which is a flow chart of a calculation method for an insert operator in any calculation process.
The method solves the problems that the traditional flow arrangement is not flexible, and the block parallel computation cannot be carried out by taking a file as input. The user can process, analyze and visualize the remote sensing image through the self-defined operator, the processing capability is not limited by time and space, and the terminal with any configuration can process the remote sensing data.
The method can perform real-time analysis, processing and visual display through chain calculation, and has flexible and elastic calculation flow.
Exemplarily, as shown in fig. 11, for a processing flow chart of the estimation algorithm for the chlorophyll level in the taihu lake region, firstly, compiling the estimation foot of the chlorophyll in the taihu lake region written by a user, generating a syntax tree in JSON format, transmitting the syntax tree to a back end for parsing, querying and calculating the required image data by the back end through parameters such as an image data set ID, time, region information, attribute information and the like, for example, selecting an image data set from "LC08/01/T1" in the data set "2019-10-01" to "2019-12-01" in time, performing mosaic fusion on the waveband data of "B2, B3 and B4" in the image data set, and adding the mosaic data to a map for display; then, filtering data (screening data of the region of interest input by the user) through a specified region, for example, selecting a Vector data set of "/PersonalGDB/Vector/taihushuiyu.geojson", acquiring a first geometric element object in the set, acquiring a geometric object in the geometric element objects, and filtering an image data set through a geometric object range; data is filtered through attribute information, for example, a filtering condition that a data field value with an attribute of 'cluoudcover' is less than or equal to 5 is constructed, a filtering condition that a data field value with an attribute of 'wrsPath' is equal to 119 is constructed, a filtering condition that a data field value with an attribute of 'wrsRow' is equal to 38 is constructed, and the image data set is filtered through a plurality of constructed query conditions.
And then executing a Taihu chlorophyll estimation algorithm defined by the script, taking the hierarchical information of the tile row and column number as a parameter execution code at the rear end, carrying out block calculation on the image, returning an operation result, such as a self-defined chlorophyll algorithm, selecting 'B4' waveband data and 'B3' waveband data in the image, and returning pixel data divided by the 'B4' waveband and the 'B3' waveband.
And finally, performing region-of-interest clipping by using the Taihu vector boundary, displaying the Taihu chlorophyll estimation result at the front end, for example, acquiring the 0 th image data in the image data set, performing range clipping by using the Taihu area, and displaying according to the region of interest.
Example 2
An embodiment of the present application provides a remote sensing image processing apparatus, as shown in fig. 12, which is a block diagram of the remote sensing image processing apparatus, the apparatus includes:
a receiving module 100, configured to receive a script code written by a user and an area of interest of an original image specified by the user;
a syntax tree module 200 for generating a syntax tree according to the script code;
the blocking module 300 is configured to block the region of interest by using a blocking algorithm to obtain a tile row-column number hierarchical parameter and an image block;
an image block acquisition module 400 for parsing and executing the syntax tree based on the tile row and column number level parameters;
the calculating module 500 is configured to execute the syntax tree to calculate the image block and obtain a calculation result.
As shown in fig. 13, which is a block diagram of the overall structure of the remote sensing image processing apparatus, the syntax tree module 200 includes:
a constructing module 201, configured to construct a corresponding sub-syntax tree by using the function type, name and parameter information of the operator function;
and the syntax tree construction module 202 is configured to use the sub-syntax tree of the previous operator function as an input parameter of the next operator function according to the operator function chain call sequence to construct the syntax tree of the script code.
The blocking module 300 includes:
an image resolution calculation module 310, configured to calculate an image resolution of the original image;
a closest level acquisition module 320 for acquiring a closest level to the image resolution from a global level based on the tile resolution;
a row-column number calculation module 330, configured to calculate the range of tile row-column numbers closest to the hierarchy.
The row and column number calculation module 330 includes:
the coordinate range acquisition module 331 is configured to calculate a geographic range of the original image, convert the geographic range of the original image into a projection range in a web mercator reference system, and calculate projection coordinates of corner points to obtain a corresponding coordinate range;
a tile parameter calculation module 332 for calculating the projection width and the tile resolution of a single tile;
a row and column number range obtaining module 333, configured to calculate a tile row and column number range according to the projection width and the tile resolution.
The calculation module 500 includes:
an algorithm construction module 501, configured to invoke an existing algorithm or parse the syntax tree to form a user requirement algorithm;
a result obtaining module 502, configured to perform chain processing on the image block by using the user requirement algorithm.
An embodiment of the present application further provides an electronic device, where the electronic device includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the remote sensing image processing method according to embodiment 1.
An embodiment of the present application further provides a readable storage medium, where computer program instructions are stored in the readable storage medium, and when the computer program instructions are read and executed by a processor, the method for processing remote sensing images according to embodiment 1 is executed.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (7)
1. A remote sensing image processing method is characterized by comprising the following steps:
receiving script codes written by a user and an interesting area of an original image appointed by the user;
generating a syntax tree according to the script codes:
constructing a corresponding sub-syntax tree by using the function type, name and parameter information of the operator function;
taking the sub-syntax tree of the previous operator function as an input parameter of the next operator function according to the operator function chain calling sequence to construct a syntax tree of the script code;
partitioning the region of interest by using a partitioning algorithm to obtain row and column number hierarchical parameters of tiles;
obtaining an image block by utilizing the row-column number hierarchical parameters of the tiles;
calling an existing algorithm or analyzing the syntax tree to form a user requirement algorithm;
and performing chain processing on the image blocks by using the user demand algorithm.
2. The remote sensing image processing method according to claim 1, wherein the partitioning the region of interest by using a partitioning algorithm to obtain tile row-column number hierarchical parameters comprises:
calculating the image resolution of the original image;
obtaining a closest level of the image resolution from a globally subdivided level based on tile resolution;
calculating the range of tile row-column numbers of the closest hierarchy.
3. The method of claim 2, wherein the calculating the range of tile row and column numbers closest to the hierarchy comprises:
calculating the geographical range of the original image, converting the geographical range of the original image into a projection range under a web mercator reference system, and calculating the projection coordinates of the angular points to obtain a corresponding coordinate range;
calculating the projection width and the tile resolution of a single tile;
and calculating a tile row and column number range according to the projection width and the tile resolution.
4. The method of claim 1, wherein obtaining the image block using tile row and column number level parameters comprises:
and searching in the original image by using the tile row and column number level parameters to obtain a corresponding image block.
5. A remote sensing image processing apparatus, comprising:
the receiving module is used for receiving script codes written by a user and an interesting area of an original image appointed by the user;
the syntax tree module is used for generating a syntax tree according to the script code;
the syntax tree module includes:
the construction module is used for constructing a corresponding sub-syntax tree by utilizing the function type, the name and the parameter information of the operator function;
the syntax tree construction module is used for taking the sub-syntax tree of the previous operator function as the input parameter of the next operator function according to the operator function chain calling sequence so as to construct the syntax tree of the script code;
the blocking module is used for blocking the region of interest by using a blocking algorithm to obtain a tile rank number hierarchical parameter;
the image block acquisition module is used for acquiring an image block by utilizing the row-column number level parameters of the tiles;
the calculation module is used for calling the existing algorithm or analyzing the syntax tree to form a user requirement algorithm; and performing chain processing on the image blocks by using the user demand algorithm.
6. An electronic device, comprising a memory for storing a computer program and a processor for executing the computer program to cause the electronic device to perform the remote sensing image processing method according to any one of claims 1 to 4.
7. A readable storage medium, wherein computer program instructions are stored in the readable storage medium, and when the computer program instructions are read and executed by a processor, the method for processing remote sensing images according to any one of claims 1 to 4 is performed.
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| CN110347499B (en) * | 2019-06-13 | 2021-04-16 | 武汉大学 | Method for generating and deploying remote sensing image tiles in real time |
| CN110555119B (en) * | 2019-08-27 | 2022-05-13 | 成都数之联科技股份有限公司 | Unmanned aerial vehicle remote sensing image slicing method and system under real-time scene |
| CN110908640B (en) * | 2019-11-26 | 2022-06-07 | 京东科技控股股份有限公司 | Method for realizing service function and script engine |
| CN111159325B (en) * | 2019-12-31 | 2023-12-19 | 清华大学 | Distributed map slicing method, device, storage medium and server |
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