Method and device for reducing geometry precision of dom data, equipment and storage medium

Abstract

The application provides a DOM data geometric accuracy reduction method, device, equipment and storage medium. It relates to the technical field of geographic data processing. The method comprises the following steps: adding an amplitude factor, a period factor and an error control factor in a hyperbolic exponential composite function, constructing a geometric accuracy reduction function and establishing a geometric accuracy reduction model; selecting a range control point from DOM data, inputting the coordinates of the range control point into the geometric accuracy reduction model, calculating a mean error, and if the mean error does not meet a preset geometric reduction scale, adjusting the error control factor in the geometric reduction model and using the geometric accuracy reduction model with the adjusted error control factor until the mean error meets the preset geometric reduction scale, so that an updated geometric accuracy reduction model is obtained. The application can overcome the significant limitations of the traditional vector data geometric accuracy reduction method in terms of grid data structure adaptability, spatial correlation preservation and continuous data continuity.

Description

Technical Field

[0001] This application relates to the field of geographic data processing technology, and in particular to a method, apparatus, device and storage medium for reducing the geometric precision of DOM data. Background Technology

[0002] As a fundamental geographic information resource, DOM data plays an irreplaceable role in promoting the development of the digital economy and serving the modernization of social governance. However, against the backdrop of rapid digital economic development, a contradiction has arisen between the demand for open sharing of DOM data and geographic information security. The emergence of geometric precision reduction technology has made the public sharing of high-precision DOM data possible. Geometric precision reduction technology refers to reducing the spatial location precision of data through mathematical transformations, transforming high-precision data into low-precision data or processing it into publicly available data. Geometric precision reduction methods can be mainly divided into three categories: linear transformation algorithms, nonlinear transformation algorithms, and combined transformation algorithms. Linear transformations include similarity transformations, affine transformations, and projective transformations, which can efficiently perform geometric correction of data. Nonlinear transformations are mainly used for geometric precision reduction in two ways: the first is to directly use mathematical functions to reduce the geometric precision of the data, mainly trigonometric functions and projection transformations. The second is to use control points in the data, fit these control points to solve for model parameters, use the solved parameters to derive a geometric precision reduction model, and use this model for geometric precision reduction. The models used here mainly include polynomial models, rational functions, and radial basis functions. Combined transformation algorithms are categorized into combinations of linear and nonlinear transformations, and combinations of nonlinear and nonlinear transformations. By combining the advantages of both types of transformations, the processed data possesses both usability and security. Current related technologies mainly focus on vector data, with little research in the field of DOM data. Therefore, there is an urgent need for a method to reduce the geometric precision of DOM data, which is of significant practical importance for improving the geographic information security protection system. Summary of the Invention

[0003] This application provides a method, apparatus, device, and storage medium for reducing the geometric precision of DOM data, in order to overcome the significant limitations of traditional vector data geometric precision reduction methods in terms of raster data structure adaptability, spatial correlation preservation, and continuity of sectional data.

[0004] In a first aspect, this application provides a method for reducing the geometric precision of DOM data, including:

[0005] By adding amplitude factor, period factor and error control factor to the hyperbolic exponential composite function, a function with reduced geometric accuracy is constructed.

[0006] Based on the aforementioned geometric accuracy reduction function, a geometric accuracy reduction model is established;

[0007] Obtain DOM data, select range control points from the DOM data, input the coordinates of the range control points into the geometric precision reduction model, calculate the mean square error, if the mean square error does not meet the preset geometric precision reduction scale, adjust the error control factor in the geometric precision reduction model and update the geometric precision reduction model using the adjusted error control factor, reselect range control points and input the coordinates of the range control points into the updated geometric precision reduction model, calculate the mean square error, until the mean square error meets the preset geometric precision reduction scale, and obtain the updated geometric precision reduction model;

[0008] The coordinates of the DOM data are input into the updated geometric precision reduction model to obtain the DOM data with reduced geometric precision.

[0009] In one possible design, the hyperbolic exponential composite function is expressed as:

[0010] ;

[0011] In the formula, f ( sinx ) represents the expression for the hyperbolic exponential composite function. e Represents the natural constant. x The x-coordinate of the DOM data before the reduction in geometric precision.

[0012] In one possible design, the geometric accuracy reduction function is expressed as:

[0013] ;

[0014] In the formula, f ( bsincx ) represents the expression for the geometric precision reduction function. b The amplitude factor representing the horizontal axis. c The composite factor representing the horizontal axis. a This represents the error control factor on the horizontal axis. x The x-coordinate of the DOM data before the reduction in geometric precision. e Represents the natural constant.

[0015] In one possible design, the geometric accuracy reduction model is represented as:

[0016] ;

[0017] In the formula, and These represent the x and y coordinates of the DOM data after the reduction in geometric precision. x and y The x-coordinate of the DOM data before the reduction in geometric precision.b and b 1 represents the amplitude factor of the horizontal and vertical axes, respectively. c and c 1 represents the composite factor of the horizontal and vertical axes, respectively. a and a 1 represents the error control factor for the horizontal and vertical axes, respectively. e Represents the natural constant.

[0018] In one possible design, the range control points are selected from the DOM data in the following manner:

[0019] Based on the map area range of the DOM data, map area control points are selected evenly from left to right and top to bottom according to the spacing of each row.

[0020] In one possible design, if the mean square error does not meet the preset geometric reduction scale, the error control factor in the geometric reduction model is adjusted using the following formula:

[0021] ;

[0022] In the formula, a This represents the error control factor on the horizontal axis. D This indicates the preset geometric reduction scale. RMSE xy The two-dimensional root mean square error of the range control points.

[0023] In one possible design, the coordinates of the DOM data can be obtained in the following ways:

[0024] The pixel coordinates are obtained by performing coordinate transformation on the pixel row and column numbers of the DOM data;

[0025] The pixel coordinates are converted into projection coordinates, and the projection coordinates are used as the coordinates of the DOM data.

[0026] Secondly, this application provides a DOM data geometric precision reduction apparatus, the apparatus comprising:

[0027] The composite function construction module is configured to add amplitude factors, period factors, and error control factors to hyperbolic exponential composite functions to construct functions with reduced geometric accuracy.

[0028] The model building module is configured to build a geometrically reduced model based on the geometrically reduced function.

[0029] The model update module is configured to acquire DOM data, select range control points from the DOM data, input the coordinates of the range control points into the geometric precision reduction model, calculate the mean square error, and if the mean square error does not meet the preset geometric precision reduction scale, adjust the error control factor in the geometric precision reduction model and update the geometric precision reduction model using the adjusted error control factor, reselect range control points and input the coordinates of the range control points into the updated geometric precision reduction model, calculate the mean square error, until the mean square error meets the preset geometric precision reduction scale, and obtain the updated geometric precision reduction model;

[0030] The precision reduction module is configured to input the coordinates of the DOM data into the updated geometric precision reduction model to obtain the DOM data with reduced geometric precision.

[0031] Thirdly, embodiments of this application provide an electronic device, including: at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, causing the at least one processor to perform the DOM data geometry precision reduction method as described in the first aspect and various possible designs of the first aspect.

[0032] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions. When a processor executes the computer-executable instructions, it implements the DOM data geometric precision reduction method described in the first aspect and various possible designs of the first aspect.

[0033] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the DOM data geometric precision reduction method described in the first aspect and various possible designs of the first aspect.

[0034] The method, apparatus, device, and storage medium for reducing the geometric precision of DOM data provided in this application have at least the following beneficial effects:

[0035] This application considers the data characteristics of DOM data and the specific requirements for geometric precision reduction. It integrates the asymptotic properties of hyperbolic exponential functions with the nonlinear characteristics of trigonometric functions, proposing a combined hyperbolic exponential and trigonometric function geometric precision reduction method. By further incorporating amplitude, period, and error control factors, controllable geometric precision reduction is achieved. Experiments show that the proposed method, while ensuring the controllability of DOM data, possesses good usability and high security, meeting the requirements for geometric precision reduction of DOM data. Attached Figure Description

[0036] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0037] Figure 1 A flowchart illustrating a method for reducing the geometric precision of DOM data provided in this application embodiment;

[0038] Figure 2 These are schematic diagrams of different amplitude parameters provided in the embodiments of this application;

[0039] Figure 3 These are schematic diagrams of different periodic function images provided in embodiments of this application;

[0040] Figure 4 This is a schematic diagram illustrating the basic information of the experimental data provided in the embodiments of this application;

[0041] Figure 5 Usability analysis diagram of data A, data B, and data C after reduced geometric accuracy provided in the embodiments of this application;

[0042] Figure 6 This is a structural diagram of the DOM data geometric accuracy reduction device provided in an embodiment of this application.

[0043] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0044] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0045] The collection, storage, use, processing, transmission, provision, and disclosure of financial data or user data involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0046] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0047] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0048] High-precision digital orthophoto map (DOM) data is widely used in land surveying and urban planning. DOM data not only possesses significant spatial positioning capabilities but also exhibits characteristics such as large data volume and fragmented storage. However, high-precision DOM data is classified as confidential data and requires geometric precision reduction techniques before public use. Existing technologies mostly focus on geometric precision reduction algorithms for vector data, with few reports on methods specifically for DOM data geometric precision reduction. Traditional vector data geometric precision reduction methods have significant limitations in terms of raster data structure adaptability, spatial correlation preservation, and fragmented data continuity. Therefore, there is an urgent need to establish a geometric precision reduction scheme that integrates the spatial characteristics of DOM data with the features of raster data to meet the needs of public sharing of DOM data.

[0049] Based on this, this application provides a method for reducing the geometric precision of DOM data. This method constructs a hyperbolic exponential composite function by combining the asymptotic properties of the hyperbolic exponential function and the periodicity of trigonometric functions. Furthermore, by adding amplitude, period, and error control factors, the precision of the function is controlled, thus constructing a geometric precision reduction model with controllable accuracy. Experiments demonstrate that this algorithm has good controllability, usability, and security, providing an effective means for the secure and public sharing of DOM data.

[0050] Specifically, such as Figure 1 The diagram shows a flowchart of a method for reducing the geometric precision of DOM data provided in an embodiment of this application. The method for reducing the geometric precision of DOM data includes the following steps S100-S400.

[0051] S100: By adding amplitude factor, period factor and error control factor to the hyperbolic exponential composite function, a function with reduced geometric accuracy is constructed.

[0052] In this embodiment, the expression of the hyperbolic exponential composite function is shown in formula (1):

[0053] (1);

[0054] In the formula, f ( sinx ) represents the expression for the hyperbolic exponential composite function. e Represents the natural constant. xThe x-coordinate of the DOM data before the reduction in geometric precision.

[0055] The main characteristics of this hyperbolic exponential composite function are as follows:

[0056] (1) Boundedness. The range of the hyperbolic exponential function is bounded, which satisfies the requirement of error controllability in the geometric precision reduction process.

[0057] (2) Continuity. Within the domain, the function changes continuously, preventing abrupt changes in some coordinate positions that could lead to data mutations during geometric precision reduction processing, thus further ensuring data availability. These characteristics meet the requirements of continuous smoothness and controllable precision for DOM data geometric precision reduction, making the selection of the hyperbolic exponential function as the geometric precision reduction algorithm feasible.

[0058] Geometric accuracy reduction is measured by the mean square error. In hyperbolic exponential composite functions, error control can be achieved by adding parameters to bring the mean square error up to the required level for geometric accuracy reduction. To further control the amplitude and period of the transformation, amplitude and period parameters are added to meet the accuracy requirements of geometric accuracy reduction processing.

[0059] Based on the above analysis and function properties, the geometric accuracy reduction function is constructed by adding amplitude factor, period factor and error control factor respectively, as shown in formula (2):

[0060] (2);

[0061] In the formula, f ( bsincx ) represents the expression for the geometric precision reduction function. b The amplitude factor representing the horizontal axis. c The composite factor representing the horizontal axis. a This represents the error control factor on the horizontal axis. x The x-coordinate of the DOM data before the reduction in geometric precision. e Represents the natural constant.

[0062] When using trigonometric functions (i.e., geometrically reduced functions) for composition, either sine or cosine functions can be used. The following example uses the geometrically reduced method of sine function composition.

[0063] In period parameter When the composite factor of the horizontal axis remains constant, the graphs of the function with different amplitudes are as follows: Figure 2 As shown, in its amplitude parameters When the amplitude factor of the horizontal axis remains constant, the graphs of the function with different periods are as follows: Figure 3 As shown.

[0064] As can be seen from the image, in the period parameter When the amplitude parameter is set unchanged The larger the value, the more severe the function jitter; an excessively large value... The parameters can cause drastic changes in the function, and these drastic changes can significantly impact the usability of DOM data. Therefore, it is necessary to set a reasonable amplitude parameter. .

[0065] In amplitude parameters Under the condition that it remains unchanged, the period parameter The larger the period, the shorter the function's period will become. However, an excessively short period can also cause drastic changes in data coordinates. Therefore, the period should be set according to the map's area. The period calculation formula is:

[0066] (3);

[0067] parameter The period value of the function should be reasonably selected based on the map size range of the DOM data. A period value that is too large or too small will affect the geometric precision of the DOM data and reduce the processing effect.

[0068] During the process of reducing geometric accuracy, it is necessary to continuously control the iteration parameters so that the mean error can meet the scale requirements of the geometric accuracy reduction process.

[0069] S200: Based on the hyperbolic exponential composite function, a model with reduced geometric accuracy is established.

[0070] Based on the hyperbolic exponential function composite strategy and precision control, this embodiment uses hyperbolic exponential composite trigonometric functions to establish an initial algorithm for reducing the geometric precision of DOM data. Let the coordinates before geometric precision reduction be... and After transformation, the coordinates are and The expression for the geometric accuracy reduction model based on the hyperbolic exponential composite function is shown in (4):

[0071] (4);

[0072] In the formula, and These represent the x and y coordinates of the DOM data after the reduction in geometric precision. x and y The x-coordinate of the DOM data before the reduction in geometric precision. b and b 1 represents the amplitude factor of the horizontal and vertical axes, respectively. c and c 1 represents the composite factor of the horizontal and vertical axes, respectively. a and a1 represents the error control factor for the horizontal and vertical axes, respectively. e Represents the natural constant.

[0073] The process of establishing a geometric accuracy reduction model based on the hyperbolic exponential composite function includes initializing algorithm parameters, error control, and establishing the geometric accuracy reduction algorithm. Using the input DOM data, the pixel row and column numbers are first transformed into projected coordinates. Then, using the transformed projected coordinates, some control points are selected, and the error control formula is used for iterative calculation to ensure the geometric accuracy reduction model meets the requirements.

[0074] S300: Obtain DOM data, select range control points from the DOM data, input the coordinates of the range control points into the geometric precision reduction model, calculate the mean square error, if the mean square error does not meet the preset geometric precision reduction scale, adjust the error control factor in the geometric precision reduction model and update the geometric precision reduction model using the adjusted error control factor, reselect range control points and input the coordinates of the range control points into the updated geometric precision reduction model, calculate the mean square error, until the mean square error meets the preset geometric precision reduction scale, and obtain the updated geometric precision reduction model.

[0075] In this embodiment, taking the error control factor of the horizontal axis as an example, the steps for reducing the geometric accuracy error of DOM data are as follows:

[0076] S301: Let the map sheet range be... , where the width is The height is According to the spacing of each line Select control points evenly from left to right and top to bottom within the map area.

[0077] S302: Select control points and input them into the initial algorithm for reducing geometric accuracy for iterative calculation. Then calculate the mean square error. If the mean square error does not meet the preset requirements... The error factor of the geometric accuracy reduction algorithm is adjusted according to formula (5). .

[0078] (5);

[0079] S303: Repeat steps S301 and S302 until the mean error reaches the preset value.

[0080] S400: Input the coordinates of the DOM data into the updated geometrically reduced model to obtain the DOM data with reduced geometric precision.

[0081] The geometric accuracy reduction model is reconfigured based on the updated error control factor in step S300, that is, the geometric accuracy reduction model is updated in... a anda 1. At this point, inputting the coordinates of the DOM data will yield the DOM data with reduced geometric precision. Note that... a 1 and a The update or adjustment methods are basically the same, so this embodiment will not repeat the details here. a The update method for 1.

[0082] The feasibility and progressiveness of this application will be further illustrated below with experimental analysis.

[0083] Based on the proposed method for reducing the geometric precision of DOM data, experiments were conducted on three DOM datasets. The experiments were analyzed from three aspects: controllability, usability, and security, according to the evaluation criteria for geometric precision reduction processing. The three DOM datasets are data A, data B, and data C.

[0084] The basic information of the DOM data used in this embodiment is as follows: Figure 4 As shown.

[0085] Reduce the scale of the preset geometry Table 1 shows the statistical results of the maximum and minimum errors and mean square errors in geometric accuracy reduction when the m is set to 10m, 15m, and 20m respectively.

[0086] Table 1. Statistics on data accuracy under different geometric accuracy reduction scales.

[0087]

[0088] Taking a geometric accuracy reduction scale of 10m as an example, usability analysis was performed on data A, data B, and data C. The analysis results are as follows: Figure 5 As shown, by Figure 5 As can be seen, the overall image has not changed significantly, the road and ground features have not been broken, and the image has not been distorted or deformed. The overall visual quality of the data is good, which proves that the geometric precision reduction algorithm is quite usable.

[0089] Whether the DOM data is safe after the geometric accuracy is reduced is mainly analyzed by spatial offset and the mean square error after polynomial fitting correction. The following is an experimental analysis of spatial offset and the mean square error after polynomial fitting correction.

[0090] Spatial offset is an important aspect of evaluating the safety of an algorithm. If the coordinates of the processed DOM data are relatively evenly distributed in the four quadrants, it proves that the function has good spatial offset. The results of the spatial offset experiment on data A, data B, and data C are shown in Table 2.

[0091] Table 2 Statistical Table of Function Space Offset Results

[0092]

[0093] The experimental analysis results of the data after the reduction in geometric accuracy using the polynomial fitting algorithm are shown in Table 3 below:

[0094] Table 3. Correction Results of Quadratic Polynomial Fitting

[0095]

[0096] After correction using quadratic polynomial fitting, the mean square error of all data fittings is no less than 10m, which is within the geometric accuracy reduction requirement. Therefore, it can be considered that the algorithm still possesses high security even after polynomial correction.

[0097] Considering the data characteristics of DOM data and the specific requirements for geometric precision reduction, this paper proposes a composite geometric precision reduction model that combines the asymptotic properties of hyperbolic exponential functions and the nonlinear characteristics of trigonometric functions. By further incorporating amplitude, period, and error control factors, controllable precision for geometric precision reduction of DOM data is achieved. Experiments show that the proposed method, while ensuring the controllability of DOM data, has good usability and high security, meeting the requirements for geometric precision reduction of DOM data.

[0098] This application also provides a device for reducing the geometric precision of DOM data, such as... Figure 6 As shown, the DOM data geometric precision reduction device includes:

[0099] The composite function construction module 601 is configured to add an amplitude factor, a period factor, and an error control factor to the hyperbolic exponential composite function to construct a function with reduced geometric accuracy.

[0100] The model building module 602 is configured to build a geometric accuracy reduction model based on the geometric accuracy reduction function.

[0101] The model update module 603 is configured to acquire DOM data, select range control points from the DOM data, input the coordinates of the range control points into the geometric precision reduction model, calculate the mean square error, and if the mean square error does not meet the preset geometric precision reduction scale, adjust the error control factor in the geometric precision reduction model and update the geometric precision reduction model using the adjusted error control factor, reselect range control points and input the coordinates of the range control points into the updated geometric precision reduction model, calculate the mean square error, until the mean square error meets the preset geometric precision reduction scale, and obtain the updated geometric precision reduction model;

[0102] The precision reduction module 604 is configured to input the coordinates of the DOM data into the updated geometric precision reduction model to obtain the DOM data with reduced geometric precision.

[0103] In some embodiments, the hyperbolic exponential composite function is expressed as:

[0104] ;

[0105] In the formula, f ( sinx ) represents the expression for the hyperbolic exponential composite function. e Represents the natural constant. x The x-coordinate of the DOM data before the reduction in geometric precision.

[0106] In some embodiments, the geometric accuracy reduction function is expressed as:

[0107] ;

[0108] In the formula, f ( bsincx ) represents the expression for the geometric precision reduction function. b The amplitude factor representing the horizontal axis. c The composite factor representing the horizontal axis. a This represents the error control factor on the horizontal axis. x The x-coordinate of the DOM data before the reduction in geometric precision. e Represents the natural constant.

[0109] In some embodiments, the geometric accuracy reduction model is represented as:

[0110] ;

[0111] In the formula, and These represent the x and y coordinates of the DOM data after the reduction in geometric precision. x and y The x-coordinate of the DOM data before the reduction in geometric precision. b and b 1 represents the amplitude factor of the horizontal and vertical axes, respectively. c and c 1 represents the composite factor of the horizontal and vertical axes, respectively. a and a 1 represents the error control factor for the horizontal and vertical axes, respectively. e Represents the natural constant.

[0112] In some embodiments, the model update module is further configured to select range control points from the DOM data in the following manner:

[0113] Based on the map area range of the DOM data, map area control points are selected evenly from left to right and top to bottom according to the spacing of each row.

[0114] In some embodiments, the model update module is further configured to adjust the error control factor in the geometric reduction model using the following formula if the mean square error does not meet a preset geometric reduction scale:

[0115] ;

[0116] In the formula, a This represents the error control factor on the horizontal axis. D This indicates the preset geometric reduction scale. RMSE xy The two-dimensional root mean square error of the range control points.

[0117] In some embodiments, the coordinates of the DOM data are obtained in the following ways:

[0118] The pixel coordinates are obtained by performing coordinate transformation on the pixel row and column numbers of the DOM data;

[0119] The pixel coordinates are converted into projection coordinates, and the projection coordinates are used as the coordinates of the DOM data.

[0120] This application provides an electronic device. The electronic device may include a processor and a memory, wherein the processor and the memory can communicate; exemplarily, the processor and the memory communicate via a communication bus.

[0121] The processor executes computer execution instructions stored in memory, causing the processor to perform the scheme in the above embodiments. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0122] The communication bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. Transceivers are used to enable communication between database access devices and other computers (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and may also include non-volatile memory.

[0123] The electronic device provided in this application embodiment can be the terminal device described in the above embodiments.

[0124] This application also provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the technical solution of the DOM data geometric precision reduction method described in the above embodiments.

[0125] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, it can implement the technical solution of the DOM data geometric accuracy reduction method in the above embodiments.

[0126] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0127] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0128] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0129] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0130] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0131] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0132] Buses can be Industry Standard Architecture (ISA) buses, Peripheral Component Interconnect (PCI) buses, or Extended Industry Standard Architecture (EISA) buses, etc. Buses can be categorized into address buses, data buses, control buses, etc.

[0133] The aforementioned storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0134] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0135] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for reducing the geometric precision of DOM data, characterized in that, The method includes: By adding amplitude factor, period factor and error control factor to the hyperbolic exponential composite function, a function with reduced geometric accuracy is constructed. Based on the aforementioned geometric accuracy reduction function, a geometric accuracy reduction model is established; Obtain DOM data, select range control points from the DOM data, input the coordinates of the range control points into the geometric precision reduction model, calculate the mean square error, if the mean square error does not meet the preset geometric precision reduction scale, adjust the error control factor in the geometric precision reduction model and update the geometric precision reduction model using the adjusted error control factor, reselect range control points and input the coordinates of the range control points into the updated geometric precision reduction model, calculate the mean square error, until the mean square error meets the preset geometric precision reduction scale, and obtain the updated geometric precision reduction model; The coordinates of the DOM data are input into the updated geometric precision reduction model to obtain the DOM data with reduced geometric precision. The geometric accuracy reduction function is expressed as: In the formula, f ( b sincx ) represents the expression for the geometric precision reduction function. b The amplitude factor representing the horizontal axis. c The periodicity factor represents the horizontal axis. a This represents the error control factor on the horizontal axis. x The x-coordinate of the DOM data before the reduction in geometric precision. e Represents the natural constant; The geometric accuracy reduction model is represented as follows: In the formula, and These represent the x and y coordinates of the DOM data after the reduction in geometric precision. x and y The x-coordinate of the DOM data before the reduction in geometric precision. b and b 1 represents the amplitude factor of the horizontal and vertical axes, respectively. c 1 represents the composite factor of the ordinate. a and a 1 represents the error control factor for the horizontal and vertical axes, respectively. e Represents the natural constant.

2. The method for reducing the geometric precision of DOM data according to claim 1, characterized in that, The hyperbolic exponential composite function is expressed as: In the formula, f ( sinx ) represents the expression for the hyperbolic exponential composite function. e Represents the natural constant. x The x-coordinate of the DOM data before the reduction in geometric precision.

3. The method for reducing the geometric precision of DOM data according to claim 1, characterized in that, Select range control points from the DOM data in the following manner: Based on the map area range of the DOM data, map area control points are selected evenly from left to right and top to bottom according to the spacing of each row.

4. The method for reducing the geometric precision of DOM data according to claim 1, characterized in that, If the mean square error does not meet the preset geometric reduction scale, the error control factor in the geometric reduction model is adjusted using the following formula: In the formula, a This represents the error control factor on the horizontal axis. D This indicates the preset geometric reduction scale. RMSE xy The two-dimensional root mean square error of the range control points.

5. The method for reducing the geometric precision of DOM data according to claim 1, characterized in that, The coordinates of the DOM data can be obtained in the following ways: The pixel coordinates are obtained by performing coordinate transformation on the pixel row and column numbers of the DOM data; The pixel coordinates are converted into projection coordinates, and the projection coordinates are used as the coordinates of the DOM data.

6. A device for reducing the geometric precision of DOM data, used to implement the method as described in any one of claims 1-5, characterized in that, The device includes: The composite function construction module is configured to add amplitude factors, period factors, and error control factors to hyperbolic exponential composite functions to construct functions with reduced geometric accuracy. The model building module is configured to build a geometrically reduced model based on the geometrically reduced function. The model update module is configured to acquire DOM data, select range control points from the DOM data, input the coordinates of the range control points into the geometric precision reduction model, calculate the mean square error, and if the mean square error does not meet the preset geometric precision reduction scale, adjust the error control factor in the geometric precision reduction model and update the geometric precision reduction model using the adjusted error control factor, reselect range control points and input the coordinates of the range control points into the updated geometric precision reduction model, calculate the mean square error, until the mean square error meets the preset geometric precision reduction scale, and obtain the updated geometric precision reduction model; The precision reduction module is configured to input the coordinates of the DOM data into the updated geometric precision reduction model to obtain the DOM data with reduced geometric precision.

7. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the DOM data geometric precision reduction method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the DOM data geometry precision reduction method as described in any one of claims 1-5.

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