A method, device, equipment and medium for seamless splicing and fusion of surveying and mapping data

Abstract

The embodiment of the present invention provides a method, device, equipment and medium for seamless splicing and fusion of surveying and mapping data, including: obtaining a digital elevation model DEM that needs to be spliced ​​and fused, and marking the digital elevation model DEMs of different data sources as DEMa and DEMb respectively; obtaining a first area △DEM0 with elevation difference data of DEMa and DEMb in the overlapping area; expanding the first area △DEM0 according to the data form of the buffer buffer to obtain a second area △DEM1; interpolating the second area △DEM1 through a moving window to obtain a third area △DEM2; restoring the third area △DEM2 to DEMb to obtain DEMb2; merging DEMb2 with DEMa to obtain fused data DEMc. By extracting the overlapping area boundary between DEMa and DEMb, expanding, interpolating and restoring the boundary, and splicing and fusion processing the obtained DEMb2 with the original DEMa. This splicing and fusion method can make the spliced ​​and fused data seamless at the overlapping boundary, and can completely eliminate the edge effect.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, equipment and medium for seamlessly splicing and fusing surveying and mapping data. Background Art

[0002] When integrating surveying and mapping data, the problem of splicing and fusion of multi-source data is often involved, such as the splicing and fusion of collected land elevation, island and reef elevation and ocean depth data; splicing and fusion of single-beam measurement data and multi-beam measurement data; splicing and fusion of data measured in different years; splicing and fusion of measurement data of different survey equipment; splicing and fusion of measured data and inversion data, etc. These data may have differences in resolution, measurement accuracy, and measurement vertical benchmark due to the influence of different factors such as measurement equipment, installation deviation, survey method, and processing method. If this is simply to merge these data together and then perform simple averaging or re-gridding processing, it is inevitable that the multi-source data will not be able to achieve a correct description of the consistency of land elevation and seabed topography. Especially in the overlapping areas of different source data, there will be different degrees of step-shaped anomalies or contour distortion phenomena, thus failing to achieve the integration effect required by the project.

[0003] In view of the problems existing in the fusion of DEM (Digit Elevation Model) from different data sources, many domestic scholars have proposed different technical solutions. However, these methods all have some shortcomings.

[0004] For example: 1. The fusion method is too simple

[0005] Regarding the DEM free splicing technology proposed by Yang Guoping [1], Su Yuanyuan [2], etc., in the overlapping area of ​​two DEMs A and B, if one has invalid data and the other has valid data, the valid data will replace the data in the overlapping area; if both have valid data, the data in the overlapping area will be determined by a simple method of choosing one from the other. The splicing result will have a step-like anomaly at the boundary of the overlapping area.

[0006] Yin Xiaodong et al. [4] unified the horizontal measurement datum, vertical measurement datum and format of multi-source data, and then merged them together to quickly reconstruct the DEM using the irregular triangulated network (TIN) method. Since the overlapping areas have not been corrected for differences, there is still the possibility of step anomalies after fusion.

[0007] 2. Requirements for overlapping boundaries

[0008] When Wang Mingsheng[3], Zheng Tuanjie[5] and others performed DEM splicing, they mainly considered the splicing of regular shapes such as strips or rectangular areas. That is, they first determined whether the two DEMs to be spliced ​​belong to up-and-down splicing or left-and-right splicing, and then adopted different splicing processes. At the same time, the existing splicing methods re-assign the data points in the entire overlapping area after performing an inverse distance weighted operation based on the distance to the two side boundaries. The wider the overlapping boundary, the more data points are re-assigned, and vice versa. In order to control the re-assignment range of the overlapping boundary, data clipping is required before splicing.

[0009] 3. Difficult to deal with projects with complex overlapping areas and low degree of automation

[0010] The fusion method proposed by Liu Shengxuan [6] requires preprocessing such as drawing overlapping lines, performing equidistant interpolation on overlapping lines, and extracting elevation values ​​at interpolation points before DEM splicing and fusion. All these steps need to be completed manually, with a low degree of automation. Moreover, if the overlapping area is complex, for example, for the splicing and fusion of non-full coverage multi-beam measurement data and regional background data, the overlapping lines are too complex and this method cannot perform well.

[0011] 4. The step-shaped anomaly at the fusion boundary is not completely resolved or the accuracy of the original data changes after fusion

[0012] The “remove-restore method” generally consists of three steps: first, subtract the two DBMs (DigitBathymetric Models) to be spliced ​​to obtain the residual value; second, process the residual value; and third, restore the processed residual value to the original DBM data. The second step is the key step. Different processing methods will achieve different results. Although Cheng Jianhua[7], Liu Yang[8], Fan Miao[9], etc. all used the “remove-restore method” to reconstruct and splice the seabed topography, they used different processing methods in the key second step and did not disclose the technical details in detail. For example, the second and third step processing methods of Cheng Jianhua[7] are “using tension splines to interpolate the difference data into 3”, and the interpolated difference data is added to the reference grid to obtain the final data set. ", and did not solve the problem of elevation step anomalies at the fusion boundary; Liu Yang's [8] second and third step processing method is "then the difference file is subjected to median filtering with a grid size of 1000m, and the filtered difference file is gridded into a difference grid with a resolution of 100m. Finally, the difference grid is superimposed and integrated with the merged water depth grid to obtain the fused DBM." The entire difference file is subjected to median filtering and then gridded, and finally superimposed and integrated into the merged water depth grid. This operation will cause the accuracy of the original data to change. For the problem of elevation step anomalies at the fusion boundary, the method adopted is "to eliminate the edge effect that occurs in the grid merging process, a transition zone is defined on one side of the high-resolution grid data. The width of the transition zone is at least 3 columns of grid points, and the specific range is determined according to the edge situation.

[0013] Its principle is based on the hyperbolic weighting function L represents the distance to the next high-resolution data constraint unit or the constraint unit outside the transition zone; w represents the weight. ", the problem is that the hyperbolic weighting function cannot completely eliminate the edge effect; the second and third processing methods of Fan Miao [9] are "using the nearest neighbor method to perform grid interpolation on the difference file, with a grid size of 1", and superimposing and merging the difference grid and the 1" benchmark grid data to form the final DBM after fusion". This method also does not solve the problem of elevation step anomalies at the fusion boundary.

[0014] The relevant references are as follows:

[0015] [1] Yang Guoping, Wang Mingxiao. Free splicing and visual inspection of DEM [J]. Journal of Surveying and Mapping Science and Technology, 2003, 20(4): 279-281;

[0016] [2] Su Yuanyuan. Free splicing of DEM and its raster conversion technology [J]. Military and Civilian Dual-Use Technology and Products, 2007, 20(6): 47-48;

[0017] [3] Wang Mingsheng, Li Yanping. Research on splicing and display of DEM with unequal grid spacing in strip areas [J]. Surveying and Mapping and Spatial Geographic Information, 2017, 40(12): 1-3;

[0018] [4] Yin Xiaodong, Guo Min, Yu Yanqing, et al. Coastal DEM data fusion based on multi-source data [J]. Journal of Dalian Maritime University, 2008, 34(2): 19-23;

[0019] [5] Zheng Tuanjie, Hu Jiasheng, Zhang Lihua, et al. Three-dimensional seamless splicing technology of multi-source data in coastal zone [J]. Marine Surveying and Mapping, 2008, 28(1): 28-31;

[0020] [6] Liu Shengxuan, Guan Yongxian, Wang Keping. A method for seamless splicing and fusion of multi-source DEM data[J]. Marine Surveying and Mapping, 2021, 41(4): 57-60;

[0021] [7] Cheng Jianhua, Huang Mengyuan, Ge Jingyu, et al. Research on seafloor topography construction method based on improved “remove-restore” algorithm[J]. Journal of Geo-Information Science, 2021, 23(3): 377-384;

[0022] [8] Liu Yang, Wu Ziyin, Zhao Dineng, et al. MF multi-source bathymetric data fusion method and ocean depth model construction [J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(9): 1171-1181.

[0023] [9] Fan Miao, Sun Yi, Xing Zhe, et al. High-precision seafloor topography reconstruction based on multi-source bathymetric data fusion [J]. Acta Oceanologica Sinica, 2017, 39(1): 130-137. Summary of the invention

[0024] In view of the above problems, embodiments of the present invention are proposed to provide a method for seamlessly splicing and fusing surveying and mapping data and a corresponding apparatus, device and medium for seamlessly splicing and fusing surveying and mapping data that overcome the above problems or at least partially solve the above problems.

[0025] In order to solve the above problems, an embodiment of the present invention discloses a method for seamless splicing and fusing surveying and mapping data, comprising:

[0026] Obtaining a digital elevation model DEM that needs to be spliced ​​and fused, and marking the digital elevation model DEMs from different data sources as DEMa and DEMb, respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb;

[0027] Acquire a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area;

[0028] The data format of the buffer buffer is preset, and the first area △DEM0 is extended according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 within the extended buffer area is a null value;

[0029] Setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2;

[0030] Restoring the third area △DEM2 onto the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area;

[0031] The DEMb2 is merged with the DEMa to obtain fused data DEMc; wherein the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

[0032] Furthermore, before performing the step S2, the step further includes preprocessing the DEMa and the DEMb;

[0033] The pre-processing comprises:

[0034] When the resolution of the DEMb is lower than that of the DEMa, the resolution of the DEMa is used as a reference value to re-interpolate and sample the resolution of the DEMb so that the resolutions of the DEMb and the DEMa are consistent;

[0035] And / or, unify the coordinate projection parameters of the DEMb and the DEMa.

[0036] Furthermore, the data format of △DEM0 is m×n, where m is the number of rows, n is the number of columns, and both m and n are positive integers;

[0037] The data format of the preset buffer buffer is used, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1 including:

[0038] According to the grid spacing of the rows and columns of the buffer buffer, the first area ΔDEM0 is expanded into the second area ΔDEM1 in the data form of (m+2*buffer)×(n+2*buffer).

[0039] Furthermore, the second region ΔDEM1 includes blank value nodes and non-blank value nodes.

[0040] Furthermore, the setting of the moving window and performing interpolation processing on the second area △ DEM1 through the moving window to obtain the third area △ DEM2 includes:

[0041] Traverse all nodes on the △DEM1 that meet the traversal conditions through the center point of the moving window;

[0042] Marking the corresponding node traversed by the center point of the moving window as a center node;

[0043] Establishing an interpolation expression between a plurality of valid data closest to the central node in the moving window;

[0044] Performing interpolation processing on the central node through the interpolation expression;

[0045] The traversal conditions include:

[0046] Each time the moving window is moved, the nodes covered in the moving window need to simultaneously meet the following two conditions: first, the corresponding node traversed by the center point of the moving window is the blank value node; second, the moving window contains the non-empty value node.

[0047] Furthermore, establishing an interpolation expression between a plurality of valid data closest to the central node in the moving window includes:

[0048]

[0049] Where D is the interpolated value;

[0050] n is the number of valid data involved in the interpolation calculation;

[0051] d is the value of a valid data point;

[0052] W(r) is the Gaussian weight function W(r i )=exp(-r i 2 / a 2 );

[0053] r is the distance from the valid data point to the point to be interpolated;

[0054] a is the relaxation factor of the weight function, which plays a role in adjusting the weight convergence speed.

[0055] A is the normalization factor, which ensures that the sum of all weights is equal to 1.

[0056] scale is the attenuation width of the Gaussian weight function, and the unit is the number of grid spacings; the closer the distance between the valid data and the central node to be interpolated is, the greater the impact will be, and the greater the weight assigned during the interpolation calculation.

[0057] Furthermore, the DEMb2 and the DEMa are merged to obtain the fused data DEMc including:

[0058] Loading the DEMa and the DEMb2 into GIS software;

[0059] When the data quality of the DEMa is higher than that of the DEMb2, the DEMa is placed on the upper layer of the DEMb2, and the DEMa and the DEMb2 are spliced ​​to obtain the DEMc.

[0060] The embodiment of the present invention discloses a surveying and mapping data seamless splicing and fusion device, comprising: a data acquisition module, used to acquire a digital elevation model DEM that needs to be spliced ​​and fused, and mark the digital elevation model DEMs of different data sources as DEMa and DEMb respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb;

[0061] A difference acquisition module, used for acquiring a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area;

[0062] The expansion module is used to preset the data format of the buffer buffer, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 in the expanded buffer area is a null value;

[0063] An interpolation processing module, used for setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2;

[0064] A restoration processing module, used for restoring the third area △DEM2 to the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area;

[0065] The merging output module is used to merge the DEMb2 and the DEMa to obtain fused data DEMc; wherein the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

[0066] An embodiment of the present invention discloses an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the above-mentioned method for seamless splicing and fusion of surveying and mapping data when executed by the processor.

[0067] An embodiment of the present invention provides a computer-readable storage medium, including a computer program stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method for seamlessly splicing and fusing surveying and mapping data as described above is implemented.

[0068] The embodiment of the present invention has the following advantages: the present invention extracts the boundary of the overlapping area between DEMa and DEMb, expands and interpolates the boundary to obtain △DEM2, then restores △DEM2 to the original DEMb to obtain a new DEMb2, then splices and fuses DEMb2 with the original DEMa, and outputs the fusion result. This splicing and fusion method can make the spliced ​​and fused data seamless (without steps) at the overlapping boundary, and can completely eliminate the edge effect.

[0069] At the same time, by setting a moving window and using the Gaussian distance weighted function to interpolate the nodes within the moving window, a smooth transition of the splicing boundary can be achieved, that is, the larger the moving window, the smoother the transition. In addition, only the data in the buffer after expansion processing is interpolated and corrected, and the data in the remaining areas do not need to be filtered or re-gridged, which maintains the accuracy of the original DEM to the greatest extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a flowchart of the steps of an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0071] Figure 2 It is a schematic diagram of a structural block diagram of an embodiment of a surveying and mapping data seamless splicing and fusion device of the present invention;

[0072] Figure 3 It is an electronic device of an embodiment of a method for seamlessly splicing and fusing surveying and mapping data of the present invention;

[0073] Figure 4 △ DEM0 schematic diagram of the first area of ​​an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0074] Figure 5 It is a schematic diagram of the second area △ DEM1 of an embodiment of a surveying and mapping data seamless splicing and fusion method of the present invention;

[0075] Figure 6It is a schematic diagram of Gaussian distance weighted function interpolation of △DEM1 in an extended buffer zone of an embodiment of a surveying and mapping data seamless splicing and fusion method of the present invention;

[0076] Figure 7 1 is a cross-sectional schematic diagram of an embodiment of a surveying and mapping data seamless splicing and fusion method of the present invention when obtaining △DEM0;

[0077] Figure 8 It is a cross-sectional schematic diagram of △DEM2 in an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0078] Fig. 9 It is a cross-sectional schematic diagram of DEMb2 of an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0079] Fig.10 It is a plane and cross-sectional effect diagram of DEMa and DEMb before fusion in an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0080] Fig.11 It is a plane effect diagram of △DEM0 of an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0081] Fig.12 It is a plane effect diagram of △DEM2 of an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention;

[0082] Fig.13 It is a plan and cross-sectional rendering of DEMc of an embodiment of a method for seamless splicing and fusion of surveying and mapping data of the present invention. DETAILED DESCRIPTION

[0083] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Percentages not specifically described in the present invention are all weight percentages / mass percentages.

[0084] Reference Figure 1-13 ,in, Figure 1 A flowchart of an embodiment of a method for seamlessly splicing and fusing surveying and mapping data of the present invention is shown, which may specifically include the following steps:

[0085] Obtaining a digital elevation model DEM that needs to be spliced ​​and fused, and marking the digital elevation model DEMs from different data sources as DEMa and DEMb, respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb;

[0086] Acquire a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area;

[0087] The data format of the buffer buffer is preset, and the first area △DEM0 is extended according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 within the extended buffer area is a null value;

[0088] Setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2;

[0089] Restoring the third area △DEM2 onto the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area;

[0090] The DEMb2 and the DEMa are merged to obtain the fused data DEMc; wherein, the data that the DEMc can present in the overlapping area are all the data presented by the DEMa in the overlapping area. It should be noted that the data quality difference in this embodiment mainly refers to the performance differences of instruments from different eras, which leads to differences in the resolution and accuracy of the collected data. The same data quality generally means that when the same set of instruments are measured in two adjacent areas in different years, it can be considered that the quality of DEMa and DEMb is basically the same.

[0091] The embodiment of the present application extracts the overlapping area boundary between DEMa and DEMb, expands and interpolates the boundary to obtain △DEM2, then restores △DEM2 to the original DEMb to obtain a new DEMb2, then splices and fuses DEMb2 with the original DEMa, and outputs the fusion result. This splicing and fusion method can make the spliced ​​and fused data seamless (without steps) at the overlapping boundary, and can completely eliminate the edge effect.

[0092] At the same time, by setting a moving window and using the Gaussian distance weighted function to interpolate the central nodes in the moving window, a smooth transition of the splicing boundary can be achieved, that is, the larger the moving window, the smoother the transition. In addition, only the data in the buffer after expansion processing is interpolated and corrected, and the data in the remaining areas do not need to be filtered or re-gridged, which maintains the accuracy of the original DEM to the greatest extent.

[0093] Next, a method for seamlessly splicing and fusing surveying and mapping data in this exemplary embodiment will be further described.

[0094] As an example, before performing the step S2, the step further includes preprocessing the DEMa and the DEMb;

[0095] The pre-processing comprises:

[0096] When the resolution of the DEMb is lower than that of the DEMa, the resolution of the DEMa is used as a reference value to re-interpolate and sample the resolution of the DEMb so that the resolutions of the DEMb and the DEMa are consistent;

[0097] And / or, unify the coordinate projection parameters of the DEMb and the DEMa. Specifically, since DEMa and DEMb are data from different data sources, they may be affected by different factors such as measurement equipment, installation deviation, survey method, processing method, etc., and there may be differences in resolution, measurement accuracy, measurement vertical benchmark, etc. In order to better perform data fusion processing on them, DEMa and DEMb need to be preprocessed before fusion processing. The preprocessing generally includes unifying coordinate projection parameters, unifying grid resolution, etc. In this embodiment, the data quality of DEMa is higher than that of DEMb, so at this time, the resolution of DEMa with higher data quality is used as a reference benchmark, and DEMb is re-interpolated and sampled so that the resolutions of DEMa and DEMb are consistent. It should be noted that since the coordinate projection parameters of data from different sources may be different, they must be converted and unified before splicing.

[0098] As an example, the data format of △DEM0 is m×n, where m is the number of rows, n is the number of columns, and both m and n are positive integers;

[0099] The data format of the preset buffer buffer is used, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1 including:

[0100] According to the grid spacing of the rows and columns of the buffer buffer, the first area △DEM0 is expanded into the second area △DEM1 in the data format of (m+2*buffer)×(n+2*buffer). Specifically, DEMa and DEMb are operated “AND” to obtain the first area △DEM0; that is, DEMa is subtracted from DEMb to obtain the first area △DEM0 with elevation difference data. Figure 4 As shown, △DEM0 is in the overlapping area of ​​DEMa and DEMb ( Figure 4 The grid node value is the elevation difference between DEMa and DEMb, and the nodes (circles) in the rest of the area are blank values.

[0101] According to the grid spacing values ​​of the rows and columns of the buffer buffer, △DEM0 is expanded: the elevation values ​​Z in the expanded buffer area of ​​the left and right boundaries of △DEM0 are all null values. The size of the new matrix is ​​(m+2*buffer)×(n+2*buffer), recorded as △DEM1. Since the elevation values ​​Z in the expanded buffer area are all null values, the reference Figure 5 In Figure 5, the triangulated point is the overlapping area of ​​DEMa and DEMb. The elevation value in this area is the difference between the two, that is, the non-null value node; the elevation value at the circle is null, that is, the blank value node. Set the elevation value Z in the extended buffer area to null. The purpose of this setting is to use the valid data within a certain range of the buffer for interpolation in the next step, so that the elevation value of each node in the buffer smoothly transitions from null value (equivalent to 0 value) to valid data value. It should be noted that the data format and size of the buffer buffer can be specified by the user, and the data unit of the buffer buffer is the grid spacing.

[0102] As an example, the setting of the moving window and performing interpolation processing on the second area △DEM1 through the moving window to obtain the third area △DEM2 includes:

[0103] Traverse all nodes on the △DEM1 that meet the traversal conditions through the center point of the moving window;

[0104] Marking the corresponding node traversed by the center point of the moving window as a center node;

[0105] Establishing an interpolation expression between a plurality of valid data closest to the central node in the moving window;

[0106] Performing interpolation processing on the central node through the interpolation expression;

[0107] The traversal conditions include:

[0108] Each time the moving window is moved, the nodes covered in the moving window need to meet the following two conditions at the same time: first, the corresponding node traversed by the center point of the moving window is the blank value node; second, the moving window contains the non-empty value node. Specifically, a moving window with a size of (2*buffer+1)×(2*buffer+1) grid spacing is constructed, and all nodes on △DEM1 are traversed with the center point of the moving window. Each time the moving window is moved, check whether the nodes covered in the moving window meet the following two conditions at the same time: first, the node corresponding to the center of the window is a null value; second, the moving window contains a non-empty value node. If both conditions are met, the center node is interpolated using several valid data closest to the center node in the moving window. The closer the distance between the valid data and the center node to be interpolated, the greater the impact, and the greater the weight assigned during the interpolation calculation.

[0109] As an example, establishing an interpolation expression between a plurality of valid data closest to the central node in the moving window includes:

[0110]

[0111] Where D is the interpolated value;

[0112] n is the number of valid data involved in the interpolation calculation;

[0113] d is the value of a valid data point;

[0114] W(r) is the Gaussian weight function W(r i )=exp(-r i 2 / a 2 );

[0115] r is the distance from the valid data point to the point to be interpolated;

[0116] a is the relaxation factor of the weight function, which plays a role in adjusting the weight convergence speed.

[0117] A is the normalization factor, which ensures that the sum of all weights is equal to 1.

[0118] Scale is the attenuation width of the Gaussian weight function, and the unit is the number of grid spacings; the closer the distance between the valid data and the central node to be interpolated is, the greater the impact is, and the greater the weight assigned during the interpolation calculation. Specifically, the central node to be interpolated in the extended buffer area of ​​△DEM1 mainly plays the role of smoothly transitioning the blank value node to the valid data point. The actual degree of smoothness depends on the size of the buffer buffer and the constant scale. The larger the two are, the smoother the transition is. Scale is usually set to 0.5. i is an intermediate variable in the loop program. In addition, it should be noted that in other embodiments, among the several valid data closest to the central node in the moving window, the number n of valid data will be limited. For example, when n is set to 5, when there are only 1-5 data in the moving window, all data are taken for interpolation; when the valid data in the moving window exceeds 5, only the 5 data closest to the central node are taken for interpolation.

[0119] As an example, the DEMb2 and the DEMa are merged to obtain the fused data DEMc including:

[0120] Loading the DEMa and the DEMb2 into GIS software;

[0121] When the data quality of the DEMa is higher than that of the DEMb2, the DEMa is placed on the upper layer of the DEMb2, and the DEMa and the DEMb2 are spliced ​​to obtain the DEMc. Specifically, △DEM2 is restored to DEMb to obtain DEMb2, that is, the addition operation of △DEM2 and DEMb is performed, DEMb+△DEM2=DEMb2, to obtain the restored DEMb2. The elevation value of the restored DEMb2 in the original overlapping area is completely consistent with the elevation value of DEMa in the original overlapping area, and DEMb2 achieves a seamless and smooth transition in the buffer area between the overlapping area. Adjust the layer order of DEMb2 and DEMa in the fusion software. The fusion software is generally GIS. Place the higher quality DEMa on the top layer and the restored DEMb2 on the bottom layer. Merge and output them as a DEMc to achieve seamless splicing and fusion of the two DEMs. It should be noted that when merging and outputting, the principle is "what you see is what you get", that is, what we can see on the computer screen is the result of the output. In the overlapping area of ​​DEMb2 and DEMa, since the high-quality DEMa is on the top layer, only the high-quality top layer data will be output, and the low-quality DEMb2 data on the lower layer will be discarded. In the area where DEMb2 and DEMa do not overlap, all the data of both will be output.

[0122] Reference Figure 2 , shows a schematic structural block diagram of an embodiment of a surveying and mapping data seamless splicing and fusion device of the present invention, which may specifically include the following modules:

[0123] A data acquisition module is used to acquire a digital elevation model DEM that needs to be spliced ​​and fused, and mark the digital elevation model DEMs from different data sources as DEMa and DEMb, respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb;

[0124] A difference acquisition module, used for acquiring a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area;

[0125] The expansion module is used to preset the data format of the buffer buffer, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 in the expanded buffer area is a null value;

[0126] An interpolation processing module, used for setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2;

[0127] A restoration processing module, used for restoring the third area △DEM2 to the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area;

[0128] The merging output module is used to merge the DEMb2 and the DEMa to obtain fused data DEMc; wherein the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

[0129] It should be noted that, for the method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present application are not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present application.

[0130] Among them, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0131] Reference Figure 3 In an embodiment of the present invention, the present invention further provides a computer device. The above-mentioned computer device 12 is expressed in the form of a general-purpose computing device. The components of the computer device 12 may include but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0132] The bus 18 represents one or more of several types of bus 18 structures, including a memory bus 18 or memory controller, a peripheral bus 18, an accelerated graphics port, a processor or a local bus 18 using any of a variety of bus 18 architectures. These architectures include, by way of example, but are not limited to, an Industry Standard Architecture (ISA) bus 18, a Micro Channel Architecture (MAC) bus 18, an Enhanced ISA bus 18, an Audio Video Electronics Standards Association (VESA) local bus 18, and a Peripheral Component Interconnect (PCI) bus 18.

[0133] Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including volatile and nonvolatile media, removable and non-removable media.

[0134] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 31 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write to non-removable, non-volatile magnetic media (commonly referred to as a "hard drive"). Although Figure 3 Not shown, a disk drive for reading and writing to a removable non-volatile disk (such as a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (such as a CD-ROM, DVD-ROM or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42, which are configured to perform the functions of various embodiments of the present invention.

[0135] A program / utility 41 having a set (at least one) of program modules 42 may be stored in, for example, a memory, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules 42, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0136] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, cameras, etc.), may communicate with one or more devices that enable a user to interact with the computer device 12, and / or may communicate with any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., local area networks (LANs)), wide area networks (WANs), and / or public networks (e.g., the Internet) via a network adapter 21. As shown, the network adapter 21 communicates with other modules of the computer device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the computer device 12, including, but not limited to, microcode, device drivers, redundant processing units 16, external disk drive arrays, RAID systems, tape drives, and data backup storage systems 34, etc.

[0137] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, such as implementing the method for seamless splicing and fusion of surveying and mapping data provided in the embodiment of the present invention.

[0138] That is, when the processing unit 16 executes the above program, the following is achieved: a data acquisition module is used to acquire the digital elevation model DEM that needs to be spliced ​​and fused, and mark the digital elevation model DEMs from different data sources as DEMa and DEMb respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb;

[0139] A difference acquisition module, used for acquiring a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area;

[0140] The expansion module is used to preset the data format of the buffer buffer, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 in the expanded buffer area is a null value;

[0141] An interpolation processing module, used for setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2;

[0142] A restoration processing module, used for restoring the third area △DEM2 to the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area;

[0143] The merging output module is used to merge the DEMb2 and the DEMa to obtain fused data DEMc; wherein the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

[0144] In an embodiment of the present invention, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method for seamless splicing and fusion of surveying and mapping data provided in all embodiments of the present application is implemented.

[0145] That is, when the program is executed by the processor, it implements: a data acquisition module, used to acquire the digital elevation model DEM that needs to be spliced ​​and fused, and mark the digital elevation model DEMs of different data sources as DEMa and DEMb respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb;

[0146] A difference acquisition module, used for acquiring a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area;

[0147] The expansion module is used to preset the data format of the buffer buffer, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 in the expanded buffer area is a null value;

[0148] An interpolation processing module, used for setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2;

[0149] A restoration processing module, used for restoring the third area △DEM2 to the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area;

[0150] The merging output module is used to merge the DEMb2 and the DEMa to obtain fused data DEMc; wherein the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

[0151] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPOM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device.

[0152] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0153] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0154] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0155] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, devices, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0156] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0160] Finally, 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 terminal 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 terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0161] The above is a detailed introduction to the method, device, equipment and medium for seamless splicing and fusion of surveying and mapping data provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for seamless splicing and fusion of surveying and mapping data, characterized in that: include: Obtaining a digital elevation model DEM that needs to be spliced ​​and fused, and marking the digital elevation model DEMs from different data sources as DEMa and DEMb, respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb; Acquire a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area; The data format of the buffer buffer is preset, and the grid spacing of the rows and columns of the buffer buffer is set to β, the first area △DEM0 is extended according to the data format of the buffer buffer to obtain the second area △DEM1, the second area △DEM1 includes blank value nodes and non-blank value nodes; wherein the elevation value Z of the second area △DEM1 in the extended buffer area is a null value; Setting a moving window, and interpolating the second region △DEM1 through the moving window to obtain the third region △DEM2, including: Traverse all nodes on the △DEM1 that meet the traversal conditions through the center point of the moving window; mark the corresponding nodes traversed by the center point of the moving window as center nodes; Establish an interpolation expression between several valid data closest to the central node in the moving window: Where D is the interpolated value; n is the number of valid data involved in the interpolation calculation; d is the value of a valid data point; W(r) is the Gaussian weight function W(r i )=exp(-r i 2 / a 2 ); r is the distance from the valid data point to the point to be interpolated; a is the relaxation factor of the weight function, which plays a role in adjusting the weight convergence speed; β is the grid spacing of rows and columns of the buffer buffer; A is the normalization factor, which ensures that the sum of all weights is equal to 1; scale is the attenuation width of the Gaussian weight function, and the unit is the number of grid spacings; the closer the distance between the valid data and the central node to be interpolated is, the greater the impact will be, and the greater the weight assigned during the interpolation calculation; Performing interpolation processing on the central node through the interpolation expression; The traversal conditions include: When the moving window is moved each time, the nodes covered in the moving window need to meet the following two conditions at the same time: first, the corresponding node traversed by the center point of the moving window is the blank value node; second, the moving window contains the non-empty value node; Restoring the third area △DEM2 onto the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area; The DEMb2 is merged with the DEMa to obtain fused data DEMc; wherein, the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

2. The method for seamless splicing and fusion of surveying and mapping data according to claim 1, characterized in that: Before obtaining the first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area, the method further includes preprocessing the DEMa and the DEMb; The pre-processing comprises: When the resolution of the DEMb is lower than that of the DEMa, the resolution of the DEMa is used as a reference value to re-interpolate and sample the resolution of the DEMb so that the resolutions of the DEMb and the DEMa are consistent; And / or, unify the coordinate projection parameters of the DEMb and the DEMa.

3. The method for seamless splicing and fusion of surveying and mapping data according to claim 1, characterized in that: The data format of △DEM0 is m×n, where m is the number of rows and n is the number of columns, and both m and n are positive integers; The data format of the buffer buffer is preset, and the grid spacing of the rows and columns of the buffer buffer is set to β. The first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1 including: According to the data format of the preset buffer buffer, and setting the grid spacing of the rows and columns of the buffer buffer to β, the first area △DEM0 is expanded into the second area △DEM1 with a data format of (m+2*β)×(n+2*β).

4. The method for seamless splicing and fusion of surveying and mapping data according to claim 1, characterized in that: The DEMb2 and the DEMa are merged to obtain the fused data DEMc including: Loading the DEMa and the DEMb2 into GIS software; When the data quality of the DEMa is higher than that of the DEMb2, the DEMa is placed on an upper layer of the DEMb2, and the DEMa and the DEMb2 are spliced ​​to obtain the DEMc.

5. A device for seamless splicing and fusion of surveying and mapping data, characterized in that: The method for seamlessly splicing and fusing surveying and mapping data according to any one of claims 1 to 4 comprises: A data acquisition module is used to acquire a digital elevation model DEM that needs to be spliced ​​and fused, and mark the digital elevation model DEMs from different data sources as DEMa and DEMb, respectively; wherein there is an overlapping area between the DEMa and the DEMb, and the data quality of the DEMa is higher than or equal to the data quality of the DEMb; A difference acquisition module, used for acquiring a first area △DEM0 with elevation difference data of the DEMa and the DEMb in the overlapping area; The expansion module is used to preset the data format of the buffer buffer, and the first area △DEM0 is expanded according to the data format of the buffer buffer to obtain the second area △DEM1; wherein the elevation value Z of the second area △DEM1 in the expanded buffer area is a null value; An interpolation processing module, used for setting a moving window, and performing interpolation processing on the second area △DEM1 through the moving window to obtain a third area △DEM2; A restoration processing module, used for restoring the third area △DEM2 to the DEMb to obtain DEMb2; wherein the elevation value of the DEMb2 in the overlapping area is consistent with the elevation value of the DEMa in the overlapping area; The merging output module is used to merge the DEMb2 and the DEMa to obtain fused data DEMc; wherein, the data that can be presented by the DEMc in the overlapping area are all the data presented by the DEMa in the overlapping area.

6. An electronic device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the method for seamless splicing and fusion of surveying and mapping data as described in any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium, characterized in that: The computer readable storage medium includes a computer program stored thereon, and when the computer program is executed by a processor, the method for seamless splicing and fusion of surveying and mapping data as described in any one of claims 1 to 4 is implemented.

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