Deformation image and DEM fusion method and electronic equipment

Abstract

The present invention provides a method and electronic device for fusing a deformable image with a DEM, comprising: obtaining digital elevation model data and deformable image data of a target area scene; converting the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems; obtaining pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model based on the first coordinate system, wherein the pixel points corresponding to the deformable image data store deformation information of the corresponding deformable image data; adding the deformation information to the pixel points of the corresponding point cloud data in the first coordinate system to update the point cloud data; and obtaining valid data in the updated point cloud data. The beneficial effects of the present invention are as follows: the error caused by coordinate conversion during data processing can be reduced, the fusion of radar deformation images and DEM can be realized, and the overall visualization effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of micro-variation radar image processing, and in particular to a deformation image and DEM fusion method and electronic equipment. Background Art

[0002] Ground-based Synthetic Aperture Radar (GB-SAR) is a new type of active microwave remote sensing technology. It achieves high-resolution imaging in the range direction by emitting large-bandwidth signals. At the same time, it achieves high-resolution imaging in the azimuth direction through synthetic aperture technology, realizing two-dimensional resolution imaging of the target area and achieving deformation monitoring with millimeter-level accuracy.

[0003] Digital Elevation Model (DEM) is a digital simulation of ground terrain through limited terrain elevation data. It uses drone photography to obtain model data to achieve on-site model reconstruction, providing on-site surface detail information and three-dimensional point cloud data of the observation area. Since the observation distance is far during the processing of radar deformation image data, the offset of the three coordinate directions in space during coordinate matching will bring significant errors. Its robustness and registration accuracy need to be further improved. Therefore, a method is needed to accurately realize the fusion of DEM data and GB-SAR deformation images to enhance the display effect. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the present invention provides a method and electronic device for fusing deformable images with DEM, which reduces the error caused by coordinate conversion during data processing by rotating the GB-SAR observation scene relative to the terrain coordinates and the position relationship in three coordinate directions of space, realizes the fusion of high-precision radar deformable images and DEM, and improves the overall visualization effect.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0006] The embodiment of the present invention provides a method for fusing a deformable image with a DEM, including:

[0007] Obtain digital elevation model data and deformation image data of the target area scene;

[0008] According to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems, the coordinate systems used by the digital elevation model data and the deformable image data are converted into a first coordinate system;

[0009] Based on the first coordinate system, acquiring pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model, wherein the pixel points corresponding to the deformable image data store corresponding deformation information of the deformable image data;

[0010] In the first coordinate system, adding deformation information to the pixel points of the point cloud data corresponding thereto to update the point cloud data;

[0011] Acquire valid data in the updated point cloud data.

[0012] Optionally, the converting the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems comprises:

[0013] Selecting a target point in the three-dimensional coordinate system of the digital elevation model data, and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data;

[0014] Determine a coordinate correspondence between the first coordinate information and the second coordinate information of the target point, wherein the second coordinate information is the coordinate information of the target point in the three-dimensional coordinate system;

[0015] Determining, according to the coordinate correspondence, a change amount between the digital elevation model data and the deformation image data in the first coordinate system;

[0016] Based on the change amount, the digital elevation model data and the deformable image data are matched into the first coordinate system.

[0017] Optionally, selecting a target point in the three-dimensional coordinate system of the digital elevation model data and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data includes:

[0018] The selected target point is expressed in the polar coordinate form in the two-dimensional coordinate system of the deformable image data. The corresponding expression is formula (1):

[0019]

[0020] Where R is the relative distance from point P to the radar, θ is the angle between the line from point P to the center of the radar and the X-axis, and z is the relative height from the target point to the horizontal plane of the radar position;

[0021] Accordingly, the determining of the coordinate correspondence between the first coordinate information and the second coordinate information of the target point includes: establishing the coordinate correspondence according to the physical conversion between the three-dimensional coordinate system of the digital elevation model data and the two-dimensional coordinate system of the deformation image data, which is expressed as formula (2):

[0022]

[0023] Wherein, the coordinate information of the target point (X, Y, Z) and the radar center (x0, y0, z0) in the three-dimensional coordinate system of the digital elevation model data is obtained, and based on the change amount, the change factor of the change amount is determined to be A;

[0024] Correspondingly, determining the amount of change between the digital elevation model data and the deformable image data in the first coordinate system according to the coordinate correspondence includes: establishing a two-dimensional coordinate system for the deformable image data, wherein the horizontal axis of the two-dimensional coordinate system is the slant range direction, and the vertical axis is the azimuth direction, and the relationship between the pixel point of the two-dimensional coordinate system of the deformable image data and the i-th pixel point in the first coordinate system is expressed by formula (3):

[0025]

[0026] Wherein, r and c are the horizontal axis and the vertical axis of the two-dimensional coordinate system, R0 is the observed near slant range of the deformation image data, θ0 is the starting angle, the spatial resolution in the slant range direction is ΔR, and the spatial resolution in the azimuth direction is Δθ;

[0027] Accordingly, matching the digital elevation model data and the deformable image data to the first coordinate system based on the change amount includes: determining the first coordinate information of the target point in the two-dimensional coordinate system of the deformable image data, substituting formula (1) and formula (3) to obtain corresponding data matched to the first coordinate system, which is expressed as formula (4):

[0028]

[0029] Among them, X i、 , Y i , Z i The deformable image data and the digital elevation model data are converted into coordinate information of the first coordinate system.

[0030] Optionally, the acquiring, based on the first coordinate system, pixel points corresponding to the deformation image data from the point cloud data of the digital elevation model includes:

[0031] Creating a geographic grid in the first coordinate system;

[0032] According to the geographic information contained in the geographic grid, searching point by point for pixel points corresponding to the deformed image data from the point cloud data of the digital elevation model;

[0033] When the pixel point is found, relevant information of the pixel point is obtained.

[0034] Optionally, in the first coordinate system, adding deformation information to a pixel point of the point cloud data corresponding thereto includes:

[0035] According to a geometric mapping relationship between pixel points in the point cloud data and corresponding pixel points in the deformed image data, the deformation information stored in the pixel points of the deformed image data is added to the pixel points of the point cloud data.

[0036] Optionally, the acquiring valid data in the updated point cloud data includes:

[0037] Acquire a valid boundary value of the deformed image data;

[0038] Based on the effective boundary value, determining the effective range of the deformation image data;

[0039] Clipping the digital elevation model data to the valid range in the deformation image data;

[0040] The point cloud data in the clipped digital elevation model data is determined as the valid data.

[0041] Optionally, the method further comprises:

[0042] Based on the valid data in the point cloud data, generating a corresponding target image;

[0043] The target image is output.

[0044] Optionally, the step of acquiring digital elevation model data of a target area scene and deformation image data based on GB-SAR includes:

[0045] The digital elevation model data and the deformation image data are subjected to image preprocessing to remove invalid interference data.

[0046] An embodiment of the present invention further provides an electronic device, including:

[0047] A first acquisition module is configured to acquire digital elevation model data and deformation image data of a target area scene;

[0048] a conversion module configured to convert the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems;

[0049] A second acquisition module is configured to acquire pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model based on the first coordinate system, wherein the pixel points corresponding to the deformable image data store corresponding deformation information of the deformable image data;

[0050] An updating module configured to add deformation information to the pixel points of the point cloud data corresponding thereto in the first coordinate system to update the point cloud data;

[0051] A generating module is configured to obtain valid data in the updated point cloud data.

[0052] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein an executable program is stored in the memory, and the processor processes the executable program to perform the following steps:

[0053] Obtain digital elevation model data and deformation image data of the target area scene;

[0054] According to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems, the coordinate systems used by the digital elevation model data and the deformable image data are converted into a first coordinate system;

[0055] Based on the first coordinate system, acquiring pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model, wherein the pixel points corresponding to the deformable image data store corresponding deformation information of the deformable image data;

[0056] In the first coordinate system, adding deformation information to the pixel points of the point cloud data corresponding thereto to update the point cloud data;

[0057] Acquire valid data in the updated point cloud data.

[0058] The present invention provides a deformation image and DEM fusion method and electronic equipment, which reduces the error caused by coordinate conversion during data processing through the rotation and position relationship of GB-SAR observation scene relative to terrain coordinates in three spatial coordinate directions, realizes the fusion of high-precision radar deformation image and DEM, and improves the overall visualization effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1A flow chart of a fusion method according to an embodiment of the present application;

[0060] Figure 2 For the embodiment of this application Figure 1 A flowchart of an embodiment of step S20;

[0061] Figure 3 A schematic diagram of a ground-based micro-variation radar observation model according to an embodiment of the present application;

[0062] Figure 4 A schematic diagram of radar deformation image coordinates according to an embodiment of the present application;

[0063] Figure 5 A flowchart of a specific embodiment of the fusion method of the embodiment of the present application;

[0064] Figure 6 A flowchart of an electronic device for the fusion method of an embodiment of the present application;

[0065] Figure 7 This is a flowchart of an electronic device of another embodiment of the fusion method of the embodiment of the present application. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0068] The present invention provides a deformation image and DEM fusion method and electronic equipment, which reduces the error caused by coordinate conversion during data processing through the rotation and position relationship of GB-SAR observation scene relative to terrain coordinates in three spatial coordinate directions, realizes the fusion of high-precision radar deformation image and DEM, and improves the overall visualization effect.

[0069] Combine the following Figures 1 to 4 The embodiments of the present invention are described in detail:

[0070] Embodiment 1:

[0071] The embodiment of the present invention provides a method for fusing a deformable image with a DEM.

[0072] Step S10, obtaining digital elevation model data and deformation image data of the target area scene.

[0073] In some embodiments of the present invention, by performing low-altitude operations using drones, a scene map of the target observation area can be obtained, and high-precision digital elevation model (DEM) data can be generated, which contains a variety of data (X, Y, Z, R, G, B, rows, columns).

[0074] In some exemplary embodiments, the ground-based synthetic aperture radar (GB-SAR) can realize all-day and all-weather ground observation by utilizing an active earth observation system and has a certain surface penetration capability. It can realize high-resolution imaging in the range direction by emitting large time-width bandwidth signals, and high-resolution imaging in the azimuth direction by using synthetic aperture technology, and can realize two-dimensional resolution imaging of the target area.

[0075] In some exemplary embodiments, the drone oblique photography model data can realize the reconstruction of the site model and provide detailed information of the site surface and three-dimensional point cloud data of the observation area.

[0076] In some exemplary embodiments, the high-precision digital elevation model (DEM) data acquired by the drone is preprocessed. Since the amount of point cloud data in the digital elevation model is relatively large, and there is some invalid interference data that affects the subsequent fusion, it is necessary to use computer mapping software to preprocess the digital elevation model to remove invalid and erroneous data.

[0077] In some exemplary embodiments, the deformation image data of the ground-based synthetic aperture radar (GB-SAR) is preprocessed. Since the resolution of the deformation image data of the ground-based synthetic aperture radar is significantly lower than the resolution of the high-precision digital elevation model (DEM) obtained by the drone, in order to determine the resolution fixed grid of the range and azimuth of the fusion model, the deformation image data of the ground-based synthetic aperture radar (GB-SAR) is usually completed by the one-dimensional difference of the two dimensions of azimuth and range.

[0078] Step S20: converting the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems.

[0079] In some embodiments of the present invention, since the deformation image data obtained by the ground-based synthetic aperture radar (GB-SAR) has a long observation distance during the processing, the error caused by coordinate conversion is more significant. Therefore, in order to fuse the terrain data and reduce the error caused by coordinate matching during data processing, it is necessary to consider the relative position in the three coordinate directions and the rotation between the two coordinate systems.

[0080] In some exemplary embodiments, the two coordinate systems are: a radar coordinate system, which is a two-dimensional coordinate system with the radar as the origin; and a geographic coordinate system, which is a three-dimensional coordinate system for the digital elevation model data acquired by the drone.

[0081] In some exemplary embodiments, see Figure 2 , step S20 further includes:

[0082] Step S201 : selecting a target point in the three-dimensional coordinate system of the digital elevation model data, and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data.

[0083] In some exemplary embodiments, see Figure 4 The relative position of any target point P in the observation area and the radar can be expressed as P(R,θ), where R is the relative distance from point P to the radar, θ is the angle between the line from point P to the center of the radar and the X-axis, the image origin is located in the upper left corner of an image, the horizontal axis of the coordinate points to the column direction (i.e., the slant range direction, with a spatial resolution of ΔR), and the vertical axis of the coordinate points to the row direction (i.e., the azimuth direction, with a spatial resolution of Δθ). The pixel position of the radar deformation image is represented by (row, col), where row and col represent the row and column of the image, respectively.

[0084] In some exemplary embodiments, assuming that the target point P is any point in the three-dimensional coordinate system of the digital elevation model data, the selected target point P is expressed in the polar coordinate form in the two-dimensional coordinate system of the deformable image data, and the corresponding expression is shown in formula (1):

[0085]

[0086] Among them, R is the relative distance from point P to the radar, θ is the angle between the line from point P to the center of the radar and the X-axis, and z is the relative height from the target point P to the horizontal plane of the radar position.

[0087] Step S202: determining a coordinate correspondence between the first coordinate information and the second coordinate information of the target point, wherein the second coordinate information is the coordinate information of the target point in the three-dimensional coordinate system.

[0088] In some exemplary embodiments, GPS measurement is used to obtain the coordinates of the point P (X, Y, Z) and the radar center (x0, y0, z0) in the geographic coordinate system.

[0089] In some exemplary embodiments, the change of the radar coordinate system relative to the geographic coordinate system in three directions of space is calculated to determine the coordinate change factor A.

[0090] Step S203: determining the amount of change between the digital elevation model data and the deformation image data in the first coordinate system according to the coordinate correspondence.

[0091] In some exemplary embodiments, a coordinate correspondence is established based on the physical conversion between the three-dimensional coordinate system of the digital elevation model data and the two-dimensional coordinate system of the deformation image data, which is expressed in the form of formula (2):

[0092]

[0093] Among them, the coordinate information of the target point (X, Y, Z) and the radar center (x0, y0, z0) in the three-dimensional coordinate system of the digital elevation model data is obtained, and based on the change amount, the change factor of the change amount is determined to be A.

[0094] In some exemplary embodiments, the radar uses a linear scanning GB-SAR system for deformation monitoring. The system forms a synthetic aperture by the uniform reciprocating motion of the antenna on a linear track. At the same time, the antenna sends and receives pulse signals in the direction perpendicular to the track (range direction), and uses pulse compression technology to achieve high resolution in the range direction. In the scenario along the direction of track motion (azimuth direction), the linear track motion is used to form a synthetic aperture, and the received electromagnetic wave signals are coherently processed to form high resolution in azimuth, thereby acquiring a two-dimensional high-resolution image of the observation area.

[0095] In some embodiments of the present invention, see Figure 3 , establish the radar coordinate system XOY with O as the origin, the starting angle of the observation area is θ0, the observation distance is R0, ΔR and Δθ are the resolutions of the radar image in azimuth and range respectively.

[0096] In some exemplary embodiments, a two-dimensional coordinate system of the deformable image data is established, wherein the horizontal axis of the two-dimensional coordinate system is the slant range direction, and the vertical axis is the azimuth direction. The two-dimensional coordinate system of the deformable image data and the i-th pixel point are expressed in the form of formula (3), which is specifically as follows:

[0097]

[0098] Among them, i is the pixel point of the target point in the first coordinate system, r and c are the horizontal axis and vertical axis of the two-dimensional coordinate system, R0 is the observed near slant range of the deformation image data, θ0 is the starting angle, the spatial resolution in the slant range direction is ΔR, and the spatial resolution in the azimuth direction is Δθ.

[0099] Step S204: matching the digital elevation model data and the deformation image data into the first coordinate system based on the change amount.

[0100] In some exemplary embodiments, the first coordinate information of the target point in the two-dimensional coordinate system of the deformable image data is determined, and formula (1) and formula (3) are substituted to obtain formula (4), which is expressed as:

[0101]

[0102] Among them, X i , Y i , Z i The deformable image data and the digital elevation model data are converted into coordinate information of the first coordinate system.

[0103] Step S30: based on the first coordinate system, obtaining pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model, wherein the pixel points corresponding to the deformable image data store corresponding deformation information of the deformable image data.

[0104] In some embodiments of the present invention, based on the first coordinate system, obtaining pixel points corresponding to the deformation image data from the point cloud data of the digital elevation model includes:

[0105] Create a geographic raster in the first coordinate system;

[0106] According to the geographic information contained in the geographic grid, the pixel points corresponding to the deformed image data are searched point by point from the point cloud data of the digital elevation model;

[0107] In some exemplary embodiments, a data set (geographic grid) with several pieces of geographic information is created, and pixel points corresponding to the radar deformation image are searched from the point cloud data of the digital elevation model in the same coordinate system.

[0108] In some exemplary embodiments, it is determined whether a pixel point in the point cloud data of the digital elevation model exists. If not, a point-by-point search is performed again for the next available pixel point.

[0109] Step S40: In the first coordinate system, the deformation information is added to the corresponding pixel points of the point cloud data to update the point cloud data.

[0110] In some embodiments of the present invention, when a pixel point is searched, the coordinate information of the radar deformation image data is geometrically mapped one by one to the pixel point according to the corresponding relationship established with the digital elevation model, and each pixel point is stored in the point cloud data of the digital elevation model. The deformation information in the radar deformation image data can be added to the point cloud data of the digital elevation model in an updated manner.

[0111] Step S50, obtaining valid data in the updated point cloud data.

[0112] In some embodiments of the present invention, obtaining valid data in the updated point cloud data includes:

[0113] Obtaining effective boundary values ​​of deformed image data;

[0114] Determine the effective range of the deformable image data based on the effective boundary value;

[0115] Clip the digital elevation model data to the valid range of the deformation image data;

[0116] The point cloud data in the clipped digital elevation model data is determined as valid data.

[0117] In some exemplary embodiments, since the digital elevation model (DEM) data of the target observation area acquired by the drone generally has a large scene, if a large amount of data from non-observation areas is also involved in the calculation, it will be time-consuming and affect the fluency. Therefore, it is necessary to search the row and column data in the various data (X, Y, Z, R, G, B, row, column) contained therein to find the maximum and minimum values ​​of the valid rows and columns that are as large as the radar deformation image matrix.

[0118] In some exemplary embodiments, during data processing, the radar deformation image data is used to set an edge threshold and reduce the search range to determine the effective range of the deformation image data.

[0119] In some exemplary embodiments, the digital elevation model (DEM) data will be cropped, the digital elevation model (DEM) data will be reduced to the same coverage as the geographic coordinate system where the radar deformation image is located, and each pixel point stores the point cloud data of the digital elevation model (DEM) and the radar deformation image data with a mapping relationship.

[0120] In some exemplary embodiments, point cloud data in clipped digital elevation model (DEM) data is determined as valid data.

[0121] In some exemplary embodiments, based on the valid data stored in the point cloud data of the digital elevation model (DEM), the two-dimensional deformation image of the ground-based synthetic aperture radar (GB-SAR) and the complete terrain data of the target area acquired by the drone are fused in the same coordinate system, and the fused image is output.

[0122] Embodiment 2:

[0123] An embodiment of the present invention provides an electronic device.

[0124] The first acquisition module is configured to acquire digital elevation model data and deformation image data of the target area scene; wherein, it is further configured as follows:

[0125] The digital elevation model data and the deformation image data are subjected to image preprocessing to remove invalid interference data.

[0126] A conversion module is configured to convert the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems; wherein it is further configured as follows:

[0127] Selecting a target point in the three-dimensional coordinate system of the digital elevation model data, and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data;

[0128] Determine a coordinate correspondence between the first coordinate information and the second coordinate information of the target point, wherein the second coordinate information is the coordinate information of the target point in the three-dimensional coordinate system;

[0129] Determining, according to the coordinate correspondence, a change amount between the digital elevation model data and the deformation image data in the first coordinate system;

[0130] Based on the change amount, the digital elevation model data and the deformable image data are matched into the first coordinate system.

[0131] The second acquisition module is configured to acquire pixel points corresponding to the deformed image data from the point cloud data of the digital elevation model based on the first coordinate system, wherein the pixel points corresponding to the deformed image data store deformation information of the corresponding deformed image data; wherein the second acquisition module is further configured to:

[0132] Creating a geographic grid in the first coordinate system;

[0133] According to the geographic information contained in the geographic grid, searching point by point for pixel points corresponding to the deformed image data from the point cloud data of the digital elevation model;

[0134] When the pixel point is found, relevant information of the pixel point is obtained.

[0135] An updating module is configured to add the deformation information to the pixel points of the point cloud data corresponding thereto in the first coordinate system to update the point cloud data; wherein the updating module is further configured as follows:

[0136] According to a geometric mapping relationship between pixel points in the point cloud data and corresponding pixel points in the deformed image data, the deformation information stored in the pixel points of the deformed image data is added to the pixel points of the point cloud data.

[0137] A generation module is configured to obtain valid data in the updated point cloud data; wherein, it is further configured to:

[0138] Acquire a valid boundary value of the deformed image data;

[0139] Based on the effective boundary value, determining the effective range of the deformation image data;

[0140] Clipping the digital elevation model data to the valid range in the deformation image data;

[0141] The point cloud data in the clipped digital elevation model data is determined as the valid data.

[0142] In some exemplary embodiments of the present application, an output module is also included, which is configured to generate a corresponding target image based on the valid data in the point cloud data and output the target image.

[0143] Embodiment three:

[0144] An embodiment of the present invention further provides an electronic device.

[0145] The system comprises a memory and a processor, wherein an executable program is stored in the memory and the processor processes the executable program, and the executable program executes any one of the fusion methods described above.

[0146] The present invention provides a deformation image and DEM fusion method and electronic equipment, which reduces the error caused by coordinate conversion during data processing through the rotation and position relationship of GB-SAR observation scene relative to terrain coordinates in three spatial coordinate directions, realizes the fusion of high-precision radar deformation image and DEM, and improves the overall visualization effect.

[0147] In some embodiments, the processor that executes the computer executable instructions may be a processing device including one or more general processing devices, such as a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), etc. More specifically, the processor may be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor that runs other instruction sets, or a processor that runs a combination of instruction sets. The processor may also be one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a system on a chip (SoC), etc.

[0148] In some embodiments, the computer-readable storage medium may be a memory such as a read-only memory (ROM), a random access memory (RAM), a phase-change random access memory (PRAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), an electrically erasable programmable read-only memory (EEPROM), other types of random access memory (RAM), a flash disk or other form of flash memory, a cache, a register, a static memory, a compact disk read-only memory (CD-ROM), a digital versatile disk (DVD) or other optical storage, a cassette or other magnetic storage device, or any other possible non-temporary medium used to store information or instructions that can be accessed by a computer device.

[0149] In some embodiments, the computer executable instructions may be implemented as a plurality of program modules, and the plurality of program modules together implement the medical image display method according to any one of the items of the present disclosure.

[0150] The present disclosure describes various operations or functions, which can be implemented as software codes or instructions or defined as software codes or instructions. The display unit can be implemented as a software code or instruction module stored on a memory, which can implement corresponding steps and methods when executed by a processor.

[0151] Such content may be source code or differential code ("delta" or "patch" code) that can be directly executed ("object" or "executable" form). The software implementation of the embodiments described herein may be provided by an article having code or instructions stored thereon, or by a method of operating a communication interface to send data through a communication interface. A machine or computer readable storage medium may enable a machine to perform the functions or operations described, and includes any mechanism for storing information in a form accessible by a machine (e.g., a computing display device, an electronic system, etc.), such as a recordable / unrecordable medium (e.g., a read-only memory (ROM), a random access memory (RAM), a disk storage medium, an optical storage medium, a flash memory display device, etc.). The communication interface includes any mechanism for interfacing with any of hardwired, wireless, optical, etc. media to communicate with other display devices, such as a memory bus interface, a processor bus interface, an Internet connection, a disk controller, etc. The communication interface may be configured by providing configuration parameters and / or sending signals to prepare the communication interface to provide a data signal describing the software content. The communication interface may be accessed by sending one or more commands or signals to the communication interface.

[0152] The computer executable instructions of the embodiments of the present disclosure can be organized into one or more computer executable components or modules. Any number and combination of such components or modules can be used to implement various aspects of the present disclosure. For example, various aspects of the present disclosure are not limited to the specific computer executable instructions or specific components or modules shown in the drawings and described herein. Other embodiments may include different computer executable instructions or components with more or less functions than those shown and described herein.

[0153] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of them) can be used in combination with each other. For example, a person of ordinary skill in the art can use other embodiments when reading the above description. In addition, in the above-mentioned specific embodiments, various features can be grouped together to simplify the present disclosure. This should not be interpreted as an intention that a disclosed feature that is not required to be protected is necessary for any claim. On the contrary, the subject matter of the present disclosure may be less than all the features of a specific disclosed embodiment. Thus, the following claims are incorporated into the specific embodiments as examples or embodiments, wherein each claim is independently used as a separate embodiment, and it is considered that these embodiments can be combined with each other in various combinations or arrangements. The scope of the present disclosure should be determined with reference to the attached claims and the full scope of equivalent forms granted by these claims.

[0154] The above embodiments are only exemplary embodiments of the present disclosure and are not intended to limit the present disclosure. The protection scope of the present disclosure is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present disclosure within the essence and protection scope of the present disclosure, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present disclosure.

Claims

1. The method for fusing deformable image and DEM is characterized by: include: Obtain digital elevation model data and deformation image data of the target area scene; According to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems, the coordinate systems used by the digital elevation model data and the deformable image data are converted into a first coordinate system; Based on the first coordinate system, acquiring pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model, wherein the pixel points corresponding to the deformable image data store corresponding deformation information of the deformable image data; In the first coordinate system, adding deformation information to the pixel points of the point cloud data corresponding thereto to update the point cloud data; Obtaining valid data in the updated point cloud data; wherein, The step of converting the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems comprises: Selecting a target point in the three-dimensional coordinate system of the digital elevation model data, and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data; Determine a coordinate correspondence between first coordinate information and second coordinate information of the target point, wherein the second coordinate information is coordinate information of the target point in the three-dimensional coordinate system; Determining, according to the coordinate correspondence, a change amount between the digital elevation model data and the deformation image data in the first coordinate system; Based on the change amount, the digital elevation model data and the deformable image data are matched into the first coordinate system.

2. The method according to claim 1, characterized in that The step of selecting a target point in the three-dimensional coordinate system of the digital elevation model data and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data includes: The selected target point is expressed in the polar coordinate form in the two-dimensional coordinate system of the deformable image data. The corresponding expression is formula (1): Where R is the relative distance from point P to the radar, θ is the angle between the line from point P to the center of the radar and the X-axis, and z is the relative height from the target point to the horizontal plane of the radar position; Accordingly, the determining of the coordinate correspondence between the first coordinate information and the second coordinate information of the target point includes: establishing the coordinate correspondence according to the physical conversion between the three-dimensional coordinate system of the digital elevation model data and the two-dimensional coordinate system of the deformation image data, which is expressed as formula (2): Wherein, the coordinate information of the target point (X, Y, Z) and the radar center (x0, y0, z0) in the three-dimensional coordinate system of the digital elevation model data is obtained, and based on the change amount, the change factor of the change amount is determined to be A; Correspondingly, determining the amount of change between the digital elevation model data and the deformable image data in the first coordinate system according to the coordinate correspondence includes: establishing a two-dimensional coordinate system for the deformable image data, wherein the horizontal axis of the two-dimensional coordinate system is the slant range direction, and the vertical axis is the azimuth direction, and the relationship between the pixel point of the two-dimensional coordinate system of the deformable image data and the i-th pixel point in the first coordinate system is expressed by formula (3): Wherein, r and c are the horizontal axis and the vertical axis of the two-dimensional coordinate system, R0 is the observed near slant range of the deformation image data, θ0 is the starting angle, the spatial resolution in the slant range direction is ΔR, and the spatial resolution in the azimuth direction is Δθ; Accordingly, matching the digital elevation model data and the deformable image data to the first coordinate system based on the change amount includes: determining the first coordinate information of the target point in the two-dimensional coordinate system of the deformable image data, substituting formula (1) and formula (3) into the first coordinate system to obtain the corresponding data matched to the first coordinate system, which is expressed in the form of formula (4): Among them, X i , Y i , Z i The deformable image data and the digital elevation model data are converted into coordinate information of the first coordinate system.

3. The method according to claim 1, characterized in that The acquiring, based on the first coordinate system, pixel points corresponding to the deformation image data from the point cloud data of the digital elevation model comprises: Creating a geographic grid in the first coordinate system; According to the geographic information contained in the geographic grid, searching point by point for pixel points corresponding to the deformed image data from the point cloud data of the digital elevation model; When the pixel point is found, relevant information of the pixel point is obtained.

4. The method according to claim 3, characterized in that: The step of adding the deformation information to the corresponding pixel points of the point cloud data in the first coordinate system includes: According to a geometric mapping relationship between pixel points in the point cloud data and corresponding pixel points in the deformed image data, the deformation information stored in the pixel points of the deformed image data is added to the pixel points of the point cloud data.

5. The method according to claim 1, characterized in that The obtaining of valid data in the updated point cloud data includes: Acquire a valid boundary value of the deformed image data; Based on the effective boundary value, determining the effective range of the deformation image data; Clipping the digital elevation model data to the valid range in the deformation image data; The point cloud data in the clipped digital elevation model data is determined as the valid data.

6. The method according to claim 1, characterized in that The method further comprises: Based on the valid data in the point cloud data, generating a corresponding target image; The target image is output.

7. The method according to claim 1, characterized in that The step of obtaining digital elevation model data and deformation image data of a target area scene includes: The digital elevation model data and the deformation image data are subjected to image preprocessing to remove invalid interference data.

8. An electronic device, characterized in that: include: A first acquisition module is configured to acquire digital elevation model data and deformation image data of a target area scene; a conversion module configured to convert the coordinate systems used by the digital elevation model data and the deformable image data into a first coordinate system according to the positional relationship between the digital elevation model data and the deformable image data and the corresponding relationship between the coordinate systems; A second acquisition module is configured to acquire pixel points corresponding to the deformable image data from the point cloud data of the digital elevation model based on the first coordinate system, wherein the pixel points corresponding to the deformable image data store corresponding deformation information of the deformable image data; An updating module configured to add deformation information to the pixel points of the point cloud data corresponding thereto in the first coordinate system to update the point cloud data; A generating module is configured to obtain valid data in the updated point cloud data; wherein, The conversion module is further configured as follows: Selecting a target point in the three-dimensional coordinate system of the digital elevation model data, and determining first coordinate information of the target point in the two-dimensional coordinate system of the deformation image data; Determine a coordinate correspondence between first coordinate information and second coordinate information of the target point, wherein the second coordinate information is coordinate information of the target point in the three-dimensional coordinate system; Determining, according to the coordinate correspondence, a change amount between the digital elevation model data and the deformation image data in the first coordinate system; Based on the change amount, the digital elevation model data and the deformable image data are matched into the first coordinate system.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores an executable program, and the executable program executes the method according to any one of claims 1 to 7.

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