Surveying and mapping image data processing method and device based on image transformation

Abstract

The invention discloses a surveying and mapping image data processing method and device based on image transformation, and relates to the technical field of data processing. The method comprises the following steps: performing oblique photography by using an unmanned aerial vehicle unit to obtain image data of a to-be-constructed area; the unmanned aerial vehicle unit performs image conversion on the image data to obtain corrected image data; the cloud service platform generates three-dimensional point cloud data of the to-be-constructed area based on the corrected image data; constructing a DEM of the to-be-constructed area based on the three-dimensional point cloud data; marking a detection point corresponding to each construction position in the DEM according to a preset construction position coordinate of the to-be-constructed area; obtaining construction structure information of each detection point from the DEM; the construction structure information comprises original elevation data; and on the basis of the difference between the original elevation data of each construction position and the corresponding design elevation data, the earth-rock excavation and filling amount of the to-be-constructed area is calculated. According to the technical scheme provided by the invention, the earth-rock calculation efficiency and accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and specifically provides a method and device for processing surveying and mapping image data based on image transformation. Background Technique

[0002] In surveying, mapping, and engineering construction projects, accurately obtaining the topographic information of the construction area and calculating the earthwork volume are key steps for subsequent engineering plan configuration. In the prior art, instruments such as total stations and levels can be used for on-site measurement to record the coordinates and elevations of each construction point, or cross-section diagrams perpendicular to the terrain trend can be generated based on the measured data to visually present the surface undulation state, and ultimately achieve the purpose of calculating the earthwork volume. However, the above methods not only have extremely low efficiency but are also extremely vulnerable to weather conditions, making it difficult to perform timely and efficient earthwork volume calculations. At the same time, the manual measurement method has a high data error rate, and the data is difficult to cover the entire area, especially in application scenarios with complex terrains such as mountainous areas. Therefore, the detected data cannot comprehensively and accurately represent the surface features, resulting in a low accuracy of the earthwork volume calculation results.

[0003] Therefore, how to overcome the above existing technical problems and defects has become a key problem to be solved. Summary of the Invention

[0004] The purpose of the present application is to provide a method and device for processing surveying and mapping image data based on image transformation to solve the problems raised in the above background technique and improve the efficiency and accuracy of earthwork volume calculation.

[0005] The technical solution of the embodiment of the present application is implemented as follows: The embodiment of the present application provides a system for processing surveying and mapping image data based on image transformation, which includes a drone unit and a cloud service platform; The drone unit includes a data acquisition module, an image processing module, and a communication module. The data acquisition module is used to obtain the image data of the area to be constructed when the drone performs oblique photography. The image processing module is used to perform image transformation on the image data to obtain corrected image data and send it to the cloud service platform using the communication module; The cloud service platform includes a data processing module, a model construction module, a feature extraction module, and a calculation module; the data processing module is used to generate three-dimensional point cloud data of the area to be constructed based on the corrected image data; the model construction module is used to construct a digital elevation model (DEM) of the area to be constructed based on the three-dimensional point cloud data; and, according to the coordinates of at least one construction position preset in the area to be constructed, mark detection points corresponding to each construction position in the DEM; the feature extraction module is used to obtain the construction structure information of each detection point from the DEM; the construction structure information includes the original elevation data of the corresponding construction position; the calculation module is used to calculate the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data of each construction position.

[0006] In the above solution, the system further includes a mobile edge computing (MEC) unit; the MEC unit includes an authentication module and a response module; The drone unit is further used to continuously send heartbeat packets to the ground using the communication module, and send a data upload request to the MEC unit after receiving the acknowledgement response (ACK) returned by the MEC unit; The MEC unit is used to authenticate the drone unit using the authentication module after receiving the heartbeat packet sent by the drone unit, and send an ACK to the drone unit after the authentication is passed; and, using the response module, in response to the data upload request, upload the soil volume change information of the area to be constructed in the current sampling period to the cloud service platform; the soil volume change information includes the soil volume change coefficient of the area to be constructed, and the soil volume change coefficient is determined based on the sensor data of the area to be constructed; The cloud service platform is used to use the calculation module to calculate the initial earthwork excavation and filling value of the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data of each construction position; and, based on the initial earthwork excavation and filling value of each construction position and the corresponding soil volume change coefficient, calculate the earthwork excavation and filling volume of the corresponding construction position.

[0007] The embodiment of the present application further provides a method for processing surveying and mapping image data based on image transformation, and the method includes: Using the drone unit in the data processing system to perform oblique photography to obtain image data of the area to be constructed; The drone unit performs image transformation on the image data to obtain corrected image data and sends it to the cloud service platform of the data processing system; The cloud service platform generates three-dimensional point cloud data of the area to be constructed based on the corrected image data; Construct a digital elevation model (DEM) of the area to be constructed based on the three-dimensional point cloud data; Mark inspection points corresponding to each construction location in the DEM according to the coordinates of at least one preset construction location in the area to be constructed; Obtain the construction structure information of each inspection point from the DEM; the construction structure information includes the original elevation data of the corresponding construction location; Calculate the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data of each construction location.

[0008] In the above solution, the method further includes: The drone unit continuously sends heartbeats to the ground; After receiving the heartbeat sent by the drone unit, the MEC unit of the data processing system authenticates the drone and sends an ACK to the drone unit after successful authentication; After receiving the ACK returned by the MEC unit, the drone unit sends a data upload request to the MEC unit; In response to the data upload request, the MEC unit uploads the soil volume change information of the area to be constructed in the current sampling period to the cloud service platform; the soil volume change information includes the soil volume change coefficient of the area to be constructed, and the soil volume change coefficient is determined based on the sensor data of the area to be constructed.

[0009] In the above solution, the calculation of the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data of each construction location includes: Calculate the initial value of the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data of each construction location; Calculate the earthwork excavation and filling volume of the area to be constructed based on the initial value of the earthwork excavation and filling volume of the area to be constructed and the corresponding soil volume change coefficient.

[0010] In the above solution, before calculating the earthwork excavation and filling volume of the area to be constructed based on the initial value of the earthwork excavation and filling volume of the area to be constructed and the corresponding soil volume change coefficient, the method further includes: The MEC unit determines the corresponding soil volume change coefficient based on the soil type and construction type of the area to be constructed; where The coefficient of soil volume change is the expansion coefficient or the compression ratio, and the construction type is excavation or filling; when the construction type of the area to be constructed is excavation, the corresponding coefficient of soil volume change is the expansion coefficient, and when the construction type of the area to be constructed is filling, the corresponding coefficient of soil volume change is the compression ratio.

[0011] In the above solution, determining the corresponding coefficient of soil volume change based on the soil type and construction type of the area to be constructed includes: Determining an initial coefficient of volume change matching the area to be constructed from a pre-configured list of coefficients of volume change based on the soil type and construction type of the area to be constructed; Determining the soil characteristic information of the area to be constructed based on the sensor data of the area to be constructed; the soil characteristic information includes water content information and particle distribution information; Correcting the initial coefficient of volume change of the area to be constructed based on the soil characteristic information to obtain the coefficient of soil volume change of the area to be constructed.

[0012] In the above solution, when the construction type of the area to be constructed is excavation, correcting the initial coefficient of volume change of the area to be constructed based on the soil characteristic information to obtain the coefficient of soil volume change of the area to be constructed includes: Correcting the pre-configured initial expansion coefficient based on the water content information in the soil characteristic information to obtain a first expansion coefficient, where the initial expansion coefficient is determined according to the soil type; the correction formula is expressed as: ; Wherein, represents the first expansion coefficient of the area to be constructed , represents the initial expansion coefficient of the area to be constructed , represents the water content sensitivity coefficient of the area to be constructed , represents the difference between the actual water content of the area to be constructed and the water content threshold of the corresponding soil type; Determining a correction factor matching the area to be constructed from the pre-configured correction factors based on the particle distribution information in the soil characteristic information; Correcting the first expansion coefficient based on the correction factor of each area to be constructed to obtain the expansion coefficient of the area to be constructed; the correction formula is expressed as: ; Wherein, represents the expansion coefficient obtained after correction of the area to be constructed , Indicates the area to be constructed Correction factor.

[0013] In the above solution, when the construction type of the area to be constructed is filling, based on the soil characteristic information, the initial volume change coefficient of the area to be constructed is corrected to obtain the soil volume change coefficient of the area to be constructed, including:[[]] Based on the water content information in the soil characteristic information, the pre-configured initial compression ratio is corrected to obtain the first compression ratio. The initial compression ratio is determined by the soil type. The correction formula is expressed as:[[]] ; Wherein,[[]] Indicates the first compression ratio of the area to be constructed Indicates the first compression ratio of the area to be constructed Indicates the area to be constructed Initial compression ratio of Indicates the area to be constructed Water content sensitivity coefficient of Indicates the area to be constructed Difference between the actual water content of the area to be constructed and the water content threshold of the corresponding soil type; Based on the particle size distribution information in the soil characteristic information, determine the correction factor matching the area to be constructed from the pre-configured correction factors; Based on the correction factor of each area to be constructed, correct the first compression ratio to obtain the compression ratio of the area to be constructed. The correction formula is expressed as:[[]] ; Wherein,[[]] Indicates the compression ratio obtained after correction of the area to be constructed Indicates the compression ratio obtained after correction of the area to be constructed Indicates the area to be constructed Correction factor of

[0014] In the above solution, the image transformation of the image data to obtain the corrected image data includes:[[]] Performing radiometric correction, geometric correction, multi-view consistency correction, and shadow correction on the image data respectively to obtain the corrected image data.

[0015] The method and device for processing surveying and mapping image data based on image transformation provided by the embodiments of the present application use an unmanned aerial vehicle (UAV) for multi-angle oblique photography. Compared with the manual on-site measurement method, it can not only quickly and accurately obtain high-resolution image data, thereby improving the data acquisition efficiency and accuracy, improving the accuracy and calculation efficiency of earthwork calculation results, but also adjust the monitoring area by adjusting the UAV path, thereby improving the monitoring coverage range and being applicable to various complex terrains, improving the comprehensiveness of data acquisition; further, by performing image transformation on the remote sensing data collected by the UAV at different sampling points, the images collected from different perspectives can be aligned in the same coordinate system, realizing the consistency of the spatial positions of the remote sensing images collected under different conditions, thereby reducing the deviation in volume estimation caused by coordinate differences between images and improving the accuracy of earthwork calculation results; further, through automated detection point marking and earthwork volume calculation, the errors caused by manual intervention can be reduced, and the work efficiency and reliability of calculation results can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 FIG. is an architecture diagram of a surveying and mapping image data processing system based on image transformation provided by the embodiments of the present application; Figure 2 FIG. is a schematic structural diagram of the UAV unit in the surveying and mapping image data processing system based on image transformation according to the embodiments of the present application; Figure 3 FIG. is a schematic structural diagram of the cloud service platform in the surveying and mapping image data processing system based on image transformation according to the embodiments of the present application; Figure 4 FIG. is a schematic structural diagram of the MEC unit in the surveying and mapping image data processing system based on image transformation according to the embodiments of the present application; Figure 5 FIG. is a schematic flow diagram of a method for processing surveying and mapping image data based on image transformation provided by the embodiments of the present application; Figure 6 FIG. is a schematic flow diagram of S506 in the method for processing surveying and mapping image data based on image transformation according to the embodiments of the present application; Figure 7 FIG. is a schematic flow diagram of determining the soil volume change coefficient in the method for processing surveying and mapping image data based on image transformation according to the embodiments of the present application; Figure 8 FIG. is a schematic flow diagram of S701 in the method for processing surveying and mapping image data based on image transformation according to the embodiments of the present application; Figure 9 FIG. is a schematic flow diagram of one method of S803 in the method for processing surveying and mapping image data based on image transformation according to the embodiments of the present application; Figure 10Another schematic flowchart of S803 in the method for processing surveying and mapping image data based on image transformation according to the embodiments of the present application; Figure 11 Schematic flowchart of the method for the MEC unit to upload soil volume transformation information in the method for processing surveying and mapping image data based on image transformation provided by the embodiments of the present application. Detailed implementation manners

[0017] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0018] The embodiments of the present application provide a system for processing surveying and mapping image data based on image transformation, as Figure 1 shown. The system may include a drone unit 101 and a cloud service platform 102. The drone unit 101 and the cloud service platform 102 will be described in detail below.

[0019] As Figure 2 shown, the drone unit 101 includes a data acquisition module 201, an image processing module 202, and a communication module 203; The data acquisition module 201 is configured to obtain image data of the area to be constructed when the drone performs oblique photography; The image processing module 202 is configured to perform image transformation on the image data to obtain corrected image data; The communication module 203 is configured to send the corrected image data to the cloud service platform of the data processing system.

[0020] In one embodiment, the image processing module 202 may specifically be configured to: Perform radiometric correction, geometric correction, multi-view consistency correction, and shadow correction on the image data respectively to obtain corrected image data.

[0021] In practical applications, oblique photography is a technology that uses a drone equipped with a multi-angle camera system to photograph the ground. Specifically, the drone unit 101 can include multiple high-resolution cameras, which simultaneously obtain high-resolution images of the target object from different perspectives. For example, the drone can carry five high-resolution cameras and take pictures from a vertically downward perspective and four perspectives with different oblique angles to capture information on multiple sides of monitoring objects such as buildings and terrain, so as to provide more comprehensive three-dimensional structure information for subsequent three-dimensional model construction, enabling the constructed three-dimensional model to accurately reflect the terrain features and the fine structure of the target object. Compared with traditional manual measurement methods, the drone can efficiently cover a large geographical area in a short time and is suitable for fields such as urban planning and land resource survey. At the same time, through a preset route planning software, the drone can automatically fly along a predetermined path and complete the data acquisition task, reducing human operation errors and improving work efficiency.

[0022] Here, considering that oblique photography involves multi-angle and multi-sampling point shooting, and the images collected at different sampling points have a certain coverage rate, therefore, in the embodiments of the present application, the original image data obtained by oblique photography is subjected to image transformation to convert the remotely sensed images collected from different perspectives to the same scale, thereby improving the accuracy of the three-dimensional model.

[0023] As Figure 3 shown, the cloud service platform 102 includes a data processing module 301, a model construction module 302, a feature extraction module 303, and a calculation module 304.

[0024] The data processing module 301 is used to generate three-dimensional point cloud data of the to-be-constructed area based on the corrected image data; The model construction module 302 is used to construct a DEM of the to-be-constructed area based on the three-dimensional point cloud data; and, according to the coordinates of at least one construction position preset in the to-be-constructed area, mark detection points corresponding to each construction position in the DEM; The feature extraction module 303 is used to obtain the construction structure information of each detection point from the DEM; the construction structure information includes the original elevation data of the corresponding construction position; The calculation module 304 is used to calculate the earthwork excavation and filling volume of the to-be-constructed area based on the difference between the original elevation data of each construction position and the corresponding designed elevation data.

[0025] In one embodiment, the embodiments of the present application may further include an MEC unit; as Figure 4 shown, the MEC unit may include an authentication module 401 and a response module 402; The UAV unit 101 can also be used to continuously send heartbeat packets to the ground using the communication module 203, and send a data upload request to the MEC unit after receiving the confirmation response ACK returned by the MEC unit; The MEC unit is configured to authenticate the UAV unit 101 using the authentication module 401 after receiving the heartbeat packet sent by the UAV unit 101, and send an ACK to the UAV unit 101 after successful authentication; and, using the response module 402, in response to the data upload request, upload the soil volume change information of the area to be constructed during the current sampling period to the cloud service platform 102; the soil volume change information includes the soil volume change coefficient of the area to be constructed, and the soil volume change coefficient is determined based on the sensor data of the area to be constructed; The cloud service platform 102 is configured to calculate the initial value of earthwork excavation and filling in the area to be constructed using the calculation module 304 based on the difference between the original elevation data and the corresponding designed elevation data at each construction location; and calculate the earthwork excavation and filling volume at the corresponding construction location based on the initial value of earthwork excavation and filling at each construction location and the corresponding soil volume change coefficient.

[0026] In one embodiment, the calculation module 305 can specifically be used for: Calculate the initial value of earthwork excavation and filling in the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data at each construction location; Calculate the earthwork excavation and filling volume in the area to be constructed based on the initial value of earthwork excavation and filling in the area to be constructed and the corresponding soil volume change coefficient.

[0027] In one embodiment, before calculating the earthwork excavation and filling volume in the area to be constructed based on the initial value of earthwork excavation and filling in the area to be constructed and the corresponding soil volume change coefficient, the calculation module 305 can also be used for: Determine the corresponding soil volume change coefficient based on the soil type and construction type of the area to be constructed; where The soil volume change coefficient is the expansion coefficient or the compression ratio, and the construction type is excavation or filling; when the construction type of the area to be constructed is excavation, the corresponding soil volume change coefficient is the expansion coefficient, and when the construction type of the area to be constructed is filling, the corresponding soil volume change coefficient is the compression ratio.

[0028] In one embodiment, the calculation module 305 can specifically be used for: Determine the initial volume change coefficient matching the area to be constructed from a pre-configured list of volume change coefficients based on the soil type and construction type of the area to be constructed; Determine the soil characteristic information of the area to be constructed based on the sensor data of the area to be constructed; the soil characteristic information includes water content information and particle distribution information; Based on the soil characteristic information, correct the initial volume change coefficient of the area to be constructed to obtain the soil volume change coefficient of the area to be constructed.

[0029] In one embodiment, when the construction type of the area to be constructed is excavation, the step of correcting the initial volume change coefficient of the area to be constructed based on the soil characteristic information to obtain the soil volume change coefficient of the area to be constructed may include: Based on the water content information in the soil characteristic information, correct the pre-configured initial expansion coefficient to obtain a first expansion coefficient, where the initial expansion coefficient is determined according to the soil type; the correction formula is expressed as: ; Wherein, represents the first expansion coefficient of the area to be constructed , represents the initial expansion coefficient of the area to be constructed , represents the water content sensitivity coefficient of the area to be constructed , represents the difference between the actual water content of the area to be constructed and the water content threshold of the corresponding soil type; Based on the particle distribution information in the soil characteristic information, determine the correction factor matching the area to be constructed from the pre-configured correction factors; Based on the correction factor of each area to be constructed, correct the first expansion coefficient to obtain the expansion coefficient of the area to be constructed; the correction formula is expressed as: ; Wherein, represents the expansion coefficient obtained after correction of the area to be constructed , represents the correction factor of the area to be constructed .

[0030] In one embodiment, when the construction type of the area to be constructed is filling, the step of correcting the initial volume change coefficient of the area to be constructed based on the soil characteristic information to obtain the soil volume change coefficient of the area to be constructed includes: Based on the water content information in the soil characteristic information, correct the pre-configured initial compression ratio to obtain a first compression ratio, where the initial compression ratio is determined according to the soil type; the correction formula is expressed as: ; Among them, represents the first compression ratio of the area to be constructed , represents the initial compression ratio of the area to be constructed , represents the water content sensitivity coefficient of the area to be constructed , represents the difference between the actual water content of the area to be constructed and the water content threshold of the corresponding soil type; Determine the correction factor matching the area to be constructed from the pre-configured correction factors based on the particle distribution information in the soil characteristic information; Based on the correction factor of each area to be constructed, correct the first compression ratio to obtain the compression ratio of the area to be constructed; the correction formula is expressed as: ; Among them, represents the compression ratio obtained after correction of the area to be constructed , represents the correction factor of the area to be constructed .

[0031] Based on the above system architecture, an embodiment of the present application provides a method for processing surveying and mapping image data based on image transformation, which is applied to a system for processing surveying and mapping image data based on image transformation; as Figure 5 shown, this method may include S501 to S506. S501 to S506 will be described in detail below in conjunction with specific embodiments.

[0032] S501: Use the drone unit in the data processing system to perform oblique photography to obtain the image data of the area to be constructed.

[0033] In actual application, the high-resolution camera in the drone unit can simultaneously obtain high-resolution images of the target from different perspectives, such as shooting from the vertical downward perspective and four different oblique angles respectively, to capture information on multiple sides of monitoring objects such as buildings and terrain, so as to be able to provide more comprehensive three-dimensional structure information for subsequent construction of a three-dimensional model, and enable the constructed three-dimensional model to accurately reflect the terrain characteristics and the fine structure of the building.

[0034] S502: The drone unit performs image transformation on the image data to obtain corrected image data and sends it to the cloud service platform of the data processing system.

[0035] In one embodiment, performing image transformation on the image data to obtain corrected image data may include: ​Perform radiometric correction, geometric correction, multi-view consistency correction, and shadow correction on the image data respectively to obtain corrected image data.

[0036] In practical applications, the image data collected by drones is easily affected by factors such as lighting, resulting in tonal differences between images. For example, when the same area is photographed multiple times at different times of the day, the tonal differences between images are caused by the change of the sun's position. In the embodiments of the present application, radiometric correction is used to eliminate the lighting differences, color distortion, and other radiometric errors in the images, enabling the photos taken at different times or under different conditions to have consistent colors and brightness, thereby improving the compatibility and consistency between the image data during the 3D reconstruction process, ensuring higher continuity and smoothness when the images obtained under different perspectives and lighting conditions are stitched together. At the same time, it can also improve the continuity of the image data in terms of color and brightness dimensions, thereby enhancing the quality and visual effect of the final 3D model, and providing a more reliable data basis for subsequent automated processing (such as feature extraction, matching, etc.) to improve the accuracy and efficiency of the entire 3D reconstruction process.

[0037] In practical applications, during the radiometric correction process, atmospheric radiative transfer models such as MODTRAN can be used to simulate the atmospheric scattering and absorption effects and remove the color deviations caused by atmospheric influences. Then, histogram matching technology is used to adjust the histograms of multiple images to a similar distribution to ensure their visual consistency.

[0038] In practical applications, drones are easily affected by environmental factors such as wind speed, resulting in possible slight offsets in the camera pose. In the embodiments of the present application, by performing geometric correction on the image data, the geometric deformations caused by factors such as lens distortion and camera pose changes can be corrected, ensuring that each pixel point can accurately correspond to the actual geographical location, thereby guaranteeing the accuracy of the 3D reconstruction.

[0039] In practical applications, during the geometric correction process, standard boards such as checkerboards can be used to obtain the internal parameters of the camera (focal length, principal point offset, etc.), and a mathematical model can be established to describe the lens distortion characteristics, that is, perform internal parameter calibration on the image data. Then, using the position and attitude information provided by the GNSS / INS positioning system, calculate the rotation and translation matrices of the camera relative to the ground coordinate system, that is, perform external parameter solution on the image data. Finally, according to the above internal and external parameters, affine transformation or more complex non-linear transformation methods can be used to perform global or local geometric correction on the image.

[0040] In practical applications, when stitching images during 3D reconstruction, when images with multiple tilt angles are stitched together, there may be some slight misalignments or ghosting; through multi-view consistency correction in the embodiments of the present application, it can be ensured that images of the same scene taken from different angles form a smooth and coherent whole after stitching, improving the realism and accuracy of the reconstructed 3D model.

[0041] In practical applications, during the multi-view consistency correction process, stable feature points in each view can be extracted using algorithms such as SIFT and SURF, and reliable matching point pairs can be selected through FLANN or RANSAC; then, using the bundle adjustment method, based on all matching point pairs, the internal and external parameters of the camera and the positions of the 3D point cloud are optimized to achieve the best consistency between multi-view images; finally, using the fusion technology, for the overlapping areas, methods such as weighted average and Poisson fusion are used for seamless stitching to eliminate discontinuities at the boundaries.

[0042] In practical applications, the monitoring object may be blocked by the shadows of other objects, resulting in possible missing of key data during subsequent 3D reconstruction; through shadow correction in the embodiments of the present application, the influence of shadows on the image quality is reduced, especially in complex terrains or building-dense areas, to avoid shadows blocking important ground feature, thereby improving the clarity of image data and avoiding the impact on 3D reconstruction and subsequent earthwork calculation due to missing key data.

[0043] In practical applications, during the shadow correction process, shadow detection can be first performed using methods such as edge detection and morphological operations to identify the shadow areas in the image; then, based on physical models or empirical formulas, the expected brightness values of the shadow areas are estimated and appropriately enhanced to achieve light compensation; finally, for the parts completely covered by shadows, texture repair can be performed. Specifically, the occluded ground features can be restored through texture replication or interpolation algorithms in the adjacent shadow-free areas.

[0044] S503: The cloud service platform generates the 3D point cloud data of the to-be-constructed area based on the corrected image data.

[0045] Specifically, the cloud service platform generates the 3D point cloud data of the to-be-constructed area based on the corrected image data, that is, S503, which may include the following steps: S1. Feature point detection and matching: Use the SIFT algorithm to extract feature points from each image and match point pairs through FLANN; S2. Fundamental matrix calculation: Use the eight-point method to solve the fundamental matrix to determine the relative position relationship between each image; S3. Relative orientation: Solve the rotation and translation parameters between cameras by performing singular value decomposition on the essential matrix; S4. Triangulation: Using the linear least squares method, back-project the paired matching points into the three-dimensional space to form a sparse point cloud; S5. Dense matching and surface reconstruction: Apply the SGM algorithm for dense matching to supplement the sparse point cloud; finally, generate the complete three-dimensional point cloud data through Poisson surface reconstruction technology.

[0046] S504: Based on the three-dimensional point cloud data, construct the DEM of the area to be constructed; and according to the coordinates of at least one construction position preset in the area to be constructed, mark the detection points corresponding to each construction position in the DEM.

[0047] S505: Obtain the construction structure information of each detection point from the DEM; the construction structure information includes the original elevation data of the corresponding construction position.

[0048] S506: Based on the difference between the original elevation data and the corresponding designed elevation data of each construction position, calculate the earthwork excavation and filling volume of the area to be constructed.

[0049] In practical applications, the earthwork excavation and filling volume can be the excavation volume or filling volume of the earthwork.

[0050] In one embodiment, as Figure 6 shown, calculating the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data and the corresponding designed elevation data of each construction position, that is, S506, may include S601 and S602.

[0051] S601: Based on the difference between the original elevation data and the corresponding designed elevation data of each construction position, calculate the initial value of the earthwork excavation and filling volume of the area to be constructed.

[0052] S602: Based on the initial value of the earthwork excavation and filling volume of the area to be constructed and the corresponding soil volume change coefficient, calculate the earthwork excavation and filling volume of the area to be constructed.

[0053] In one embodiment, as Figure 7 shown, before calculating the earthwork excavation and filling volume of the area to be constructed based on the initial value of the earthwork excavation and filling volume of the area to be constructed and the corresponding soil volume change coefficient, that is, before executing S602, the method may further include: S701: The MEC unit determines the corresponding soil volume change coefficient based on the soil type and construction type of the area to be constructed; where The coefficient of soil volume change is the expansion coefficient or the compression ratio, and the construction type is excavation or filling; when the construction type of the area to be constructed is excavation, the corresponding coefficient of soil volume change is the expansion coefficient, and when the construction type of the area to be constructed is filling, the corresponding coefficient of soil volume change is the compression ratio.

[0054] In practical applications, soil types can include clay, silt, sand, loam, and silt.

[0055] In one embodiment, as Figure 8 shown, determining the corresponding coefficient of soil volume change based on the soil type and construction type of the area to be constructed, i.e., S701, can include S801 to S803.

[0056] S801: Based on the soil type and construction type of the area to be constructed, determine the initial coefficient of volume change that matches the area to be constructed from a pre-configured list of coefficients of volume change.

[0057] In practical applications, when the soil types are different, the internal structural characteristics of the soil are also different. The coefficient of volume change for each soil type can be pre-configured according to the soil type, and the coefficients of volume change pre-configured for various soil types are used to construct a list of coefficients of volume change; the list of coefficients of volume change can be understood as an association table between soil types and the preset initial coefficients of volume change.

[0058] In practical applications, clay has fine particles and a high plasticity index, and usually contains a large amount of clay minerals, such as montmorillonite or illite; clay has a high expansibility, especially when it encounters water, and the initial expansion coefficient of clay can be pre-configured to be 0.2 - 0.3; at the same time, clay will be significantly compressed under load, and the initial compression ratio of clay can be pre-configured to be 0.5 - 0.8; Silt particles are between sand and clay, have a certain plasticity and low permeability; the degree of expansion deformation of silt is relatively low, and the initial expansion coefficient of silt can be pre-configured to be 0.05 - 0.1; at the same time, the degree of compression deformation of silt is also relatively small, and the initial compression ratio of silt can be pre-configured to be 0.1 - 0.3; Sand is a coarse-grained soil, has good drainage and low plasticity; sand is mainly composed of larger particles, and the internal space changes little, so the degree of expansion deformation is low, and the initial expansion coefficient of sand can be pre-configured to be 0; at the same time, the degree of compression deformation of sand is also very low, and it will not be significantly compressed under a large pressure, and the initial compression ratio of sand can be pre-configured to be 0.01 - 0.05; Loam is a mixture of clay, silt, and sand, with a moderate texture and good agricultural properties. The degree of swelling deformation of loam is medium, and the initial swelling coefficient of the originally configured loam can be 5% - 15%. At the same time, the degree of compression deformation of loam is also relatively moderate, approximately 0.2 to 0.5. Silt has a high organic matter content, is very soft and porous. Due to the high water content of silt and the gas generated by the decomposition of organic matter, its degree of swelling deformation is high, and the initial swelling coefficient of the configured silt can be 1. At the same time, the degree of compression deformation of silt is also relatively high, and the initial compression ratio of the pre-configured silt can be 1.

[0059] S802: Based on the sensor data of the area to be constructed, determine the soil characteristic information of the area to be constructed; the soil characteristic information includes water content information and particle distribution information.

[0060] In practical applications, time domain reflectometry (TDR) sensors or frequency domain reflectometry (FDR) sensors can be set in the area to be constructed, and the corresponding sensor data can include water content data; use TDR sensors or FDR sensors to collect soil water content data.

[0061] In practical applications, the particle distribution information can represent the particle size distribution in the soil; the particle distribution information can include the soil type; different types of soil (such as sand, clay, loam, etc.) have different structural characteristics and particle compositions, and these factors determine the deformation characteristics of the soil when subjected to external forces. Specifically, cohesive soils with fine particles are more likely to expand and have a higher density after compaction; while sandy soils with coarse particles are relatively stable, with a smaller degree of expansion and compression.

[0062] In practical applications, the water content information of the area to be constructed can be determined based on the sensor data of the area to be constructed, the particle distribution information of the area to be constructed can be determined based on the soil type of the area to be constructed, and then based on the water content information and the particle distribution information, soil characteristic information can be generated.

[0063] S803: Based on the soil characteristic information, correct the initial volume change coefficient of the area to be constructed to obtain the soil volume change coefficient of the area to be constructed.

[0064] In one embodiment, as Figure 9 shown, when the construction type of the area to be constructed is excavation, the step of correcting the initial volume change coefficient of the area to be constructed based on the soil characteristic information to obtain the soil volume change coefficient of the area to be constructed, that is, S803, can include S901 to S903.

[0065] S901: Based on the water content information in the soil characteristic information, correct the pre-configured initial expansion coefficient to obtain the first expansion coefficient, where the initial expansion coefficient is determined according to the soil type; the correction formula is expressed as: ; Wherein, represents the first expansion coefficient of the area to be constructed, of the area to be constructed, represents the initial expansion coefficient of the area to be constructed, of the area to be constructed, represents the water content sensitivity coefficient of the area to be constructed, of the area to be constructed, represents the difference between the actual water content of the area to be constructed and the water content threshold of the corresponding soil type. of the area to be constructed.

[0066] In practical applications, the water content information characterizes the water content situation in the soil of the area to be constructed. Specifically, it may include the water content sensitivity coefficient and the actual water content.

[0067] In practical applications, during the expansion coefficient correction process, the water content sensitivity coefficient is used to describe the degree of volume expansion of the soil due to the increase in water content after excavation; the value range of the water content sensitivity coefficient of the expansion coefficient is 0 to 0.2, and it can be specifically pre-configured according to the on-site test data of the corresponding soil type or according to experience.

[0068] Here, by introducing the water content sensitivity coefficient in the expansion coefficient correction, it is possible to predict the impact of water content on the soil volume change characteristics during the excavation process, thereby improving the accuracy of the expansion coefficient correction result.

[0069] S902: Based on the particle size distribution information in the soil characteristic information, determine the correction factor matching the area to be constructed from the pre-configured correction factors.

[0070] In practical applications, according to the particle size distribution characteristics of different soil types, the correction factor for each soil type can be pre-configured. For example, for clay, its correction factor is pre-configured as 1.1, while for sand, its correction factor is pre-configured as 0.9.

[0071] S903: Based on the correction factor of each area to be constructed, correct the first expansion coefficient to obtain the expansion coefficient of the area to be constructed; the correction formula is expressed as: ; Wherein, represents the expansion coefficient obtained after correction of the area to be constructed, of the area to be constructed, represents the area to be constructed, Correction factor.

[0072] In one embodiment, as Figure 10 shown, when the construction type of the area to be constructed is filling, based on the soil characteristic information, correcting the initial volume change coefficient of the area to be constructed to obtain the soil volume change coefficient of the area to be constructed, that is, S803, may include S1001 to S1003.

[0073] S1001: Based on the water content information in the soil characteristic information, correcting a pre-configured initial compression ratio to obtain a first compression ratio, where the initial compression ratio is determined according to the soil type; the correction formula is expressed as: ; Wherein, represents the first compression ratio of the area to be constructed ; represents the initial compression ratio of the area to be constructed ; represents the water content sensitivity coefficient of the area to be constructed ; represents the difference between the actual water content of the area to be constructed and the water content threshold of the corresponding soil type.

[0074] In actual application, the water content information characterizes the water content situation in the soil of the area to be constructed. Specifically, it may include a water content sensitivity coefficient and an actual water content.

[0075] In actual application, during the compression ratio correction process, the water content sensitivity coefficient is used to describe the degree of volume change of the soil due to the decrease or increase of the water content after backfilling and compaction; the value range of the water content sensitivity coefficient of the compression ratio is 0 to 0.2, and it can be specifically configured in advance according to the on-site test data of the corresponding soil type or according to experience.

[0076] Here, by introducing the water content sensitivity coefficient in the compression ratio correction, it is possible to predict the influence of the water content on the soil volume change characteristics during the backfilling process, thereby improving the accuracy of the expansion coefficient correction result.

[0077] S1002: Based on the particle size distribution information in the soil characteristic information, determining a correction factor matching the area to be constructed from the pre-configured correction factors.

[0078] Specifically, based on the soil type in the soil characteristic information, a correction factor matching the area to be constructed can be determined from the pre-configured correction factors.

[0079] In actual application, correction factors for each soil type can be pre-configured according to the particle size distribution characteristics of different soil types. For example, for clay, its correction factor is pre-configured as 1.1, while for sandy soil, its correction factor is pre-configured as 0.9.

[0080] S1003: Based on the correction factor of each construction area to be constructed, correct the first compression ratio to obtain the compression ratio of the construction area to be constructed; the correction formula is expressed as: ; Wherein, represents the construction area to be constructed the compression ratio obtained after correction, represents the construction area to be constructed correction factor.

[0081] In actual application, in order to reduce the data processing volume and transmission volume of the MEC unit and reduce the bandwidth resources occupied by the communication between the MEC unit and the cloud service platform, when the drone monitors the area associated with the MEC unit, the MEC unit can perform relevant data processing and uploading.

[0082] Based on this, in an embodiment, as Figure 11 shown, the method may further include: S1101: The drone unit continuously sends heartbeat packets to the ground.

[0083] In actual application, during the process of the drone performing the inspection task, it can continuously send heartbeat packets to the ground. The heartbeat packets contain basic information such as the identity information, location, and status of the drone, which are used to inform the ground equipment of the location of the drone; the heartbeat packets can also be called data packets, and can also be called handshake requests, which are used to indicate that the drone hopes to establish a connection with the ground base station; the embodiments of the present application do not limit this, as long as its function can be achieved.

[0084] S1102: After receiving the heartbeat packet sent by the drone unit, the MEC unit of the data processing system authenticates the drone and sends an ACK to the drone unit after the verification passes.

[0085] In actual application, when the drone enters the wireless coverage range of the MEC unit, the MEC unit can detect the handshake request from the drone, that is, the heartbeat packet, and return an ACK, indicating that the signal has been successfully received and ready to start communication.

[0086] S1103: After receiving the ACK returned by the MEC unit, the drone unit sends a data upload request to the MEC unit.

[0087] S1104: In response to the data upload request, the MEC unit uploads the soil volume change information of the area to be constructed in the current sampling period to the cloud service platform; the soil volume change information includes the soil volume change coefficient of the area to be constructed, and the soil volume change coefficient is determined based on the sensor data of the area to be constructed.

[0088] In practical applications, S1101 to S1104 can represent the process of the MEC unit uploading the soil volume transformation information.

[0089] In practical applications, after receiving the data upload request sent by the UAV unit, the MEC unit can calculate the soil volume change coefficient of the area to be constructed, that is, execute S801 to S803, and upload the calculated soil change coefficient.

[0090] Here, the MEC unit only performs data analysis and upload when the UAV arrives at the area associated with the MEC unit, reducing the data processing volume of the MEC unit, thereby reducing the data processing pressure of the MEC unit, ensuring the safe and stable operation of the MEC unit. At the same time, the amount and frequency of transmitted data are reduced, not only reducing the bandwidth occupancy, but also reducing the load pressure caused by data transmission, further improving the reliability of the MEC unit.

[0091] In summary, the mapping image data processing method based on image transformation provided in the embodiments of the present application uses a UAV for multi-angle oblique photography. Compared with the manual on-site measurement method, it can not only quickly and accurately obtain high-resolution image data, thereby improving the data collection efficiency and accuracy, improving the accuracy and calculation efficiency of the earthwork calculation result, but also can adjust the monitoring area by adjusting the UAV path, thereby improving the monitoring coverage range, and can be applied to various complex terrains, improving the comprehensiveness of data collection; further, by performing image transformation on the remote sensing data collected by the UAV at different sampling points, the images collected from different perspectives can be aligned in the same coordinate system, realizing the consistency of the spatial positions of the remote sensing images collected under different conditions, thereby reducing the situation where the volume estimation deviation occurs due to the coordinate differences between the images, and improving the accuracy of the earthwork calculation result; further, through automatic detection point annotation and earthwork volume calculation, the errors caused by manual intervention can be reduced, and the work efficiency and the reliability of the calculation result can be improved.

[0092] It should be noted that when the mapping image data processing system based on image transformation provided in the above embodiments performs mapping image data processing based on image transformation, only the division of the above program modules is used for illustration. In actual applications, the above processing can be allocated to different program modules according to needs, that is, the internal structure of the system is divided into different program modules to complete all or part of the processing described above. In addition, the mapping image data processing system based on image transformation provided in the above embodiments and the embodiments of the mapping image data processing method based on image transformation belong to the same concept. For the specific implementation process, please refer to the method embodiments and will not be elaborated here.

[0093] It should be noted that "first", "second", etc. are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence.

[0094] In addition, the technical solutions described in the embodiments of the present application can be arbitrarily combined without conflict.

[0095] The above is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A mapping image data processing system based on image transformation, characterized in that: The system includes a drone unit and a cloud service platform; The drone unit includes a data acquisition module, an image processing module and a communication module; the data acquisition module is used to obtain image data of the area to be constructed when the drone performs oblique photography; the image processing module is used to perform image transformation on the image data, obtain corrected image data and send it to the cloud service platform using the communication module; The cloud service platform includes a data processing module, a model building module, a feature extraction module and a calculation module; the data processing module is used to generate three-dimensional point cloud data of the area to be constructed based on the corrected image data; the model building module is used to construct a digital elevation model DEM of the area to be constructed based on the three-dimensional point cloud data; and, according to the coordinates of at least one construction position preset in the area to be constructed, marking the detection points corresponding to each construction position in the DEM; the feature extraction module is used to obtain the construction structure information of each detection point from the DEM; the construction structure information includes the original elevation data of the corresponding construction position; the calculation module is used to calculate the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data of each construction position and the corresponding design elevation data.

2. The system according to claim 1, characterized in that The system also includes a mobile edge computing MEC unit; the MEC unit includes an identity authentication module and a response module; The drone unit is further configured to continuously send a heartbeat packet to the ground using the communication module, and after receiving an acknowledgment response ACK returned by the MEC unit, send a data upload request to the MEC unit; The MEC unit is used to authenticate the drone unit using the identity authentication module after receiving the heartbeat packet sent by the drone unit, and send an ACK to the drone unit after the identity authentication is passed; And, utilizing the response module, in response to the data upload request, uploading the soil volume change information of the area to be constructed within the current sampling period to the cloud service platform; the soil volume change information includes the soil volume change coefficient of the area to be constructed, and the soil volume change coefficient is determined based on the sensor data of the area to be constructed; The cloud service platform is used to calculate the initial value of earthwork excavation and filling in the area to be constructed based on the difference between the original elevation data of each construction location and the corresponding design elevation data by using the calculation module; And, based on the initial value of earthwork excavation and filling at each construction location and the corresponding soil volume change coefficient, the earthwork excavation and filling amount of the corresponding construction location is calculated.

3. A method for processing surveying and mapping image data based on image transformation, characterized in that: The method comprises: Use the drone unit in the data processing system to perform oblique photography to obtain image data of the area to be constructed; The drone unit performs image transformation on the image data to obtain corrected image data and sends the corrected image data to the cloud service platform of the data processing system; The cloud service platform generates three-dimensional point cloud data of the area to be constructed based on the corrected image data; Based on the three-dimensional point cloud data, a digital elevation model DEM of the area to be constructed is constructed; According to the coordinates of at least one construction location preset in the area to be constructed, marking a detection point corresponding to each construction location in the DEM; Acquire the construction structure information of each detection point from the DEM; the construction structure information includes the original elevation data of the corresponding construction location; Based on the difference between the original elevation data of each construction location and the corresponding design elevation data, the amount of earthwork excavation and filling in the area to be constructed is calculated.

4. The method according to claim 3, characterized in that The method further comprises: The drone unit continuously sends heartbeat packets to the ground; The MEC unit of the data processing system authenticates the drone after receiving the heartbeat packet sent by the drone unit, and sends an ACK to the drone unit after the authentication is passed; After receiving the ACK returned by the MEC unit, the UAV unit sends a data upload request to the MEC unit; In response to the data upload request, the MEC unit uploads the soil volume change information of the area to be constructed in the current sampling period to the cloud service platform; the soil volume change information includes the soil volume change coefficient of the area to be constructed, and the soil volume change coefficient is determined based on the sensor data of the area to be constructed.

5. The method according to claim 4, characterized in that The method of calculating the earthwork excavation and filling volume of the area to be constructed based on the difference between the original elevation data of each construction location and the corresponding design elevation data includes: Calculate the initial value of earthwork excavation and filling in the area to be constructed based on the difference between the original elevation data of each construction location and the corresponding design elevation data; The amount of earthwork excavation and filling in the area to be constructed is calculated based on the initial value of earthwork excavation and filling in the area to be constructed and the corresponding soil volume change coefficient.

6. The method according to claim 5, characterized in that Before calculating the amount of earthwork excavation and filling in the area to be constructed based on the initial value of earthwork excavation and filling in the area to be constructed and the corresponding soil volume change coefficient, the method further includes: The MEC unit determines the corresponding soil volume variation coefficient based on the soil type and construction type of the area to be constructed; wherein, The soil volume change coefficient is an expansion coefficient or a compression ratio, and the construction type is excavation or filling; when the construction type of the area to be constructed is excavation, the corresponding soil volume change coefficient is an expansion coefficient, and when the construction type of the area to be constructed is filling, the corresponding soil volume change coefficient is a compression ratio.

7. The method according to claim 6, characterized in that The determining of the corresponding soil volume variation coefficient based on the soil type and construction type of the area to be constructed includes: Based on the soil type and construction type of the area to be constructed, determining an initial volume change coefficient matching the area to be constructed from a pre-configured volume change coefficient list; Based on the sensor data of the area to be constructed, determining soil characteristic information of the area to be constructed; the soil characteristic information includes water content information and particle distribution information; Based on the soil characteristic information, the initial volume variation coefficient of the area to be constructed is corrected to obtain the soil volume variation coefficient of the area to be constructed.

8. The method according to claim 7, characterized in that When the construction type of the area to be constructed is excavation, the initial volume change coefficient of the area to be constructed is corrected based on the soil characteristic information to obtain the soil volume change coefficient of the area to be constructed, including: Based on the water content information in the soil characteristic information, the pre-configured initial expansion coefficient is corrected to obtain a first expansion coefficient, wherein the initial expansion coefficient is determined according to the soil type; the correction formula is expressed as: ； in, Indicates the area to be constructed The first expansion coefficient, Indicates the area to be constructed Initial expansion coefficient, Indicates the area to be constructed The moisture content sensitivity coefficient, Indicates the area to be constructed The difference between the actual water content and the water content threshold of the corresponding soil type; Based on the particle distribution information in the soil characteristic information, determining a correction factor matching the area to be constructed from pre-configured correction factors; Based on the correction factor of each area to be constructed, the first expansion coefficient is corrected to obtain the expansion coefficient of the area to be constructed; the correction formula is expressed as: ； in, Indicates the area to be constructed The expansion coefficient obtained after correction is Indicates the area to be constructed correction factor.

9. The method according to claim 7, characterized in that: When the construction type of the area to be constructed is filling, the initial volume change coefficient of the area to be constructed is corrected based on the soil characteristic information to obtain the soil volume change coefficient of the area to be constructed, including: Based on the water content information in the soil characteristic information, the pre-configured initial compression ratio is corrected to obtain a first compression ratio, where the initial compression ratio is determined by the soil type; the correction formula is expressed as: ； in, Indicates the area to be constructed The first compression ratio, Indicates the area to be constructed The initial compression ratio, Indicates the area to be constructed The moisture content sensitivity coefficient, Indicates the area to be constructed The difference between the actual water content and the water content threshold of the corresponding soil type; Based on the particle distribution information in the soil characteristic information, determining a correction factor matching the area to be constructed from pre-configured correction factors; Based on the correction factor of each area to be constructed, the first compression ratio is corrected to obtain the compression ratio of the area to be constructed; the correction formula is expressed as: ； in, Indicates the area to be constructed The compression ratio after correction is Indicates the area to be constructed correction factor.

10. The method according to any one of claims 3 to 9, characterized in that The performing image transformation on the image data to obtain corrected image data comprises: The image data are respectively subjected to radiation correction, geometric correction, multi-view consistency correction and shadow correction to obtain corrected image data.

Images