High-resolution satellite image correction method and system

Abstract

The invention discloses a high-resolution satellite image correction method and system, and relates to the technical field of high-resolution satellite image processing, and the method comprises the following steps: S1, image atmospheric correction, S2, connection point analysis, S3, image ortho-rectification, and S4, image geometric correction. According to the method, the matched homonymy point file input by the user is received, secondary correction is performed on the high-resolution satellite image data according to the matched homonymy point file by using the geometric correction algorithm, so that the high-resolution satellite image information closer to reality is obtained, and meanwhile, the high-resolution satellite image information is analyzed by using the DEM data during ortho-rectification, so that the accuracy of the high-resolution satellite image information is improved. The high-resolution satellite image data obtained through atmospheric correction is different from correction data obtained through traditional processing, and the high-resolution satellite image data obtained through atmospheric correction is more accurate and more accurate and can be used for outputting more real image products with rich information, so that the accuracy and the refinement level of meteorological disaster monitoring in the aspects of water body monitoring, flood disaster monitoring and the like are improved. The influence of the absorption and scattering effects of the atmosphere on solar radiation is eliminated, and it is guaranteed that image data are more real.

Description

Technical Field

[0001] The present invention relates to the technical field of high-resolution satellite image processing, and in particular to a high-resolution satellite image correction method and system. Background Art

[0002] The Gaofen series of satellites supplement the information of the Fengyun series of high-resolution satellites by providing high spatial resolution data and hyperspectral data. They play an important role in the meteorological field in responding to special weather and surface disasters. From disaster monitoring to accuracy verification, they provide important technical means and data support for meteorological forecasting, climate research, disaster prevention and relief, etc. However, affected by factors such as satellite orbit and attitude, the curvature of the earth's surface and atmospheric refraction, satellite images often produce geometric distortion and spectral distortion, which affects the judgment and analysis of surface cover types and attributes. Therefore, corresponding measures and technical means need to be taken to solve these problems and improve the accuracy and reliability of data. During use, control points are usually matched automatically, and an affine model or a geometric polynomial model is constructed using the matched control points to sample the image to complete the geometric correction process. This may result in a large number of erroneous matching points in the matching results. Because it is impossible to receive matching points with the same name provided by the user, the final corrected image data often does not fit the actual image data, and a single correction method cannot be applied to different image data. Summary of the invention

[0003] The object of the present invention is to provide a high-resolution satellite image correction method and system to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a high-resolution satellite image correction method, comprising the following steps: S1. Image atmospheric correction: The DN value in the high-resolution satellite image data is converted into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm. After selecting the atmospheric correction model, the atmospheric correction lookup table is established using the aerosol optical thickness and atmospheric parameters. The surface reflectivity is calculated using the relevant parameters in the atmospheric correction lookup table to obtain the corrected high-resolution satellite image data. The corrected high-resolution satellite image data is analyzed using the resampling method and then transmitted to the storage device; S2, analyzing connection points: analyzing the high-resolution satellite image data to be corrected according to these control points and DEM data to obtain multiple connection points, determining the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculating the resolution of the current high-resolution satellite image data using the average elevation surface; S3, image orthorectification: If the data for orthorectification is DEM regular grid data, the square grid points of DEM are used as the correction unit, and the high-resolution satellite image coordinates of all points in the correction unit are calculated by the bilinear interpolation formula. If the data for orthorectification is vector feature point data and three-dimensional discrete point cloud data, the triangulation network is used as the correction unit, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed by the affine transformation formula. The corrected high-resolution satellite image data is analyzed based on these data by the orthorectification algorithm; S4. Image geometric correction: The control point primitive information is transferred to the control point primitive database. After obtaining the high-resolution satellite image data to be corrected, the coordinates of the offset points are modified according to the position coordinates of the control point primitives of the high-resolution satellite image to be corrected using the geometric correction algorithm, and the preliminarily corrected high-resolution satellite image data is output. After receiving the matching same-name point file input by the user, the high-resolution satellite image data is secondary corrected using the geometric correction algorithm according to the matching same-name point file.

[0005] Preferably, the step S1 specifically includes the following steps: S101, after obtaining the high-resolution satellite image data to be corrected, convert the DN value in the high-resolution satellite image data into the apparent reflectivity of the top of the atmosphere according to the calibration coefficient, the solar altitude angle and the imaging time parameters through the atmospheric reflection analysis algorithm; S102, dividing the atmospheric correction model into three types, namely, an image feature-based model, a ground linear regression empirical model, and an atmospheric radiation transfer model; S103, after selecting the atmospheric correction model, extract the aerosol optical thickness, calculate the atmospheric parameters according to the aerosol optical thickness, and establish an atmospheric correction lookup table using the aerosol optical thickness and the atmospheric parameters.

[0006] Preferably, the step S1 specifically further comprises the following steps: S104, when correcting the high-resolution satellite image data through the atmospheric correction model, after obtaining relevant parameters in the lookup table using the aerosol type, sensor angle, and aerosol optical thickness, the surface reflectivity is calculated using the parameters through the surface analysis algorithm, thereby obtaining the corrected high-resolution satellite image information; S105, analyzing the corrected high-resolution satellite image data using a resampling method to obtain processed high-resolution satellite image data, and transmitting the processed high-resolution satellite image data to a storage device.

[0007] Preferably, the step S2 specifically includes the following steps: S201, obtaining DEM data within the range of the high-resolution satellite image to be corrected, selecting a plurality of control points in the high-resolution satellite image data to be corrected, and analyzing the high-resolution satellite image data to be corrected according to the control points and the DEM data to obtain a plurality of connection points; S202, reading the RPC coefficient corresponding to the high-resolution satellite image data, determining the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculating the resolution of the current high-resolution satellite image data using the average elevation surface.

[0008] Preferably, the step S3 specifically includes the following steps: S301, the terrain data obtained by one-way orthorectification is divided into three types, namely DEM regular grid data, vector feature point line data and three-dimensional discrete point cloud data; S302. If the data used for orthorectification is DEM regular grid data, the square grid points of DEM are used as correction units, and the high-resolution satellite image coordinates of the four corner points corresponding to the grid points are calculated using the collinear equation. The high-resolution satellite image coordinates of all points in the correction unit are calculated using the bilinear interpolation formula.

[0009] Preferably, the step S3 specifically further comprises the following steps: S303, if the data during orthorectification is vector feature point data and three-dimensional discrete point cloud data, triangulation is used as the correction unit, and the high-resolution satellite image coordinates of the three vertices of each triangulation are calculated using the collinear equation, and the high-resolution satellite image coordinates are associated with the actual location coordinates through the affine transformation formula, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed; S304, determining the coordinates of each pixel in the corrected high-resolution satellite image data; using the coordinates of each pixel after correction combined with the RPC coefficient to calculate the row and column numbers of the pixel corresponding to the high-resolution satellite image; analyzing the corrected high-resolution satellite image data based on these data using an orthorectification algorithm, the orthorectification algorithm is specifically as follows: in, represents the plane coordinates, represents the coordinates of the corresponding ground control points, represents the projection focal length, represents the scale parameter of the model, Indicates the side view. and Both represent model parameters.

[0010] Preferably, the step S4 specifically includes the following steps: S401, after the control point is selected, the corresponding image information is generated through the control point, and the image information is transmitted as the control point primitive information to the control point primitive database, and the control point related information is transmitted to the control point primitive database at the same time, and the related information includes the control point number, the control point primitive position coordinates, the control point primitive resolution and the current storage location; S402, after obtaining the high-resolution satellite image data to be corrected, after determining the control point primitive set corresponding to the high-resolution satellite image data to be corrected according to the control point primitive database, the coordinates of the offset point are modified according to the position coordinates of the control point primitives of the high-resolution satellite image to be corrected using a geometric correction algorithm, and the high-resolution satellite image data of preliminary correction is output, wherein the geometric correction algorithm is specifically as follows: in, Represents the pixel coordinates in the high-resolution satellite image data to be corrected. Indicates the pixel coordinates in the current high-resolution satellite image data. Indicates various parameters related to the horizontal coordinate in high-resolution satellite image data. Indicates various parameters related to the vertical coordinate in high-resolution satellite image data; S403, after receiving the initially corrected high-resolution satellite image data and the matching same-name point file input by the user, a geometric correction algorithm is used to perform secondary correction on the high-resolution satellite image data according to the matching same-name point file to obtain corrected high-resolution satellite image data.

[0011] The high-resolution satellite image correction system comprises a resampling analysis unit, a resolution calculation unit, an orthorectification unit and a geometric correction unit; The resampling analysis unit converts the DN value in the high-resolution satellite image data into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm, selects the atmospheric correction model, establishes an atmospheric correction lookup table using the aerosol optical thickness and the atmospheric parameters, calculates the surface reflectivity using the relevant parameters in the atmospheric correction lookup table, thereby obtaining the corrected high-resolution satellite image data, and transmits the corrected high-resolution satellite image data to the storage device after analyzing it using the resampling method; The resolution calculation unit analyzes the high-resolution satellite image data to be corrected according to the control points and the DEM data to obtain a plurality of connection points, determines the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculates the resolution of the current high-resolution satellite image data using the average elevation surface; If the data during orthorectification is DEM regular grid data, the orthorectification correction unit uses the square grid points of the DEM as the correction unit, and calculates the high-resolution satellite image coordinates of all points in the correction unit through a bilinear interpolation formula; if the data during orthorectification is vector feature point data and three-dimensional discrete point cloud data, the triangulation is used as the correction unit, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed through the affine transformation formula, and the corrected high-resolution satellite image data is analyzed based on these data through an orthorectification algorithm; The geometric correction unit transmits the control point primitive information to the control point primitive database, obtains the high-resolution satellite image data to be corrected, uses the geometric correction algorithm to modify the coordinates of the offset point according to the position coordinates of the control point primitive of the high-resolution satellite image to be corrected, outputs the preliminarily corrected high-resolution satellite image data, receives the matching same-name point file input by the user, and uses the geometric correction algorithm to perform secondary correction on the high-resolution satellite image data according to the matching same-name point file.

[0012] Compared with the prior art, the present invention has the following beneficial effects: The present invention receives high-resolution satellite multispectral images input by users, performs standardized processing on high-resolution satellite data, including processing of optical, radar and hyperspectral data. Image data obtained by atmospheric correction is different from the corrected data after traditional processing, and the influence of the absorption and scattering effects of the atmosphere on solar radiation and the atmosphere on target radiation is eliminated, so as to ensure that the image data is more authentic and reliable. In addition, the present invention receives the matched homonymous point files input by users, and performs secondary correction on the high-resolution satellite image data according to the matched homonymous point files by using a geometric correction algorithm, so as to obtain high-resolution satellite image information that is closer to reality. At the same time, the results obtained by multiple corrections are more in line with the needs of users. Some ground control points are selected on the high-resolution satellite images through orthorectification, and the high-resolution satellite image information is analyzed by using DEM data. The processed high-resolution satellite images have topographic map characteristics and high-resolution satellite image characteristics, are rich in information, and the standardized processing time of single-view optical data is less than ten minutes, and the standardized processing time of single-view SAR data is less than fifteen minutes, so the performance is more excellent. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 Provide an overall method flow chart for an embodiment of the present invention; Figure 2 A flow chart of a method for image atmospheric correction provided by an embodiment of the present invention; Figure 3 A flow chart of a method for orthorectification of images provided by an embodiment of the present invention; Figure 4 A flow chart of a method for image geometric correction provided by an embodiment of the present invention; Figure 5 The effect diagram of the image before and after atmospheric correction provided by the embodiment of the present invention; Figure 6 The effect diagram of the image before and after orthorectification provided by the embodiment of the present invention; Figure 7 The effect diagram of the image before and after geometric correction provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] See also Figure 1-7 The present invention provides a technical solution: a high-resolution satellite image correction method, comprising the following steps: S1. Image atmospheric correction: The DN value in the high-resolution satellite image data is converted into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm. After selecting the atmospheric correction model, the atmospheric correction lookup table is established using the aerosol optical thickness and atmospheric parameters. The surface reflectivity is calculated using the relevant parameters in the atmospheric correction lookup table to obtain the corrected high-resolution satellite image data. The corrected high-resolution satellite image data is analyzed using the resampling method and then transmitted to the storage device; S2, analyzing connection points: analyzing the high-resolution satellite image data to be corrected according to these control points and DEM data to obtain multiple connection points, determining the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculating the resolution of the current high-resolution satellite image data using the average elevation surface; S3, image orthorectification: If the data for orthorectification is DEM regular grid data, the square grid points of DEM are used as the correction unit, and the high-resolution satellite image coordinates of all points in the correction unit are calculated by the bilinear interpolation formula. If the data for orthorectification is vector feature point data and three-dimensional discrete point cloud data, the triangulation network is used as the correction unit, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed by the affine transformation formula. The corrected high-resolution satellite image data is analyzed based on these data by the orthorectification algorithm; S4. Image geometric correction: The control point primitive information is transferred to the control point primitive database. After obtaining the high-resolution satellite image data to be corrected, the coordinates of the offset points are modified according to the position coordinates of the control point primitives of the high-resolution satellite image to be corrected using the geometric correction algorithm, and the preliminarily corrected high-resolution satellite image data is output. After receiving the matching same-name point file input by the user, the high-resolution satellite image data is secondary corrected using the geometric correction algorithm according to the matching same-name point file.

[0016] Step S1 specifically includes the following steps: S101, after obtaining the high-resolution satellite image data to be corrected, the DN value in the high-resolution satellite image data is converted into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm according to the calibration coefficient, the solar altitude angle and the imaging time parameter. The atmospheric reflection analysis algorithm is specifically as follows: in, is the apparent reflectivity of the top of the atmosphere, represents the radiance received by the satellite, represents the distance between the sun and the earth, represents the solar constant, represents the solar zenith angle; S102, dividing the atmospheric correction model into three types, namely, an image feature-based model, a ground linear regression empirical model, and an atmospheric radiation transfer model; S103, after selecting the atmospheric correction model, extract the aerosol optical thickness, calculate the atmospheric parameters according to the aerosol optical thickness, and establish an atmospheric correction lookup table using the aerosol optical thickness and the atmospheric parameters.

[0017] Step S1 specifically also includes the following steps: S104, when correcting the high-resolution satellite image data through the atmospheric correction model, after obtaining relevant parameters in the lookup table using the aerosol type, sensor angle, and aerosol optical thickness, the surface reflectivity is calculated using the parameters through the surface analysis algorithm, thereby obtaining the corrected high-resolution satellite image information; S105, analyzing the corrected high-resolution satellite image data using a resampling method to obtain processed high-resolution satellite image data, and transmitting the processed high-resolution satellite image data to a storage device; Step S2 specifically includes the following steps: S201, obtaining DEM data within the range of the high-resolution satellite image to be corrected, selecting a plurality of control points in the high-resolution satellite image data to be corrected, and analyzing the high-resolution satellite image data to be corrected according to the control points and the DEM data to obtain a plurality of connection points; S202, reading the RPC coefficient corresponding to the high-resolution satellite image data, determining the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculating the resolution of the current high-resolution satellite image data using the average elevation surface; Step S3 specifically includes the following steps: S301, the terrain data obtained by one-way orthorectification is divided into three types, namely DEM regular grid data, vector feature point line data and three-dimensional discrete point cloud data; S302, if the data for orthorectification is DEM regular grid data, the square grid points of DEM are used as correction units, and the high-resolution satellite image coordinates of the four corner points corresponding to the grid points are calculated using the collinearity equation, and the high-resolution satellite image coordinates of all points in the correction unit are calculated using the bilinear interpolation formula. The collinearity equation is specifically: in, represents the image plane coordinates of the image point, Represents the internal orientation elements of high-resolution satellite image data. represents the object space coordinates of the camera point, represents the object space coordinates of the object point, The nine direction cosines composed of three exterior azimuth elements representing the high-resolution satellite image data; Step S3 specifically also includes the following steps: S303, if the data during orthorectification is vector feature point data and three-dimensional discrete point cloud data, triangulation is used as the correction unit, and the high-resolution satellite image coordinates of the three vertices of each triangulation are calculated using the collinear equation, and the high-resolution satellite image coordinates are associated with the actual location coordinates through the affine transformation formula, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed; S304, determining the coordinates of each pixel in the corrected high-resolution satellite image data; using the coordinates of each pixel after correction combined with the RPC coefficient to calculate the row and column numbers of the pixel corresponding to the high-resolution satellite image; analyzing the corrected high-resolution satellite image data based on these data using an orthorectification algorithm, the orthorectification algorithm is specifically as follows: in, represents the plane coordinates, represents the coordinates of the corresponding ground control points, represents the projection focal length, represents the scale parameter of the model, Indicates the side view. and All represent model parameters; Step S4 specifically includes the following steps: S401, after the control point is selected, the corresponding image information is generated through the control point, and the image information is transmitted as the control point primitive information to the control point primitive database, and the control point related information is transmitted to the control point primitive database at the same time, and the related information includes the control point number, the control point primitive position coordinates, the control point primitive resolution and the current storage location; S402, after obtaining the high-resolution satellite image data to be corrected, after determining the control point primitive set corresponding to the high-resolution satellite image data to be corrected according to the control point primitive database, the coordinates of the offset point are modified according to the position coordinates of the control point primitives of the high-resolution satellite image to be corrected using a geometric correction algorithm, and the high-resolution satellite image data of preliminary correction is output. The specific geometric correction algorithm is: in, Represents the pixel coordinates in the high-resolution satellite image data to be corrected. Indicates the pixel coordinates in the current high-resolution satellite image data. Indicates various parameters related to the horizontal coordinate in high-resolution satellite image data. Indicates various parameters related to the vertical coordinate in high-resolution satellite image data; S403, after receiving the initially corrected high-resolution satellite image data and the matching same-name point file input by the user, a geometric correction algorithm is used to perform secondary correction on the high-resolution satellite image data according to the matching same-name point file to obtain corrected high-resolution satellite image data; A high-resolution satellite image correction system, comprising a resampling analysis unit, a resolution calculation unit, an orthorectification unit and a geometric correction unit; The resampling analysis unit converts the DN value in the high-resolution satellite image data into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm. After selecting the atmospheric correction model, the atmospheric correction lookup table is established using the aerosol optical thickness and atmospheric parameters. The surface reflectivity is calculated using the relevant parameters in the atmospheric correction lookup table, thereby obtaining the corrected high-resolution satellite image data. The corrected high-resolution satellite image data is analyzed using the resampling method and then transmitted to the storage device; The resolution calculation unit analyzes the high-resolution satellite image data to be corrected according to these control points and DEM data to obtain multiple connection points, determines the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculates the resolution of the current high-resolution satellite image data using the average elevation surface; Orthorectification unit: If the data during orthorectification is DEM regular grid data, the square grid points of DEM are used as correction units, and the high-resolution satellite image coordinates of all points in the correction unit are calculated by bilinear interpolation formula. If the data during orthorectification is vector feature point data and three-dimensional discrete point cloud data, the triangulation network is used as the correction unit, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed by the affine transformation formula. The corrected high-resolution satellite image data are analyzed based on these data by the orthorectification algorithm. The geometric correction unit transmits the control point primitive information to the control point primitive database, obtains the high-resolution satellite image data to be corrected, and then uses the geometric correction algorithm to modify the coordinates of the offset point according to the position coordinates of the control point primitive of the high-resolution satellite image to be corrected, outputs the preliminarily corrected high-resolution satellite image data, receives the matching same-name point file input by the user, and then uses the geometric correction algorithm to perform secondary correction on the high-resolution satellite image data according to the matching same-name point file.

[0018] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0019] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A high-resolution satellite image correction method, characterized in that: The method comprises the following steps: S1. Image atmospheric correction: The DN value in the high-resolution satellite image data is converted into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm. After selecting the atmospheric correction model, the atmospheric correction lookup table is established using the aerosol optical thickness and atmospheric parameters. The surface reflectivity is calculated using the relevant parameters in the atmospheric correction lookup table to obtain the corrected high-resolution satellite image data. The corrected high-resolution satellite image data is analyzed using the resampling method and then transmitted to the storage device; S2, analyzing connection points: analyzing the high-resolution satellite image data to be corrected according to these control points and DEM data to obtain multiple connection points, determining the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculating the resolution of the current high-resolution satellite image data using the average elevation surface; S3, image orthorectification: If the data for orthorectification is DEM regular grid data, the square grid points of DEM are used as the correction unit, and the high-resolution satellite image coordinates of all points in the correction unit are calculated by the bilinear interpolation formula. If the data for orthorectification is vector feature point data and three-dimensional discrete point cloud data, the triangulation network is used as the correction unit, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed by the affine transformation formula. The corrected high-resolution satellite image data is analyzed based on these data by the orthorectification algorithm; S4. Image geometric correction: The control point primitive information is transferred to the control point primitive database. After obtaining the high-resolution satellite image data to be corrected, the coordinates of the offset points are modified according to the position coordinates of the control point primitives of the high-resolution satellite image to be corrected using the geometric correction algorithm, and the preliminarily corrected high-resolution satellite image data is output. After receiving the matching same-name point file input by the user, the high-resolution satellite image data is secondary corrected using the geometric correction algorithm according to the matching same-name point file.

2. A high-resolution satellite image correction method according to claim 1, characterized in that: The step S1 specifically includes the following steps: S101, after obtaining the high-resolution satellite image data to be corrected, convert the DN value in the high-resolution satellite image data into the apparent reflectivity of the top of the atmosphere according to the calibration coefficient, the solar altitude angle and the imaging time parameters through the atmospheric reflection analysis algorithm; S102, dividing the atmospheric correction model into three types, namely, an image feature-based model, a ground linear regression empirical model, and an atmospheric radiation transfer model; S103, after selecting the atmospheric correction model, extract the aerosol optical thickness, calculate the atmospheric parameters according to the aerosol optical thickness, and establish an atmospheric correction lookup table using the aerosol optical thickness and the atmospheric parameters.

3. A high-resolution satellite image correction method according to claim 2, characterized in that: The step S1 specifically further comprises the following steps: S104, when correcting the high-resolution satellite image data through the atmospheric correction model, after obtaining relevant parameters in the lookup table using the aerosol type, sensor angle, and aerosol optical thickness, the surface reflectivity is calculated using the parameters through the surface analysis algorithm, thereby obtaining the corrected high-resolution satellite image information; S105, analyzing the corrected high-resolution satellite image data using a resampling method to obtain processed high-resolution satellite image data, and transmitting the processed high-resolution satellite image data to a storage device.

4. The high-resolution satellite image correction method according to claim 1, characterized in that: The step S2 specifically includes the following steps: S201, obtaining DEM data within the range of the high-resolution satellite image to be corrected, selecting a plurality of control points in the high-resolution satellite image data to be corrected, and analyzing the high-resolution satellite image data to be corrected according to the control points and the DEM data to obtain a plurality of connection points; S202, reading the RPC coefficient corresponding to the high-resolution satellite image data, determining the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculating the resolution of the current high-resolution satellite image data using the average elevation surface.

5. The high-resolution satellite image correction method according to claim 1, characterized in that: The step S3 specifically comprises the following steps: S301, the terrain data obtained by one-way orthorectification is divided into three types, namely DEM regular grid data, vector feature point line data and three-dimensional discrete point cloud data; S302. If the data used for orthorectification is DEM regular grid data, the square grid points of DEM are used as correction units, and the high-resolution satellite image coordinates of the four corner points corresponding to the grid points are calculated using the collinear equation. The high-resolution satellite image coordinates of all points in the correction unit are calculated using the bilinear interpolation formula.

6. A high-resolution satellite image correction method according to claim 5, characterized in that: The step S3 specifically further comprises the following steps: S303, if the data during orthorectification is vector feature point data and three-dimensional discrete point cloud data, triangulation is used as the correction unit, and the high-resolution satellite image coordinates of the three vertices of each triangulation are calculated using the collinear equation, and the high-resolution satellite image coordinates are associated with the actual location coordinates through the affine transformation formula, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed; S304, determining the coordinates of each pixel in the corrected high-resolution satellite image data; using the coordinates of each pixel after correction combined with the RPC coefficient to calculate the row and column numbers of the pixel corresponding to the high-resolution satellite image; and analyzing the corrected high-resolution satellite image data based on these data using an orthorectification algorithm.

7. The high-resolution satellite image correction method according to claim 1, characterized in that: The step S4 specifically comprises the following steps: S401, after the control point is selected, the corresponding image information is generated through the control point, and the image information is transmitted as the control point primitive information to the control point primitive database, and the control point related information is transmitted to the control point primitive database at the same time, and the related information includes the control point number, the control point primitive position coordinates, the control point primitive resolution and the current storage location; S402, after obtaining the high-resolution satellite image data to be corrected, after determining the control point primitive set corresponding to the high-resolution satellite image data to be corrected according to the control point primitive database, modify the coordinates of the offset point according to the position coordinates of the control point primitives of the high-resolution satellite image to be corrected using a geometric correction algorithm, and output the preliminarily corrected high-resolution satellite image data; S403, after receiving the initially corrected high-resolution satellite image data and the matching same-name point file input by the user, a geometric correction algorithm is used to perform secondary correction on the high-resolution satellite image data according to the matching same-name point file to obtain corrected high-resolution satellite image data.

8. A high-resolution satellite image correction system according to any one of claims 1 to 7, characterized in that It includes a resampling analysis unit, a resolution calculation unit, an orthorectification unit and a geometric correction unit; The resampling analysis unit converts the DN value in the high-resolution satellite image data into the apparent reflectivity of the top of the atmosphere through the atmospheric reflection analysis algorithm, selects the atmospheric correction model, establishes an atmospheric correction lookup table using the aerosol optical thickness and the atmospheric parameters, calculates the surface reflectivity using the relevant parameters in the atmospheric correction lookup table, thereby obtaining the corrected high-resolution satellite image data, and transmits the corrected high-resolution satellite image data to the storage device after analyzing it using the resampling method; The resolution calculation unit analyzes the high-resolution satellite image data to be corrected according to the control points and the DEM data to obtain a plurality of connection points, determines the longitude and latitude range of the high-resolution satellite image according to the row and column numbers of the high-resolution satellite image data, and calculates the resolution of the current high-resolution satellite image data using the average elevation surface; If the data during orthorectification is DEM regular grid data, the orthorectification correction unit uses the square grid points of the DEM as the correction unit, and calculates the high-resolution satellite image coordinates of all points in the correction unit through a bilinear interpolation formula; if the data during orthorectification is vector feature point data and three-dimensional discrete point cloud data, the triangulation is used as the correction unit, and the affine transformation parameters and the high-resolution satellite image coordinates of all points are analyzed through the affine transformation formula, and the corrected high-resolution satellite image data is analyzed based on these data through an orthorectification algorithm; The geometric correction unit transmits the control point primitive information to the control point primitive database, obtains the high-resolution satellite image data to be corrected, uses the geometric correction algorithm to modify the coordinates of the offset point according to the position coordinates of the control point primitive of the high-resolution satellite image to be corrected, outputs the preliminarily corrected high-resolution satellite image data, receives the matching same-name point file input by the user, and uses the geometric correction algorithm to perform secondary correction on the high-resolution satellite image data according to the matching same-name point file.

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