Multi-slice remote sensing data reprojection method and device, medium and equipment

Abstract

The invention discloses a multi-slice remote sensing data re-projection method and device, a medium and equipment, and relates to the field of remote sensing image processing, and the method comprises the steps: obtaining a plurality of slices of first remote sensing data in a reference time period; performing conversion operation on the position information of the plurality of slices in the grid to obtain re-projection positions of the plurality of slices in the target coordinate system; wherein the conversion operation comprises splicing, reprojection and resampling operation; constructing a position corresponding relation matrix according to the position information of the plurality of slices before the conversion operation and the re-projection positions of the slices in the target coordinate system; according to the constructed position corresponding relation matrix, position information corresponding to the re-projection positions of the slices in other time periods in the second remote sensing data is determined through a search function, and the data value of each slice in other time periods is obtained; wherein the second remote sensing data is original remote sensing data acquired in other time periods.

Description

Technical Field

[0001] The present invention relates to the technical field of remote sensing image processing, and in particular to a multi-slice remote sensing data reprojection method, device, medium and equipment. Background Art

[0002] With the development of remote sensing technology and the expansion of its application fields, more and more scientific research or commercial applications in multiple disciplines such as meteorology, hydrology, ecology, and geography require reprojection processing of large quantities of remote sensing data.

[0003] Traditional reprojection techniques typically perform separate calculations for each remote sensing image. This per-image processing strategy is particularly necessary for resampling methods that require altering the original pixel values (such as bilinear interpolation and cubic spline interpolation). However, traditional reprojection methods fail to effectively exploit the commonalities between data, resulting in extensive repeated computations and a significant waste of computational resources. This per-image reprojection approach is particularly inadequate for multi-temporal and multi-slice remote sensing data. Furthermore, while the nearest neighbor method, as a resampling method that preserves original pixel values, offers advantages such as computational simplicity and high processing speed, its per-image reprojection approach also wastes computational time in large-scale data processing, making it difficult to meet the requirements of real-time remote sensing data processing. This makes it difficult to obtain the location information of large quantities of reprojected remote sensing data within the original data, and consequently, to quickly obtain the corresponding data values. Summary of the Invention

[0004] The present invention provides a multi-slice remote sensing data reprojection method, apparatus, medium, and device to solve the above-mentioned problem existing in the prior art, namely, how to quickly obtain the position information of a large amount of reprojected remote sensing data in the original data, thereby obtaining the corresponding data value. The present invention provides a multi-slice remote sensing data reprojection method, which includes: Acquire a plurality of slices of first remote sensing data during a reference period; Performing a conversion operation on the position information of the multiple slices in the grid to obtain reprojected positions of the multiple slices in the target coordinate system; wherein the conversion operation includes splicing, reprojection and resampling operations; Construct a position correspondence matrix based on the position information of multiple slices before the transformation operation and their reprojected positions in the target coordinate system; According to the constructed position correspondence matrix, the position information corresponding to the reprojected position of the slices in other time periods in the second remote sensing data is determined by a lookup function to obtain the data value of each slice in other time periods; wherein the second remote sensing data is the original remote sensing data obtained in other time periods.

[0005] Optionally, the location information specifically includes: Slice index layer, row number layer, and column number layer.

[0006] Optionally, performing a conversion operation on the position information of the multiple slices in the grid to obtain reprojected positions of the multiple slices in the target coordinate system specifically includes: M reproj =ReprojectAndResample(Merge({I i | i ∈ S}), CS orig →CS target , res orig →res target ); Among them, I i is the index or row and column number layer data of the i-th slice, S={1,2,...,n} is the slice set, Merge is the splicing function, CS orig is the coordinate system of the original first remote sensing data, CS target is the target coordinate system, res orig is the original resolution, res target is the target resolution, M reproj The tile index layer after the conversion operation.

[0007] Optionally, determining, based on the constructed position correspondence matrix, position information in the second remote sensing data corresponding to the reprojected position of slices in other time periods by a lookup function specifically includes: The reprojected position of each slice is obtained using the following formula: D output,t,i′,j′,k′ =D input,t,i,j,k ; in, (i,j,k)=Lookup(T, (i′,j′,k′)); Among them, D output,t,i′,j′,k′ is the data D in the target coordinate system output,t The reprojected position of each slice in D input,t,i,j,k is the original remote sensing data D input,t The corresponding position information (i, j, k) in , Lookup is the search function, and T is the position correspondence matrix; The search function takes any reprojected position as input, brings it into the position correspondence matrix T, and determines its corresponding grid position information in the original remote sensing data.

[0008] The present invention provides a multi-slice remote sensing data reprojection device, comprising: An acquisition module, configured to acquire a plurality of slices of first remote sensing data during a reference period; A coordinate conversion module is used to convert the position information of multiple slices in the grid to obtain the reprojected positions of the multiple slices in the target coordinate system; wherein the conversion operation includes splicing, reprojection and resampling operations; A position correspondence matrix construction module is used to construct a position correspondence matrix based on the position information of multiple slices before the transformation operation and their reprojected positions in the target coordinate system; The determination module is used to determine the corresponding position information of the reprojected position of the slices in other time periods in the second remote sensing data through a lookup function based on the constructed position correspondence matrix, and obtain the data value of each slice in other time periods; wherein the second remote sensing data is the original remote sensing data obtained in other time periods.

[0009] The present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the multi-slice remote sensing data reprojection method is implemented.

[0010] The present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the multi-slice remote sensing data reprojection method is implemented.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention provides a multi-slice remote sensing data reprojection method, which establishes a mapping relationship between pixel positions in different projection coordinate systems by introducing a position correspondence matrix. When reprojecting subsequent data, there is no need to repeat the coordinate conversion, and the mapped position can be obtained by matrix search, thereby achieving rapid reprojection; at the same time, an accurate mapping relationship between the original data and the output data is established through the position correspondence matrix T. For each output position, the corresponding original data position can be found in the matrix T through the search function, thereby ensuring that data of different phases and different slices can be accurately reprojected to the corresponding position in the same target coordinate system. The effect of this precise registration makes the reprojected data completely aligned in space, so that the corresponding data values can be quickly obtained, ensuring the spatial consistency of the data; the position correspondence matrix constructed by the present invention is universal and is not limited by the type of projection transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0013] Figure 1 A flowchart of a multi-slice remote sensing data reprojection method provided by an embodiment of the present invention; Figure 2A technical roadmap for a multi-slice remote sensing data reprojection method provided by an embodiment of the present invention; Figure 3 A schematic diagram of a computer device for a multi-slice remote sensing data reprojection method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0014] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0015] The following describes in detail the technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems using specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The following embodiments of the present invention are described in conjunction with the accompanying drawings.

[0016] like Figure 1 and Figure 2 As shown, this embodiment shows a multi-slice remote sensing data reprojection method, including: S1: Acquire multiple slices of first remote sensing data in a reference period.

[0017] For example, each slice is gridded (e.g., 1200×1200 1km resolution grids form a slice file) with uniform resolution and coordinate system. This dataset is represented by a three-dimensional array D, where Dt,i,j,k represents the pixel value at row j and column k in slice i at time phase (e.g., day number). Here, t, i, j, and k are the indices of time phase, slice, row, and column, respectively.

[0018] S2: performing a conversion operation on the position information of the multiple slices in the grid to obtain reprojected positions of the multiple slices in the target coordinate system; wherein the conversion operation includes splicing, reprojection, and resampling operations.

[0019] Optionally, the location information specifically includes: a slice index layer, a row number layer, and a column number layer.

[0020] For example, when constructing a slice index layer, you can select data from any phase (such as any day) as a benchmark (called input file), denoted by D base,i,j,k , where i, j, and k are the indices of slices, rows, and columns, respectively. Create an index layer I for each slice i, where the value of each grid is a triple (i, j, k), which represents the slice number, row number, and column number of the grid in the original data, which can be expressed as:

[0021] I i (j,k)=(i,j,k); For example, when reprojecting and resampling the slice index layer, the coordinate system of the original data is set to CS orig , the target coordinate system is CS target . Reproject and resample the tile index layer Is from CS orig Transform to CS target , and change the resolution from the original resolution res orig Resample to the new resolution res target The reprojected and resampled slice index layer is denoted as M reproj ,This process can be expressed as:

[0022] M reproj =ReprojectAndResample(Merge({I i | i ∈ S}), CS orig →CS target , res orig →res target ); Among them, I i is the index or row and column number layer data of the i-th slice, S={1,2,...,n} is the slice set, Merge is the splicing function, CS orig is the coordinate system of the original data, CS target is the target coordinate system, res orig is the original resolution, res target is the target resolution, and ReprojectAndResample is the algorithm for implementing reprojection and resampling.

[0023] It should be noted that there is no need to give a specific reprojection calculation form here, and this embodiment is not limited to a specific reprojection type.

[0024] S3: Construct a position correspondence matrix based on the position information of multiple slices before the transformation operation and their reprojected positions in the target coordinate system.

[0025] For example, for any grid (i′, j′, k′) in the output data, since the nearest neighbor resampling method is used, the grid value must correspond to the slice index layer I s A specific value in which the I sThe position information of a specific grid in the original slice index layer I can be used to compare the position of the grid (i′, j′, k′) in the output data with its position in the original slice index layer I. s The corresponding relationship is established with the position information (i, j, k) in the output data and stored in the position correspondence matrix T. Finally, by traversing all the grids of the output data, the complete position correspondence matrix T is constructed, that is, T i′,j′,k′ = (i,j,k).

[0026] S4: According to the constructed position correspondence matrix, the position information corresponding to the reprojected position of the slices in other time periods in the second remote sensing data is determined by a lookup function to obtain the data value of each slice in other time periods; wherein the second remote sensing data is the original remote sensing data obtained in other time periods.

[0027] For example, the position information in the second remote sensing data corresponding to the reprojected position of slices in other time periods can be determined by a lookup function based on the constructed position correspondence matrix, specifically including: D output,t,i′,j′,k′ =D input,t,i,j,k ; in, (i,j,k)=Lookup(T, (i′,j′,k′)); Among them, D output,t,i′,j′,k′ is the data in the target coordinate system (i.e. output data) D output,t The reprojected position of each slice in D input,t,i,j,k is the original remote sensing data (i.e. input data) D input,t The corresponding position information (i, j, k) in , Lookup is the search function, and T is the position correspondence matrix; The search function takes the position information of any grid in the output data as input, brings it into the position correspondence matrix T, determines its corresponding grid position in the original remote sensing data, and then obtains the data value of each corresponding slice.

[0028] The following uses the batch reprojection of MODIS snow cover data in a certain area as an example to illustrate the solution of the present invention: the input data is the MODIS daily snow cover data product with a resolution of 500 meters. The area is covered by 8 slices every day, and each slice file has 2400 rows and 2400 columns. The 8 slice files of the area are reprojected every day, that is, the original MODIS Sinusoidal sinusoidal projection coordinate system is transformed into the Albers projection coordinate system of the same resolution (central meridian 105 degrees, first standard parallel 25 degrees, second standard parallel 47 degrees) and merged into one file.

[0029] By using traditional methods, such as using MODIS Reprojection Tool software to perform this operation, it takes 12 minutes; in contrast, after applying the method proposed in the present invention for batch reprojection, it only takes 6 seconds; this means that if 10 years of MODIS dual-satellite daily snow products need to be reprojected and resampled, the time required by the traditional method = 365*10*2*12 / 24 / 60≈60 days, while the time required by the present invention = 365*10*2*6 / 3600≈12 hours, that is, half a day; compared with the traditional method, the method proposed in the present invention greatly improves the efficiency of batch remote sensing data reprojection.

[0030] The above is a multi-slice remote sensing data reprojection method provided in one or more embodiments of this specification. Based on the same idea, this specification also provides a corresponding multi-slice remote sensing data reprojection device, including: An acquisition module, configured to acquire a plurality of slices of first remote sensing data during a reference period; A coordinate conversion module is used to convert the position information of multiple slices in the grid to obtain the reprojected positions of the multiple slices in the target coordinate system; wherein the conversion operation includes splicing, reprojection and resampling operations; A position correspondence matrix construction module is used to construct a position correspondence matrix based on the position information of multiple slices before the transformation operation and their reprojected positions in the target coordinate system; The determination module is used to determine the corresponding position information of the reprojected position of the slices in other time periods in the second remote sensing data through a lookup function based on the constructed position correspondence matrix, and obtain the data value of each slice in other time periods; wherein the second remote sensing data is the original remote sensing data obtained in other time periods.

[0031] The specific limitations of the multi-slice remote sensing data reprojection device can be found in the limitations of the multi-slice remote sensing data reprojection method described above and will not be further elaborated here. Each module within the multi-slice remote sensing data reprojection device can be implemented in whole or in part via software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor within a computer device in hardware form, or stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0032] The present invention also provides a computer-readable storage medium, which stores a computer program. The computer program can be used to execute the multi-slice remote sensing data reprojection method provided above.

[0033] The present invention also provides Figure 3 The structural diagram of the computer equipment shown in FIG. Figure 3As shown, at the hardware level, the computer device includes a processor, an internal bus, a network interface, memory, and non-volatile storage, and may also include other hardware required for operations. The processor reads the corresponding computer program from the non-volatile storage into the internal memory and then runs it to implement the multi-slice remote sensing data reprojection method provided in the above embodiment.

[0034] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

Claims

1. A multi-slice remote sensing data reprojection method, characterized in that: include: Acquire a plurality of slices of first remote sensing data during a reference period; Performing a conversion operation on the position information of the multiple slices in the grid to obtain reprojected positions of the multiple slices in the target coordinate system; wherein the conversion operation includes splicing, reprojection and resampling operations; Construct a position correspondence matrix based on the position information of multiple slices before the transformation operation and their reprojected positions in the target coordinate system; According to the constructed position correspondence matrix, the position information corresponding to the reprojected position of the slices in other time periods in the second remote sensing data is determined by a lookup function to obtain the data value of each slice in other time periods; wherein the second remote sensing data is the original remote sensing data obtained in other time periods.

2. The multi-slice remote sensing data reprojection method according to claim 1, wherein: The location information specifically includes: Slice index layer, row number layer, and column number layer.

3. The multi-slice remote sensing data reprojection method according to claim 2, wherein: The converting operation on the position information of the multiple slices in the grid to obtain the reprojected positions of the multiple slices in the target coordinate system specifically includes: M reproj =ReprojectAndResample(Merge({I i | i ∈ S}), CS orig →CS target , res orig →res target ); Among them, I i is the index or row and column number layer data of the i-th slice, S={1,2,...,n} is the slice set, Merge is the splicing function, CS orig is the coordinate system of the original first remote sensing data, CS target is the target coordinate system, res orig is the original resolution, res target is the target resolution, M reproj The tile index layer after the conversion operation.

4. The multi-slice remote sensing data reprojection method according to claim 1, wherein: The step of determining, based on the constructed position correspondence matrix, position information in the second remote sensing data corresponding to the reprojected position of slices in other time periods by using a lookup function specifically includes: The reprojected position of each slice is obtained using the following formula: D output,t,i′,j′,k′ =D input,t,i,j,k ; in, (i,j,k)=Lookup(T, (i′,j′,k′)); Among them, D output,t,i′,j′,k′ is the data D in the target coordinate system output,t The reprojected position of each slice in D input,t,i,j,k is the original remote sensing data D input,t The corresponding position information (i, j, k) in , Lookup is the search function, and T is the position correspondence matrix; The search function takes any reprojected position as input, brings it into the position correspondence matrix T, and determines its corresponding grid position information in the original remote sensing data.

5. A multi-slice remote sensing data reprojection device, characterized in that: include: An acquisition module, configured to acquire a plurality of slices of first remote sensing data during a reference period; A coordinate conversion module is used to convert the position information of multiple slices in the grid to obtain the reprojected positions of the multiple slices in the target coordinate system; wherein the conversion operation includes splicing, reprojection and resampling operations; A position correspondence matrix construction module is used to construct a position correspondence matrix based on the position information of multiple slices before the transformation operation and their reprojected positions in the target coordinate system; The determination module is used to determine the corresponding position information of the reprojected position of the slices in other time periods in the second remote sensing data through a lookup function based on the constructed position correspondence matrix, and obtain the data value of each slice in other time periods; wherein the second remote sensing data is the original remote sensing data obtained in other time periods.

6. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the multi-slice remote sensing data reprojection method according to any one of claims 1 to 4 is implemented.

7. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for reprojecting multi-slice remote sensing data according to any one of claims 1 to 4 is implemented.

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