Unmanned aerial vehicle image ortho-rectification method and device facing water surface

Abstract

The invention provides a water surface-oriented unmanned aerial vehicle image ortho-rectification method and device, which are applied to the technical field of unmanned aerial vehicle surveying and mapping, and the method comprises the following steps: obtaining an unmanned aerial vehicle image obtained by shooting a water surface area by an unmanned aerial vehicle; coordinate system conversion is carried out based on the longitude and latitude of the photography center, and plane coordinates of the photography center in a photography measurement coordinate system are obtained; determining a ground point coordinate of each pixel in the unmanned aerial vehicle image in the photogrammetry coordinate system according to a collinear equation based on the plane coordinate of the photogrammetry center and the unified water surface elevation value; constructing point cloud data of the unmanned aerial vehicle image based on the ground point coordinate of each pixel; determining a ground sampling distance based on the geodetic height of the unmanned aerial vehicle image, the unified water surface elevation value and the equivalent focal length of the unmanned aerial vehicle during shooting; and based on the ground sampling distance, carrying out orthographic rasterization processing on the point cloud data of the unmanned aerial vehicle image to obtain an image after orthographic correction. According to the invention, the defect of excessive dependence on ground feature points in the prior art is overcome.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) mapping technology, and in particular to a method and apparatus for orthorectifying UAV images facing the water surface. Background Technology

[0002] Drone aerial photography operations in nearshore waters and lakes face significant challenges due to the unique characteristics of these environments. Most areas lack distinct ground features in aerial photographs. While some areas may contain features such as aquaculture facilities, their sparse distribution and highly similar characteristics make it difficult for traditional feature point extraction and matching techniques to accurately obtain a sufficient number of reliable feature points. Using ground control points for auxiliary correction requires substantial manpower and resources for control point deployment, and the measurement and marking of these control points are extremely difficult in the complex aquatic environment.

[0003] However, most existing UAV image orthorectification technologies rely on the extraction and matching of feature points to establish the geometric relationship between the image and the real scene, thereby achieving image orthorectification.

[0004] Because nearshore waters cannot meet this technical requirement, a large number of UAV aerial photographs cannot be fully orthorectified, making it difficult to apply these images to actual marine surveying, environmental monitoring and other fields, resulting in a waste of data resources. Summary of the Invention

[0005] This invention provides a method and apparatus for orthorectifying UAV images facing the water surface, which solves the problem that existing UAV image orthorectification methods facing the water surface rely too much on ground feature points, thereby improving the spatial consistency of UAV images in water surface areas.

[0006] This invention provides a method for orthorectifying UAV images facing the water surface, comprising the following steps.

[0007] The process involves acquiring drone images of a water surface area taken by a drone along a preset flight path; performing coordinate system transformation based on the latitude and longitude of the drone image's camera center to obtain the planar coordinates of the camera center in a photogrammetric coordinate system; determining a uniform water surface elevation value for the water surface area; determining the ground point coordinates of each pixel in the drone image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the camera center, and the uniform water surface elevation value; constructing point cloud data of the drone image based on the ground point coordinates of each pixel; determining the ground sampling distance based on the geodetic height of the drone image, the uniform water surface elevation value, and the equivalent focal length of the drone during shooting; and performing orthorectified rasterization on the point cloud data of the drone image based on the ground sampling distance to obtain an orthorectified image.

[0008] According to the present invention, a method for orthorectifying UAV images facing a water surface is provided, wherein determining the uniform water surface elevation value of the water surface area includes: determining the uniform water surface elevation value of the water surface area based on the local horizontal plane and tidal height of the water surface area; The determination of the ground sampling distance based on the ground height of the UAV imagery, the unified water surface elevation value, and the equivalent focal length of the UAV during image capture includes: The ground sampling distance is determined using the following formula: ; in, Indicates the ground sampling distance, This indicates the elevation of the image from the drone. This represents the unified water surface elevation value. This indicates the equivalent focal length when the drone is taking the picture.

[0009] According to the present invention, an orthorectification method for UAV images facing a water surface is provided. The step of determining the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the image center, and the unified water surface elevation value includes: taking each pixel in the UAV image as the current pixel and determining the ground point coordinates of the current pixel according to the following formula. : ; ; in, This represents the x-coordinate of the current pixel in the photogrammetric coordinate system. This represents the ordinate of the current pixel in the photogrammetric coordinate system. The geodetic height representing the coordinates of the ground point. This indicates the elevation of the image from the drone. and These represent the x and y coordinates of the current pixel in the UAV image, respectively. and These represent the x-coordinate and y-coordinate of the optical center of the UAV image, respectively. and These represent the x-coordinate and y-coordinate of the photogrammetric center in the photogrammetric coordinate system, respectively; coefficients , , , , , , , , It is a rotation matrix The direction cosine element is used to describe the rotation relationship of the image space coordinate system of the UAV image relative to the photogrammetric coordinate system.

[0010] According to the present invention, an orthorectification method for UAV imagery facing a water surface is provided. The method involves orthorasterizing the point cloud data of the UAV imagery based on the ground sampling distance to obtain an orthorectified image. The steps include: determining the boundary of a regular grid based on the extreme values ​​of the x and y coordinates of all ground points in the point cloud data of the UAV imagery; determining the starting coordinates and number of grids for the regular grid based on the ground sampling distance and the boundary of the regular grid; constructing the regular grid based on the ground sampling distance, the starting coordinates, and the number of grids; interpolating the point cloud data of the UAV imagery based on the regular grid using a KD-tree-based nearest neighbor search and weighted interpolation algorithm to obtain an image attribute regular grid; and traversing the image attribute regular grid and solving for each element in the image attribute regular grid to obtain the orthorectified image.

[0011] According to the present invention, a method for orthorectifying UAV images facing the water surface is provided, wherein for any grid point in the regular grid, the interpolation weight of the arbitrary grid point is inversely proportional to the weight exponent of the distance to the neighboring point.

[0012] According to the present invention, an orthorectification method for UAV images facing a water surface is provided, wherein constructing the regular grid based on the ground sampling distance, the starting coordinates, and the number of grids includes: defining the regular grid. Each element Corresponding grid coordinates ,satisfy: ; ; ; in, The x-coordinate of the starting coordinates. This represents the x-coordinate index of the grid coordinates in the regular grid. Indicates the ground sampling distance, The ordinate represents the starting coordinate. This represents the y-coordinate index of the grid coordinates in the regular grid. Indicates the number of grid cells in the horizontal direction. Indicates the number of grid cells in the vertical direction.

[0013] This invention also provides an orthorectification device for UAV images facing a water surface, comprising the following modules: an acquisition module for acquiring UAV images taken by a UAV along a preset flight path over a water surface area; a conversion module for performing coordinate system conversion based on the latitude and longitude of the photographic center of the UAV image to obtain the planar coordinates of the photographic center in a photogrammetric coordinate system; a determination module for determining a uniform water surface elevation value for the water surface area; a point cloud module for determining the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photographic center, and the uniform water surface elevation value, and constructing point cloud data of the UAV image based on the ground point coordinates of each pixel; a distance module for determining the ground sampling distance based on the geodetic height of the UAV image, the uniform water surface elevation value, and the equivalent focal length of the UAV during shooting; and a correction module for performing orthorasterization processing on the point cloud data of the UAV image based on the ground sampling distance to obtain an orthorectified image.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for orthorectifying UAV images facing the water surface.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the orthorectification method for UAV images facing the water surface as described above.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for orthorectifying UAV images facing the water surface.

[0017] The present invention provides a method and apparatus for orthorectifying UAV images of water surfaces. By acquiring UAV images and flight parameters and performing coordinate system transformation based on the latitude and longitude of the photography center, it ensures the uniformity of spatial reference and the accuracy of geometric positioning. By setting a unified water surface elevation value, it effectively simplifies the elevation modeling process for water surfaces, which are approximate planes, and avoids calculation errors caused by complex terrain undulations. By combining collinearity equations and unified elevation, it calculates the coordinates of ground points pixel by pixel and constructs a point cloud, ensuring the fine expression of image geometric information. Furthermore, by introducing geodetic height, water surface elevation, and equivalent focal length to determine the ground sampling distance, it achieves resolution adaptive control. Finally, orthorectification is completed based on this sampling distance, which significantly improves the spatial consistency of UAV images of water surface areas and has good practicality and engineering applicability. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the orthorectification method for UAV images facing the water surface provided by the present invention.

[0020] Figure 2 This is a schematic diagram of the module of the UAV image orthorectification device facing the water surface provided by the present invention.

[0021] Figure 3 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0023] This invention proposes an orthorectification method for UAV images facing the water surface that does not rely on feature points. This method is designed for aerial photography scenarios in nearshore sea areas, lakes and other water surface areas. It innovatively breaks through the limitations of traditional correction techniques that rely on ground feature points. By integrating UAV flight parameters, water surface optical characteristics and geometric modeling techniques, it achieves orthorectification of UAV images facing the water surface, providing key technical support for marine monitoring, water area mapping and other fields.

[0024] Optionally, the orthorectification method for UAV images facing the water surface in this embodiment of the invention can be executed by a server, by a terminal device, or by both a server and a terminal device. Taking the execution of the orthorectification method for UAV images facing the water surface in this embodiment by a server as an example.

[0025] Figure 1 This is a flowchart illustrating the orthorectification method for UAV images facing the water surface provided by the present invention, as shown below. Figure 1 As shown, the method includes the following steps.

[0026] Step 101: Obtain drone images of the water surface area taken by the drone according to the preset flight path.

[0027] In this embodiment of the invention, the drone is controlled to perform aerial photography of the water surface area along a preset route, acquire drone images in JPG format with EXIF ​​metadata, and simultaneously record flight trajectory and attitude data as flight parameters (including GPS coordinates, flight altitude, roll angle, pitch angle, yaw angle, etc.).

[0028] The ExifTool is used to parse the UAV image EXIF ​​data to obtain image scale information (Width (in pixels), Height (in pixels)), camera intrinsic parameters (equivalent focal length f (in pixels), optical center coordinates) (Unit: pixels)), Location information of the photography center S (longitude lon_s (unit: degrees), latitude lat_s (unit: degrees), geodetic height) (Unit: meters) and attitude angles (roll angle) (Unit: degrees) Pitch angle (Unit: degrees), yaw angle (Unit: degrees) and other parameters.

[0029] In some embodiments, a ground control station plans the preset flight path of the UAV to ensure complete coverage of the target water surface area; the UAV, equipped with an aerial camera, automatically flies along the preset flight path and takes vertical or oblique photographs of the water area at set time intervals or distance intervals during the flight, simultaneously recording high-precision POS data (including latitude and longitude, altitude), IMU attitude data (pitch, roll, heading angle), flight altitude, speed and GPS timestamp at the time of camera exposure for each image; after the UAV completes the mission, it lands and obtains complete UAV images and matching flight parameters through data export.

[0030] Step 102: Based on the latitude and longitude of the photography center in the UAV image, perform coordinate system transformation to obtain the planar coordinates of the photography center in the photogrammetric coordinate system.

[0031] In this embodiment of the invention, the latitude and longitude (longitude lon_s, latitude lat_s) of the UAV image's photography center are converted into planar coordinates (unit: meters) in the CGCS2000 Gauss-Kruger plane coordinate system through projection transformation.

[0032] Central meridian of drone imagery Calculated based on image longitude (3-degree zone projection): ; in, The central meridian of the drone image is indicated. Indicates the lower limit rounding. Longitude indicating the center of the drone image.

[0033] Step 103: Determine the uniform water surface elevation value for the water surface area.

[0034] According to the present invention, a method for orthorectifying UAV images facing a water surface is provided, wherein determining the uniform water surface elevation value of the water surface area includes: Based on the local horizontal plane and tidal height of the water surface area, a uniform water surface elevation value for the water surface area is determined.

[0035] In this embodiment of the invention, when the drone aerial photography area is located in a water area, there is no obvious terrain undulation. Assuming that the water area is a local horizontal plane, a uniform water surface elevation value (such as the sum of the horizontal horizontal plane and the tidal height) is set based on the elevation data of adjacent land or water level stations, and the influence of small waves is ignored.

[0036] Based on monitoring data or geographic reference information of the water surface area, the average elevation reference value of the water surface is calculated by using the measured values ​​of elevation points of adjacent land or the real-time water level data recorded by water level stations as the basis, combined with the tidal variation characteristics of the target area (if there are periodic tides); finally, the water surface of the area is set as a unified elevation plane.

[0037] The tidal correction can be dynamically obtained from tide gauge data, while static water level elevation is used directly in non-tidal areas. During implementation, minor elevation fluctuations caused by waves (typically ≤0.1 meters) are ignored to ensure the geometric stability of the water surface as a local horizontal plane.

[0038] Step 104: Based on the collinearity equation, and using the planar coordinates of the photography center and the unified water surface elevation, determine the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system; and construct the point cloud data of the UAV image based on the ground point coordinates of each pixel.

[0039] In this embodiment of the invention, for any grid on the UAV image, its planar coordinates in the UAV image are (x, y), and the image pixel value is The coordinates of the corresponding ground point P in the photogrammetric coordinate system (a coordinate system used to describe the spatial position of ground objects; here, the CGCS2000 3-degree zone projected coordinate system is used) are: (Unit: meters)

[0040] According to the present invention, an orthorectification method for UAV images facing a water surface is provided. Based on the collinearity equation and the planar coordinates of the photogrammetric center and a uniform water surface elevation value, the method determines the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system, including: Take each pixel in the UAV imagery as the current pixel, and determine the ground point coordinates of the current pixel using the following formula. : ; ; in, This represents the x-coordinate of the current pixel in the photogrammetric coordinate system. This represents the ordinate of the current pixel in the photogrammetric coordinate system. The geodetic height represents the coordinates of a point on the ground. Indicates the elevation of the drone image. and These represent the x and y coordinates of the current pixel in the drone image, respectively. and These represent the x-coordinate and y-coordinate of the optical center of the UAV image, respectively. and These represent the x and y coordinates of the photogrammetric center in the photogrammetric coordinate system; coefficients , , , , , , , , It is a rotation matrix The direction cosine element is used to describe the rotation relationship between the image space coordinate system and the photogrammetric coordinate system of UAV imagery.

[0041] In this embodiment of the invention, the coordinates of the photography center in the photogrammetric coordinate system are ( (This refers to the spatial position of the center of the camera lens when this photo was taken.)

[0042] , , (where i = 1, 2, 3) is not an independent parameter; they together form a 3 The rotation matrix R is 3. This matrix is ​​calculated from the camera's three attitude angles (heading angle, pitch angle, and roll angle).

[0043] , , It is a rotation matrix The first column represents the direction cosine of the X-axis of the photogrammetric coordinate system in the camera coordinate system.

[0044] , , It is a rotation matrix The second column represents the direction cosine of the Y-axis of the photogrammetric coordinate system in the camera coordinate system.

[0045] , , It is a rotation matrix The third column represents the direction cosine of the Z-axis of the photogrammetric coordinate system in the camera coordinate system (usually pointing towards the Earth's center).

[0046] This represents the component of the vector from the projection center to the object point along the camera optical axis (Zc axis).

[0047] In this embodiment of the invention, given the pixel coordinates P(x, y) of a point on a UAV image, and with known camera intrinsic parameters... The camera's location at the time and attitude, and the approximate elevation of that point ( In the case of point P, the above formula can accurately calculate the coordinates of the ground point corresponding to that point (ground point P). ).

[0048] A set of point cloud data can be obtained by using the above formula. By traversing the image and repeating the above steps, you can obtain... Group point cloud data , For spatial coordinates, This corresponds to the image pixel value.

[0049] Through the embodiments of the present invention, a precise mapping relationship between the pixel coordinates of UAV images and the ground point coordinates of the photogrammetric coordinate system is constructed by collinearity equations. By utilizing the planar coordinates of the photography center, the unified water surface elevation value, and the image attitude parameters (direction cosine elements of the rotation matrix), the geometric calculation of pixel-level ground point coordinates is realized, effectively eliminating the geometric deformation caused by changes in UAV attitude and lens distortion, and improving the planar accuracy and geometric fidelity of orthophotos of the water surface area.

[0050] Step 105: Determine the ground sampling distance based on the ground height, uniform water surface elevation value, and equivalent focal length of the UAV imagery.

[0051] According to the present invention, an orthorectification method for UAV images facing a water surface is provided, which determines the ground sampling distance based on the geodetic height of the UAV image, the uniform water surface elevation value, and the equivalent focal length during UAV shooting, including: The ground sampling distance is determined using the following formula: ; in, Indicates the ground sampling distance. Indicates the elevation of the drone image. Indicates a uniform water surface elevation value. This indicates the equivalent focal length when shooting with a drone.

[0052] In this embodiment of the invention, three core parameters are first extracted from the UAV aerial photography system: The central elevation of the photography center (i.e., the elevation of the drone imagery) ): This value is obtained from real-time elevation data recorded by the GNSS / IMU system on the drone. It represents the vertical distance (in meters) between the center of the camera lens and the reference ellipsoid at the moment of the photograph.

[0053] Unified water surface elevation (Z): The established static water surface elevation datum (unit: meters) is used, and this value is calculated from water level station data or the elevation of adjacent land.

[0054] Equivalent focal length (f): Camera intrinsic parameter (unit: pixels) parsed from image EXIF ​​metadata, which must be consistent with the scale calculation unit.

[0055] In the above formula, the molecule The denominator represents the vertical distance from the center of the photograph to the water surface (i.e., the projected distance). It represents the equivalent focal length, which is used to determine the field of view of an image. The larger the focal length, the smaller the ground area corresponding to a unit pixel.

[0056] Through the embodiments of the present invention, a ground sampling distance (GSD) calculation model based on UAV imagery, uniform water surface elevation, and equivalent focal length is used to achieve a quantitative assessment of the spatial resolution of water surface area images. The formula intuitively reflects the linear influence of flight altitude difference and focal length on GSD, providing key spatial scale parameters for water surface orthorectification.

[0057] Step 106: Based on the ground sampling distance, orthorectify the point cloud data of the UAV image to obtain the orthorectified image.

[0058] In this embodiment of the invention, the planar coordinates of all ground points in the point cloud data are first traversed, and the maximum and minimum values ​​in the X direction and the Y direction are extracted. These four extreme values ​​together define the spatial coverage of the point cloud.

[0059] The spatial extent is divided into a regular grid based on the ground sampling distance (GSD): Horizontal direction (X-axis): Generates a mesh sequence with a step size GSD, starting coordinates The number of grids M is determined by dividing the range width by GSD and then rounding it up, using a floor-down alignment method.

[0060] Vertical direction (Y-axis): Similarly, generate a mesh sequence, starting coordinates. The number of grid cells L is calculated using the same logic.

[0061] Create a two-dimensional matrix (regular grid matrix) with M rows and L columns, where each grid cell (j,k) corresponds to a planar coordinate.

[0062] For the grid coordinates of each target grid point in the regular grid The KD-tree spatial indexing algorithm quickly searches for the n nearest neighbors (typically n=4~9) in the original point cloud data. The KD-tree organizes the point cloud into layers according to its spatial structure, which greatly improves the search efficiency.

[0063] Dynamically assign weights based on the spatial distance between neighboring points and the target grid point: Calculate the Euclidean distance from each neighboring point to the target grid point. Weight With distance of The power is inversely proportional to the power. In other words, the closer the neighboring points are, the greater their influence on the target grid point. The pixel value of the target grid point is obtained by weighted averaging of the pixel values ​​of its neighboring points, ensuring a smooth color transition.

[0064] By using regular grids and resampling operations, the geometric distortion caused by the drone's attitude tilt in the original image is completely eliminated, generating a corrected regular grid matrix.

[0065] The corrected regular grid matrix is ​​bound to the CGCS2000 3-degree zone projected coordinate system and saved as a GeoTIFF file. This format automatically embeds metadata such as coordinate range, resolution, and projection parameters, and can be directly loaded and used in GIS software.

[0066] According to the present invention, an orthorectification method for UAV imagery facing a water surface is provided, which performs orthorasterization processing on the point cloud data of UAV imagery based on ground sampling distance to obtain orthorectified imagery, including: The boundary of the regular grid is determined by the extreme values ​​of the x and y coordinates of all ground points in the point cloud data of UAV imagery. Based on the ground sampling distance and the boundary of the regular grid, the starting coordinates and number of grids of the regular grid are determined; A regular grid is constructed based on the ground sampling distance, starting coordinates, and number of grids; A nearest neighbor search and weighted interpolation algorithm based on KD tree is used to interpolate the point cloud data of UAV imagery based on a regular grid to obtain image attribute regular raster. Traverse the image attribute rule grid and solve for each element in the image attribute rule grid to obtain the orthorectified image.

[0067] In this embodiment of the invention, the boundary of the regular grid is determined: , , , ; in, This represents the maximum value of the x-coordinate of the regular grid. This represents the minimum value of the x-coordinate of the regular grid. This represents the maximum value of the y-coordinate of the regular grid. This represents the minimum value of the ordinate of the regular grid. This represents the x-coordinate of the i-th ground point in the point cloud data of the UAV imagery. The ordinate represents the coordinates of the i-th ground point in the point cloud data of the UAV imagery; This represents the total number of ground points in the point cloud data.

[0068] Construct a regular grid sequence in the horizontal direction (X-axis) : ; Where the initial coordinates Number of grid cells in the horizontal direction ; Construct a regular grid sequence in the vertical direction (Y-axis) : ; Where the initial coordinates Number of grid cells in the vertical direction . This indicates that the lower limit is rounded down.

[0069] Through the embodiments of the present invention, a regular grid is constructed by ground sampling distance (GSD), realizing the spatial regularization processing of water surface point cloud data. The grid boundary is automatically determined by extreme coordinates, and the grid resolution is precisely controlled by GSD to ensure that the corrected image strictly matches the actual water scale. The nearest neighbor search and weighted interpolation algorithm accelerated by KD tree effectively solves the grid hole problem caused by sparse distribution of point clouds, and significantly improves the continuity of water surface topography representation.

[0070] According to the present invention, an orthorectification method for UAV images facing a water surface is provided, which constructs a regular grid based on ground sampling distance, starting coordinates, and grid number, including: Define a regular grid Each element Corresponding grid coordinates ,satisfy: ; ; ; in, The x-coordinate representing the starting coordinate. This represents the x-coordinate index of the grid coordinates in a regular grid. Indicates the ground sampling distance. The ordinate represents the starting coordinate. This represents the y-coordinate index of the grid coordinates in a regular grid. Indicates the number of grid cells in the horizontal direction. Indicates the number of grid cells in the vertical direction.

[0071] In this embodiment of the invention, the horizontal starting coordinates and vertical starting coordinates The extreme values ​​of the point cloud boundary were obtained by rounding down to the nearest integer multiple of GSD.

[0072] In the horizontal direction (X-axis), starting from the horizontal initial coordinate, M coordinate values ​​are generated incrementally by step size GSD; In the vertical direction (Y-axis), starting from the vertical initial coordinate, L coordinate values ​​are generated incrementally with a step size GSD; Construct a two-dimensional matrix of dimension L×M (i.e., a regular grid). ), where each element Corresponding grid coordinates This forms a regularly spaced grid that covers the entire point cloud area.

[0073] Through the embodiments of the present invention, the starting coordinates ( , The grid is accurately positioned spatially by using the ground sampling distance (GSD). A regular grid system covering the target water area is automatically generated by a linear combination of the row and column indices (j,k) and the number of grids (M,L). This ensures the consistency between the grid spacing and the image spatial resolution (GSD) and eliminates accumulated errors through explicit coordinate calculation.

[0074] According to the present invention, a method for orthorectifying UAV images facing the water surface is provided, wherein for any grid point in a regular grid, the interpolation weight of any grid point is inversely proportional to the weight exponential power of the distance to neighboring points.

[0075] In this embodiment of the invention, data resampling involves interpolating the original irregularly distributed point cloud data onto the grid based on the constructed regular grid.

[0076] For any regular grid Search for its n nearest neighbors using a KD-tree , where m is the nearest neighbor index.

[0077] Calculate grid values ​​using weighted interpolation ,in As weight, For distance, The weighted index (usually taken as) ), This represents the original pixel value corresponding to the m-th ground point in the point cloud. Traverse the regular grid. Complete each element Solving for the orthorectification of the image completes the orthorectification.

[0078] Geocoding is used for storage: The CGCS2000 3-degree zone projected coordinate system is adopted, with the central meridian as... Simply save the orthorectified image as a GeoTIFF file.

[0079] Through the embodiments of the present invention, an interpolation weight allocation strategy that is inversely proportional to the weight exponent of the distance to neighboring points is adopted to achieve spatial adaptive weighted interpolation of regular grid points. This makes the point cloud data closer to the grid point to be interpolated contribute more to the correction result, effectively suppressing the interference of distant noise points.

[0080] The orthorectification device for UAV images facing the water surface provided by the present invention will be described below. The orthorectification device for UAV images facing the water surface described below can be referred to in correspondence with the orthorectification method for UAV images facing the water surface described above.

[0081] refer to Figure 2 , Figure 2 This is a schematic diagram of the module of the UAV image orthorectification device facing the water surface provided by the present invention.

[0082] The acquisition module 201 is used to acquire drone images of the water surface area taken by the drone according to a preset route; The conversion module 202 is used to perform coordinate system transformation based on the latitude and longitude of the photography center of the UAV image to obtain the planar coordinates of the photography center in the photogrammetric coordinate system. Module 203 is used to determine the uniform water surface elevation value of the water surface area; Point cloud module 204 is used to determine the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photography center and the unified water surface elevation value; and to construct point cloud data of the UAV image based on the ground point coordinates of each pixel. The distance module 205 is used to determine the ground sampling distance based on the geodetic height, uniform water surface elevation value and equivalent focal length of the UAV imagery. The correction module 206 is used to perform orthorectification processing on the point cloud data of UAV imagery based on the ground sampling distance to obtain orthorectified imagery.

[0083] Specifically, the above-mentioned orthorectification device for UAV images facing the water surface provided by the present invention can realize all the method steps implemented in the above-mentioned embodiment of the orthorectification method for UAV images facing the water surface, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0084] Figure 3 This is a schematic diagram of the physical structure of the electronic device provided by the present invention, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communications bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other through the communications bus 340. The processor 310 can call logic instructions in the memory 330 to execute a method for orthorectifying UAV images facing a water surface. This method includes: acquiring UAV images taken by the UAV along a preset flight path over a water surface area; performing coordinate system transformation based on the latitude and longitude of the UAV image's photographic center to obtain the planar coordinates of the photographic center in a photogrammetric coordinate system; determining a uniform water surface elevation value for the water surface area; determining the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photographic center, and the uniform water surface elevation value; constructing point cloud data of the UAV image based on the ground point coordinates of each pixel; determining the ground sampling distance based on the UAV image's geodetic height, the uniform water surface elevation value, and the equivalent focal length during UAV shooting; and performing orthorasterization processing on the point cloud data of the UAV image based on the ground sampling distance to obtain the orthorectified image.

[0085] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0086] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the above-described method for orthorectifying UAV images facing a water surface. This method includes: acquiring UAV images taken by a UAV along a preset flight path over a water surface area; performing coordinate system transformation based on the latitude and longitude of the UAV image's photography center to obtain the planar coordinates of the photography center in a photogrammetric coordinate system; determining a uniform water surface elevation value for the water surface area; determining the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photography center, and the uniform water surface elevation value; constructing point cloud data of the UAV image based on the ground point coordinates of each pixel; determining the ground sampling distance based on the UAV image's geodetic height, the uniform water surface elevation value, and the equivalent focal length during UAV photography; and performing orthorasterization processing on the point cloud data of the UAV image based on the ground sampling distance to obtain the orthorectified image.

[0087] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the orthorectification method for UAV images facing a water surface provided by the methods described above. The method includes: acquiring UAV images taken by a UAV along a preset flight path over a water surface area; performing coordinate system transformation based on the latitude and longitude of the UAV image's photographic center to obtain the planar coordinates of the photographic center in a photogrammetric coordinate system; determining a uniform water surface elevation value for the water surface area; determining the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photographic center, and the uniform water surface elevation value; constructing point cloud data of the UAV image based on the ground point coordinates of each pixel; determining the ground sampling distance based on the UAV image's geodetic height, the uniform water surface elevation value, and the equivalent focal length taken by the UAV; and performing orthorasterization processing on the point cloud data of the UAV image based on the ground sampling distance to obtain the orthorectified image.

[0088] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0089] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for orthorectifying UAV images facing a water surface, characterized in that, include: Acquire drone images of a water surface area taken by a drone following a preset flight path; Based on the latitude and longitude of the photography center in the UAV image, a coordinate system transformation is performed to obtain the planar coordinates of the photography center in the photogrammetric coordinate system; Determine a uniform water surface elevation value for the aforementioned water surface area; Based on the collinearity equation, and using the planar coordinates of the photography center and the unified water surface elevation, the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system are determined; and based on the ground point coordinates of each pixel, point cloud data of the UAV image is constructed. The ground sampling distance is determined based on the ground height of the UAV image, the unified water surface elevation value, and the equivalent focal length of the UAV during shooting. Based on the ground sampling distance, the point cloud data of the UAV image is orthorectified to obtain an orthorectified image.

2. The method for orthorectifying UAV images facing the water surface according to claim 1, characterized in that, Determining the uniform water surface elevation value for the water surface area includes: Based on the local horizontal plane and tidal height of the water surface area, a uniform water surface elevation value for the water surface area is determined; The determination of the ground sampling distance based on the ground height of the UAV image, the unified water surface elevation value, and the equivalent focal length of the UAV during shooting includes: determining the ground sampling distance according to the following formula: ； in, Indicates the ground sampling distance, This indicates the elevation of the image from the drone. This represents the unified water surface elevation value. This indicates the equivalent focal length when the drone is taking the picture.

3. The method for orthorectifying UAV images facing the water surface according to claim 1, characterized in that, The step of determining the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photography center, and the unified water surface elevation value includes: Each pixel in the UAV image is taken as the current pixel, and the ground point coordinates of the current pixel are determined according to the following formula. : ； ； in, This represents the x-coordinate of the current pixel in the photogrammetric coordinate system. This represents the ordinate of the current pixel in the photogrammetric coordinate system. The geodetic height representing the coordinates of the ground point. This indicates the elevation of the image from the drone. and These represent the x and y coordinates of the current pixel in the UAV image, respectively. and These represent the x-coordinate and y-coordinate of the optical center of the UAV image, respectively. and These represent the x-coordinate and y-coordinate of the photogrammetric center in the photogrammetric coordinate system, respectively; coefficients , , , , , , , , It is a rotation matrix The direction cosine element is used to describe the rotation relationship of the image space coordinate system of the UAV image relative to the photogrammetric coordinate system.

4. The method for orthorectifying UAV images facing the water surface according to claim 1, characterized in that, The process of orthorectifying the point cloud data of the UAV imagery based on the ground sampling distance to obtain orthorectified images includes: The boundary of the regular grid is determined based on the extreme values ​​of the x and y coordinates of all ground points in the point cloud data of the UAV imagery. Based on the ground sampling distance and the boundary of the regular grid, the starting coordinates and the number of grids of the regular grid are determined; The regular grid is constructed based on the ground sampling distance, the starting coordinates, and the number of grids; The point cloud data of the UAV imagery is interpolated based on the regular grid using a KD-tree-based nearest neighbor search and weighted interpolation algorithm to obtain an image attribute regular grid. The image attribute rule grid is traversed, and each element in the image attribute rule grid is solved to obtain the orthorectified image.

5. The method for orthorectifying UAV images facing the water surface according to claim 4, characterized in that, For any grid point in the regular grid, the interpolation weight of the arbitrary grid point is inversely proportional to the weight exponent of the distance to neighboring points.

6. The method for orthorectifying UAV images facing the water surface according to claim 4, characterized in that, The construction of the regular grid based on the ground sampling distance, the starting coordinates, and the number of grids includes: Define a regular grid Each element Corresponding grid coordinates ,satisfy: ； ； ； in, The x-coordinate of the starting coordinates. This represents the x-coordinate index of the grid coordinates in the regular grid. Indicates the ground sampling distance, The ordinate represents the starting coordinate. This represents the y-coordinate index of the grid coordinates in the regular grid. Indicates the number of grid cells in the horizontal direction. Indicates the number of grid cells in the vertical direction.

7. A device for orthorectifying UAV images facing a water surface, characterized in that, include: The acquisition module is used to acquire drone images taken by the drone over the water surface area according to a preset flight path. The conversion module is used to perform coordinate system transformation based on the latitude and longitude of the photography center of the UAV image to obtain the planar coordinates of the photography center in the photogrammetric coordinate system. The determination module is used to determine the uniform water surface elevation value of the water surface area; The point cloud module is used to determine the ground point coordinates of each pixel in the UAV image in the photogrammetric coordinate system based on the collinearity equation, the planar coordinates of the photography center, and the unified water surface elevation value; and to construct the point cloud data of the UAV image based on the ground point coordinates of each pixel. The distance module is used to determine the ground sampling distance based on the ground height of the UAV image, the uniform water surface elevation value, and the equivalent focal length of the UAV during shooting. The correction module is used to perform orthorectification processing on the point cloud data of the UAV image based on the ground sampling distance to obtain the orthorectified image.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the orthorectification method for UAV images facing the water surface as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the orthorectification method for UAV images facing the water surface as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the orthorectification method for UAV images facing the water surface as described in any one of claims 1 to 6.

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