Data processing method and device, equipment, storage medium and computer program product

Abstract

The invention provides a data processing method and apparatus, a device, a storage medium and a computer program product. The method comprises the steps of obtaining first vector data of a building; the first vector data comprises height data of the building; acquiring satellite remote sensing image parameter information corresponding to the building based on the first vector data; determining translation data corresponding to the building according to the satellite remote sensing image parameter information and the height data; and acquiring satellite remote sensing image data, and determining contour data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

Description

Technical Field

[0001] This application relates to the field of image extraction technology, and in particular to a data processing method, apparatus, device, storage medium, and computer program product. Background Technology

[0002] For applications in 3D modeling and 2D mapping, extracting data on building rooftops and facades is an important part of geographic information. Currently, deep learning methods are mainly used to extract building rooftops and facades from optical remote sensing data. However, deep learning methods are highly dependent on the quantity and quality of training sample data during training, have high computational resource requirements, and are affected by lighting and shadows, leading to inaccurate extracted data. Summary of the Invention

[0003] This application provides a data processing method, apparatus, device, storage medium, and computer program product that can improve the accuracy of extracted data.

[0004] To achieve the above objectives, the technical solution of this application is implemented as follows:

[0005] Firstly, this application proposes a data processing method, the method comprising:

[0006] Acquire first vector data of the building; the first vector data includes the height data of the building.

[0007] Based on the first vector data, obtain the satellite remote sensing image parameter information corresponding to the building;

[0008] The translation data corresponding to the building is determined based on the satellite remote sensing image parameter information and the height data;

[0009] The system acquires satellite remote sensing image data and determines the outline data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

[0010] In the above scheme, the satellite remote sensing image parameter information includes at least satellite side-swing angle information and satellite azimuth angle information; the step of determining the translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data includes:

[0011] The translation distance information corresponding to the building is determined based on the satellite side angle information and the height data;

[0012] The translation data is determined based on the translation distance information and the satellite azimuth angle.

[0013] In the above scheme, the contour data includes at least the roof contour data and the side elevation contour data of the building; determining the contour data of the building based on the first vector data and the translation data includes:

[0014] The roof outline data is determined based on the first vector data and the translation data;

[0015] The side facade contour data is determined based on the roof contour data and the first vector data.

[0016] In the above scheme, determining the roof outline data based on the first vector data and the translation data includes:

[0017] The first coordinate data of the first contour point of the bottom contour of the building is determined based on the first vector data;

[0018] The roof outline data is determined based on the translation data and the first coordinate data of the first outline point.

[0019] In the above scheme, determining the side facade contour data based on the roof contour data and the first vector data includes:

[0020] Based on the roof outline data, determine the second coordinate data of the second outline point of the roof outline;

[0021] The side elevation profile data is determined based on the first coordinate data and the second coordinate data determined from the first vector data.

[0022] In the above scheme, determining the side elevation contour data based on the first coordinate data and the second coordinate data determined from the first vector data includes:

[0023] The second vector data corresponding to the building is determined based on the first coordinate data and the second coordinate data;

[0024] The side facade contour data is determined based on the second vector data and the roof contour data.

[0025] In the above scheme, obtaining the satellite remote sensing image parameter information corresponding to the building based on the first vector data includes:

[0026] The first vector data is projected onto the first coordinate system to obtain the satellite remote sensing image parameter information.

[0027] Secondly, this application proposes a data processing apparatus, the apparatus comprising:

[0028] An acquisition unit is used to acquire first vector data of a building; the first vector data includes the height data of the building; and to acquire satellite remote sensing image parameter information corresponding to the building based on the first vector data.

[0029] The determining unit is configured to determine the translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data; acquire satellite remote sensing image data, and determine the outline data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

[0030] Thirdly, this application proposes a data processing apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0031] Fourthly, this application proposes a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0032] Fifthly, this application proposes a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the methods described above.

[0033] This application proposes a data processing method, apparatus, device, storage medium, and computer program product. The method includes: acquiring first vector data of a building; the first vector data includes the building's height data; acquiring satellite remote sensing image parameter information corresponding to the building based on the first vector data; determining translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data; acquiring satellite remote sensing image data, and determining the building's outline data from the satellite remote sensing image data based on the first vector data and the translation data. By adopting the above implementation scheme, the actual height data of the building is obtained through the building's first vector data, and the actual height data of the building is combined with the satellite remote sensing image parameter information. This fully utilizes the spatial geometric relationship of the building in the satellite remote sensing image, achieving accurate positioning of the building's outline data. This avoids the dependence on training data and the high computational resource requirements of deep learning. Furthermore, this application determines the building's outline data through the actual height data and satellite remote sensing image, eliminating the need to extract the building's outline and texture features, avoiding the influence of lighting and shadows, and thus improving the accuracy of the determined outline data. Attached Figure Description

[0034] Figure 1 A flowchart illustrating a data processing method provided in an embodiment of this application;

[0035] Figure 2A schematic diagram illustrating an exemplary translation of the bottom outline of a building, provided for an embodiment of this application;

[0036] Figure 3 A schematic diagram of an exemplary building roof outline provided for an embodiment of this application;

[0037] Figure 4 A schematic diagram of an exemplary building facade provided for an embodiment of this application;

[0038] Figure 5 A schematic diagram of an exemplary building side elevation provided for an embodiment of this application;

[0039] Figure 6 A schematic diagram illustrating the effect of an exemplary roof extraction provided in an embodiment of this application;

[0040] Figure 7 A schematic diagram illustrating the effect of an exemplary side elevation extraction provided in an embodiment of this application;

[0041] Figure 8 A schematic diagram of the bottom outline of a building in an exemplary scenario A provided for an embodiment of this application;

[0042] Figure 9 A schematic diagram of the roof outline of a building in an exemplary scenario A provided for an embodiment of this application;

[0043] Figure 10 A schematic diagram of the side elevation of a building in an exemplary scenario A provided for embodiments of this application;

[0044] Figure 11 A schematic diagram of the bottom outline of a building in an exemplary scenario B provided for embodiments of this application;

[0045] Figure 12 A schematic diagram of the roof outline of a building in an exemplary scenario B provided for embodiments of this application;

[0046] Figure 13 A schematic diagram of the side elevation of a building in an exemplary scenario B provided for embodiments of this application;

[0047] Figure 14 A flowchart illustrating an exemplary data processing method provided in this application embodiment;

[0048] Figure 15 A schematic diagram of the structure of a data processing device provided in this application;

[0049] Figure 16 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application. Detailed Implementation

[0050] In order to gain a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of this application.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0052] In the following description, references to "some embodiments" are made, which describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict. It should also be noted that the terms "first," "second," etc., used in the embodiments of this application are only used to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first," "second," etc., may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0053] This application provides a data processing method. Figure 1 This is a flowchart illustrating a data processing method provided in an embodiment of this application; as shown below. Figure 1 As shown, the method includes:

[0054] S101. Obtain the first vector data of the building; the first vector data includes the height data of the building.

[0055] It should be noted that in practical applications (such as 3D modeling and 2D mapping), building outline data is important geographic information data. The building can be understood as a structure within satellite remote sensing imagery. There can be one or more such buildings.

[0056] In this embodiment, the first vector data can be understood as the bottom vector data of the building. The process of obtaining the first vector data can be determined according to the actual situation and is not limited here. As an example, the bottom vector data can be obtained by querying the document data corresponding to the building. The first vector data includes at least height data, bottom outline data, bottom coordinate points, and coordinate data corresponding to the coordinate points. The height data can be understood as the actual height data of the building. In practical applications, the height data can be denoted as h, h∈[0,2π), and the unit is meters.

[0057] It should be noted that when there is only one building, the height data can be directly obtained from the first vector data of the building; when there are multiple buildings, the height data can be obtained from the first vector data of any one building in the first vector data of all buildings.

[0058] S102. Obtain satellite remote sensing image parameter information corresponding to the building based on the first vector data.

[0059] In this embodiment, satellite remote sensing image parameter information can be understood as the shooting parameter information of satellite remote sensing images. In practical applications, satellite remote sensing image parameter information includes at least satellite side angle information and satellite azimuth angle information. The process of obtaining satellite remote sensing image parameter information specifically includes: projecting the first vector data onto the first coordinate system to obtain the satellite remote sensing image parameter information.

[0060] The first coordinate system can be understood as the projection coordinate system of the satellite remote sensing image. Projecting the first vector data onto the first coordinate system to obtain the satellite remote sensing image parameter information can be understood as projecting the vector data of the building's bottom onto the projection coordinate system of the satellite remote sensing image to read the image's capture parameter information.

[0061] To facilitate understanding, the process of projecting the first vector data to the first coordinate system is illustrated here. The vector data is reprojected to the projection coordinate system of the satellite remote sensing image (because there will be some error between the vector data and the same point in the remote sensing image under different coordinate systems, which will lead to insufficient extraction accuracy). The specific operation is as follows: In the open source geographic information system desktop software (Quantum GIS, QGIS), select “Vector” -> “Data Management Tools” -> “Projection and Transformation” -> “Features” -> “Projection” in the menu bar. Then, in the pop-up “Projection” dialog box, select the projection coordinate system used by the satellite remote sensing image and click OK to complete the reprojection. Then, read the shooting parameters of the satellite remote sensing image, including the satellite side tilt angle α and the satellite azimuth angle θ.

[0062] The solution in this application uses the satellite side angle and satellite azimuth angle in the satellite remote sensing image parameter information as core parameters, and makes full use of the spatial geometric relationship of buildings in the remote sensing image, which facilitates the accurate positioning of the roof and facade by combining the bottom vector data carrying the building height data.

[0063] S103. Determine the translation data corresponding to the building based on satellite remote sensing image parameter information and height data.

[0064] In this embodiment of the application, the satellite remote sensing image parameter information includes at least satellite side-swing angle information and satellite azimuth angle information; the process of determining translation data specifically includes: determining the translation distance information corresponding to the building based on the satellite side-swing angle information and height data; and determining the translation data based on the translation distance information and satellite azimuth angle.

[0065] Among them, the satellite side-slip angle information can be understood as the angle of the satellite side-slip angle. In practical applications, the angle of the satellite side-slip angle can be denoted as α, where α ∈ [0, 2π). The satellite azimuth angle information can be understood as the angle of the satellite azimuth angle. In practical applications, the angle of the satellite azimuth angle can be denoted as θ, where θ ∈ [0, 2π). It should be noted that the angle of the satellite azimuth angle can undergo the transformation shown in formula (1), which is as follows:

[0066]

[0067] In this formula, the left side represents the acquired satellite azimuth information, and the right side represents the original satellite azimuth information, which can be obtained from the document data corresponding to the satellite remote sensing image.

[0068] It is understandable that translation distance information can be denoted as I in practical applications; translation data can be understood as translation vector, which can be denoted as (x,y) in practical applications.

[0069] The translation distance information corresponding to the building is determined based on the satellite side tilt angle information and height data. This can be understood as obtaining the translation distance according to the translation distance calculation formula (2), which is as follows:

[0070] I=h*tan(α) (2)

[0071] Where I represents translational distance information, h represents altitude data, and α represents satellite side tilt angle.

[0072] The translation data determined based on translation distance information and satellite azimuth can be expressed by formula (3), which is as follows:

[0073]

[0074] Where (x,y) represents translation data, I represents translation distance information, and θ represents satellite azimuth angle.

[0075] In this embodiment, the translation distance and translation vector are calculated using mathematical formulas, resulting in uniqueness and independent of the quality of satellite remote sensing images.

[0076] The solution of the embodiment of the present application calculates the translation distance and translation vector by using the spatial geometric relationship of buildings in remote sensing images and combining the building height, satellite side-sway angle, and satellite azimuth angle, which facilitates the extraction of building roofs and side facades based on the translation data and translation vector. It is not affected by factors such as light and shadow, and there is no need for complex computing resources to train a deep learning model, and the extraction result is more accurate.

[0077] S104. Obtain satellite remote sensing image data, and determine the contour data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

[0078] Among them, the satellite remote sensing image data can be understood as the data corresponding to the remote sensing image for which the contour data of the building needs to be determined.

[0079] In the embodiment of the present application, the contour data at least includes the roof contour data of the building and the side facade contour data of the building; the process of determining the contour data of the building based on the first vector data and the translation data specifically includes: determining the roof contour data based on the first vector data and the translation data; determining the side facade contour data according to the roof contour data and the first vector data.

[0080] Among them, the roof contour data can be understood as a set of contour coordinate points of the building roof; the side facade contour data can be understood as a set of side facades of the building; it should be noted that the side facades of the building include visible side facades and invisible side facades, and the side facade contour data includes the visible side facade contour data of the building and the invisible side contour facade data of the building.

[0081] It should be noted that the process of determining the roof contour data based on the first vector data and the translation data specifically includes: determining the first coordinate data of the first contour point of the bottom contour of the building according to the first vector data; determining the roof contour data based on the translation data and the first coordinate data of the first contour point.

[0082] Among them, the first contour point can be understood as the bottom contour point of the building, and the number of the first contour points can be one or more, and the specific number can be determined according to the first vector data. The first coordinate data can be understood as a set of contour points of the bottom contour. In practical applications, the first coordinate data can be recorded as D = {(x

[0083] , , i , y i ), 0 < i ≤ N + 1}, where i represents the number of the bottom contour point, and N represents the number of the bottom contour points of the building.

[0083] Determining the roof contour data based on the translation data and the first coordinate data of the first contour point can be understood as translating the first coordinate data according to the translation data, and constructing a closed polygon from the translated coordinate point set to obtain the roof contour data of the building. For the convenience of understanding, Figure 2 This application provides an exemplary schematic diagram of the translation of the bottom outline of a building; as shown. Figure 2 As shown, in practical applications, Figure 2 The building in the image is 51.95 meters high, the satellite azimuth is 280.074 degrees, the satellite side tilt is 18.14 degrees, and the calculated translation vector is (16.76, -2.98). Figure 2 In the middle (a), the first vector data is represented, which is the closed polygon constructed by the first contour points; Figure 2 In the middle (b), the roof outline data is represented by a closed polygon constructed from the coordinate points after translation.

[0084] In the embodiments of the application, the process of determining the side facade contour data based on the roof contour data and the first vector data specifically includes: determining the second coordinate data of the second contour points of the roof contour based on the roof contour data; and determining the side facade contour data based on the first coordinate data and the second coordinate data determined by the first vector data.

[0085] The second contour point can be understood as the roof contour point of the building; the number of the second contour points is the same as the number of the first contour points, and there is a one-to-one correspondence between the first contour points and the second contour points.

[0086] The second coordinate data can be understood as the set of coordinates of the roof outline points. In practical applications, the set of outline coordinate points of the roof outline data can be represented as: Where (x0, y0) represents translation data, i represents the nth bottom contour point, and N represents the number of bottom contour points of the building.

[0087] The second coordinate data of the second contour point of the roof contour determined based on the roof contour data can be understood as the set of coordinates of the roof contour point determined based on the roof contour data.

[0088] Determining the side elevation outline data based on the first coordinate data and the second coordinate data determined by the first vector data can be understood as determining the building's exterior facade data based on the first coordinate data and the second coordinate data, and subtracting the roof outline data from the exterior facade data to obtain the side elevation outline data; wherein, the building's exterior facade data can be formed by combining multiple single-sided views of the building drawn from the first coordinate data and the second coordinate data; the process of drawing a single-sided view of the building can be understood as obtaining any two outline point data from the first coordinate data, and obtaining two corresponding outline point data from the second coordinate data, and drawing these four outline point data into a closed quadrilateral, which is the single-sided view of the building.

[0089] In the embodiments of this application, the process of determining the side elevation outline data based on the first coordinate data and the second coordinate data determined by the first vector data specifically includes: determining the second vector data corresponding to the building based on the first coordinate data and the second coordinate data; and determining the side elevation outline data based on the second vector data and the roof outline data.

[0090] The second vector data can be the exterior facade data of the building. Determining the second vector data corresponding to the building based on the first coordinate data and the second coordinate data can be understood as merging the first coordinate data of two first contour points and the second coordinate data of the corresponding two second contour points into a single side data of the building, merging all the first contour points and the second contour points into multiple side data in the above method, and merging the multiple side data into the second vector data.

[0091] The side elevation outline data is determined based on the second vector data and the roof outline data. This can be understood as follows: after erasing the roof outline data from the second vector data, what remains is the side elevation outline data.

[0092] For ease of understanding, here's an example: Reconstructing the building's side elevation based on the roof and base outlines allows us to abstract the building as a simple cube, as shown in the image. The building's side elevation can be considered as the cube's lateral face; that is, the set of outline points for a single side of the building is... Where, p i ,p i+1 ∈D, i represents the nth bottom contour point, N represents the number of bottom contour points of the building, and D represents the set of bottom contour points of the building. This represents the set of points representing the roof outline of a building. By drawing four points from each set as a closed quadrilateral, a single side view of the building can be obtained.

[0093] For ease of understanding, Figure 3 A schematic diagram of an exemplary building roof outline provided for embodiments of this application; as shown Figure 3 As shown, P1, P2, P3, P4, P5, P6, P7, P8, P9, P 10 P 11 P 12 P 13 and P 14 Represents the outline points at the base of the building. and Points representing the outline of the building's roof. These are the contour points after P1 has been translated. These are the contour points after P2 has been translated. These are the contour points after P3 has been translated. These are the contour points after P4 has been translated. These are the contour points after P5 has been translated. These are the contour points after P6 has been translated. These are the contour points after P7 has been translated. These are the contour points after P8 has been translated. These are the contour points after P9 has been translated. It is P 10 The translated contour points It is P 11 The translated contour points It is P 12 The translated contour points It is P 13 The translated contour points It is P 14 After translation, the contour points P1, P2, A closed quadrilateral drawn with four points is a single side of a building.

[0094] It should be noted that in remote sensing imagery, due to obstruction from other side facades or building tops, building side facades can be divided into visible and invisible side facades. Therefore, the set of side facades is... Where S is the set of side elevations, i represents the nth bottom outline point, N represents the number of bottom outline points of the building, and P i This represents the set of outline points on a single side of a building. This represents the set of points representing the roofline of a building. For ease of understanding, Figure 4 A schematic diagram of an exemplary building facade provided for an embodiment of this application; as shown Figure 4 As shown, the building's side elevation is the data obtained by merging multiple sides constructed from all contour points, such as P1, P2, etc. Four points constitute the side profile of a single building: P2, P3, and P2. Four points constitute the side profile of a single building, P3, P4. Four points constitute the side profile of a single building, P4, P5. Four points form the side of a single building. By sequentially combining all the outline points, a single building side is formed. Combining all the single building sides forms the building facade.

[0095] Understandably, by erasing the vector plane of the top of the building from the vector plane of the merged side facades of the target building, the vector plane of the building's side facades can be obtained. Figure 5 A schematic diagram of an exemplary building side elevation provided for an embodiment of this application; as shown Figure 5 As shown, Figure 5 The outline constructed by part (a) is the side facade of the building.

[0096] For ease of understanding, Figure 6This application provides an exemplary schematic diagram illustrating the effect of roof extraction, as shown in the embodiment. Figure 6 As shown, Figure 6 The outline constructed by parts (a), (b), (c), (d), (e), (f), (g), (h), (i), and (j) is the roof of the building; Figure 7 This application provides an exemplary schematic diagram illustrating the effect of side elevation extraction, as shown in the embodiment. Figure 7 As shown, Figure 7 The outlines constructed from parts (a), (b), (c), (d), (e), (f), (g), (h), (i), and (j) constitute the side elevation of the building. For ease of understanding, an example image showing the extracted roof and side elevation of the building in scene A is provided below. Figure 8 This is a schematic diagram of the bottom outline of a building in an exemplary scenario A provided in this application embodiment. Figure 9 This is a schematic diagram of the roof outline of a building in an exemplary scenario A provided in this application embodiment. Figure 10 This is an exemplary schematic diagram of the side elevation outline of a building in scenario A, provided for an embodiment of this application. Alternatively, an example of the extracted roof and side elevation of a building in scenario B can also be shown. Figure 11 This is a schematic diagram of the bottom outline of a building in an exemplary scenario B provided in this application embodiment. Figure 12 This is a schematic diagram of the roof outline of a building in an exemplary scenario B provided in this application embodiment. Figure 13 This is a schematic diagram of the side elevation of a building in an exemplary scenario B provided for an embodiment of this application.

[0097] The solution in this application embodiment extracts the side facade based on the edge contours of the building's bottom and top, resulting in more stable extraction results.

[0098] For ease of understanding, the data processing method in practical applications can be exemplified as a method for extracting roof and side facades based on building height and bottom vectors. Figure 14 A flowchart illustrating an exemplary data processing method provided in this application embodiment; as shown Figure 14 As shown:

[0099] 1. Obtain the vector of the building's bottom.

[0100] It should be noted that the building bottom vector can be understood as obtaining the building bottom vector data.

[0101] 2. Obtain remote sensing imagery information.

[0102] It should be noted that the remote sensing imagery information includes the satellite side angle and the satellite azimuth angle.

[0103] 3. Obtain the height data of a single building based on the vector at the bottom of the building.

[0104] 4. Calculate the translation azimuth angle based on the height data of a single building and the information captured by remote sensing images.

[0105] It should be noted that the translation azimuth angle can be understood as the translation distance information mentioned above.

[0106] 5. Calculate the translation length based on the translation azimuth angle and remote sensing image information.

[0107] It should be noted that this translation length can be understood as the translation data mentioned above, i.e., the translation vector.

[0108] 6. Locate the building roof based on the translation length and the building bottom vector.

[0109] It should be noted that the building roof data is determined based on the translation length and the building bottom vector, thereby realizing the building roof positioning.

[0110] 7. Reconstruct the side elevation of the building based on the translation process between the bottom vector of the building and the roof of the building.

[0111] It should be noted that the side facade of the building is restored based on the translation process from the bottom vector of the building to the roof data in the building roof positioning.

[0112] 8. Output the data for the building's roof and side facade.

[0113] The solution in this application does not require complex computing resources to train the deep learning model, making it highly applicable. It does not require extracting the roof and facade contours of buildings, thus it is unaffected by factors such as lighting and shadows. Facade extraction based on the edge contours of the building's base and top results in more stable extraction results. Furthermore, it effectively avoids the poor generalization limitations of algorithms caused by the diversity of remote sensing imagery, and requires no training set. For any high-resolution remote sensing image, it can quickly, accurately, and automatically locate the roof boundaries and side facade contours of buildings, effectively improving the efficiency and accuracy of urban 3D modeling and geographic information acquisition.

[0114] This application provides a data processing apparatus. Figure 15 A schematic diagram of the structure of a data processing device provided in this application; as shown Figure 15 As shown, the data processing apparatus 1500 includes:

[0115] Acquisition unit 1501 is used to acquire first vector data of a building; the first vector data includes the height data of the building; and acquire satellite remote sensing image parameter information corresponding to the building based on the first vector data.

[0116] The determining unit 1502 is used to determine the translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data; acquire satellite remote sensing image data, and determine the outline data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

[0117] Optionally, the satellite remote sensing image parameter information includes at least satellite side-swing angle information and satellite azimuth angle information; the determining unit 1502 is further configured to determine the translation distance information corresponding to the building based on the satellite side-swing angle information and the height data; and to determine the translation data based on the translation distance information and the satellite azimuth angle.

[0118] Optionally, the contour data includes at least the roof contour data and the side elevation contour data of the building; the determining unit 1502 is further configured to determine the roof contour data based on the first vector data and the translation data; and to determine the side elevation contour data based on the roof contour data and the first vector data.

[0119] Optionally, the determining unit 1502 is further configured to determine the first coordinate data of the first contour point of the bottom contour of the building based on the first vector data; and to determine the roof contour data based on the translation data and the first coordinate data of the first contour point.

[0120] Optionally, the determining unit 1502 is further configured to determine second coordinate data of the second contour point of the roof contour based on the roof contour data; the first contour point corresponds to the second contour point; and determine the side facade contour data according to the first coordinate data determined by the first vector data and the second coordinate data.

[0121] Optionally, the determining unit 1502 is further configured to determine the second vector data corresponding to the building based on the first coordinate data and the second coordinate data; and to determine the side facade contour data based on the second vector data and the roof contour data.

[0122] Optionally, the acquisition unit 1501 is further configured to project the first vector data onto the first coordinate system to obtain the satellite remote sensing image parameter information.

[0123] This application also provides a data processing device. Figure 16 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application; as shown below. Figure 16 As shown, the data processing device 1600 includes a processor 1601 and a memory 1603. Optionally, the data processing device 1600 may also include a communication bus 1602.

[0124] In specific embodiments, the processor 1601 can be at least one of the following: Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), CPU, controller, microcontroller, and microprocessor. It is understood that for different devices, the electronic device used to implement the processor function can also be other types, and this embodiment does not impose specific limitations.

[0125] In this embodiment, the communication bus 1602 is used to establish communication between the processor 1601 and the memory 1603; when the processor 1601 executes the running program stored in the memory 1603, it implements the following data processing method:

[0126] Acquire first vector data of the building; the first vector data includes the height data of the building; acquire satellite remote sensing image parameter information corresponding to the building based on the first vector data; determine the translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data; acquire satellite remote sensing image data, and determine the outline data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

[0127] Furthermore, the satellite remote sensing image parameter information includes at least satellite side-swing angle information and satellite azimuth angle information; the processor 1601 is also used to determine the translation distance information corresponding to the building based on the satellite side-swing angle information and the height data; and to determine the translation data based on the translation distance information and the satellite azimuth angle.

[0128] Furthermore, the contour data includes at least the roof contour data and the side elevation contour data of the building; the processor 1601 is also configured to determine the roof contour data based on the first vector data and the translation data; and to determine the side elevation contour data based on the roof contour data and the first vector data.

[0129] Furthermore, the processor 1601 is also configured to determine the first coordinate data of the first contour point of the bottom contour of the building based on the first vector data; and to determine the roof contour data based on the translation data and the first coordinate data of the first contour point.

[0130] Furthermore, the processor 1601 is also configured to determine second coordinate data of the second contour points of the roof contour based on the roof contour data; and to determine the side facade contour data based on the first coordinate data determined by the first vector data and the second coordinate data.

[0131] Furthermore, the processor 1601 is also configured to determine the second vector data corresponding to the building based on the first coordinate data and the second coordinate data; and to determine the side facade contour data based on the second vector data and the roof contour data.

[0132] Furthermore, the processor 1601 is also used to project the first vector data onto the first coordinate system to obtain the satellite remote sensing image parameter information.

[0133] This application provides a storage medium storing a computer program thereon. The computer-readable storage medium stores one or more programs, which can be executed by one or more processors. The computer program implements the data processing method described above.

[0134] Based on the above embodiments, this application provides a computer program product, including a computer program that can be executed by one or more processors, and the computer program implements the data processing method described above.

[0135] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0136] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the related technology, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause an image display device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this disclosure.

[0137] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application.

Claims

1. A data processing method, characterized in that, The method includes: Acquire first vector data of the building; the first vector data includes the height data of the building. Based on the first vector data, obtain the satellite remote sensing image parameter information corresponding to the building; The translation data corresponding to the building is determined based on the satellite remote sensing image parameter information and the height data; The system acquires satellite remote sensing image data and determines the outline data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

2. The method according to claim 1, characterized in that, The satellite remote sensing image parameter information includes at least satellite side-swing angle information and satellite azimuth angle information; the step of determining the translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data includes: The translation distance information corresponding to the building is determined based on the satellite side angle information and the height data; The translation data is determined based on the translation distance information and the satellite azimuth angle.

3. The method according to claim 1, characterized in that, The contour data includes at least the roof contour data and the side elevation contour data of the building; determining the contour data of the building based on the first vector data and the translation data includes: The roof outline data is determined based on the first vector data and the translation data; The side facade contour data is determined based on the roof contour data and the first vector data.

4. The method according to claim 3, characterized in that, Determining the roof outline data based on the first vector data and the translation data includes: The first coordinate data of the first contour point of the bottom contour of the building is determined based on the first vector data; The roof outline data is determined based on the translation data and the first coordinate data of the first outline point.

5. The method according to claim 3, characterized in that, Determining the side facade contour data based on the roof contour data and the first vector data includes: Based on the roof outline data, determine the second coordinate data of the second outline point of the roof outline; The side elevation profile data is determined based on the first coordinate data and the second coordinate data determined from the first vector data.

6. The method according to claim 5, characterized in that, Determining the side elevation contour data based on the first coordinate data determined from the first vector data and the second coordinate data includes: The second vector data corresponding to the building is determined based on the first coordinate data and the second coordinate data; The side facade contour data is determined based on the second vector data and the roof contour data.

7. The method according to claim 1, characterized in that, The step of obtaining satellite remote sensing image parameter information corresponding to the building based on the first vector data includes: The first vector data is projected onto the first coordinate system to obtain the satellite remote sensing image parameter information.

8. A data processing apparatus, characterized in that, The device includes: An acquisition unit is used to acquire first vector data of a building; the first vector data includes the height data of the building; and to acquire satellite remote sensing image parameter information corresponding to the building based on the first vector data. The determining unit is configured to determine the translation data corresponding to the building based on the satellite remote sensing image parameter information and the height data; acquire satellite remote sensing image data, and determine the outline data of the building from the satellite remote sensing image data based on the first vector data and the translation data.

9. A data processing device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the method according to any one of claims 1-7.

10. A storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1-7.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.

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