Real scene three-dimensional reconstruction technology based on remote sensing image and oblique photography data

Abstract

The invention discloses a live-action three-dimensional reconstruction technology based on remote sensing images and oblique photography data, and particularly relates to the technical field of photography. Comprising a data acquisition module, a data preprocessing module, a multi-view image matching and adjusting module, a live-action three-dimensional modeling module, a live-action three-dimensional model post-processing and optimizing module and a live-action three-dimensional model output module. According to the method, the innovation of a live-action three-dimensional reconstruction technology is realized by combining the remote sensing image and the oblique photography data, the precision and efficiency of three-dimensional reconstruction are remarkably improved, the efficient management and processing of large-scale data are realized, the comprehensiveness and accuracy of the data are ensured, the reconstruction quality is accurately evaluated through multi-dimensional data analysis, and the reconstruction efficiency is improved. Potential problems can be found in time, the real-scene three-dimensional module carries out post-processing, and a real-time monitoring and timely response mechanism of the module is optimized, so that the safety and stability of the reconstruction process are effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of photography technology, and more specifically, to a real-scene three-dimensional reconstruction technology based on remote sensing images and oblique photography data. Background Art

[0002] In the field of three-dimensional reconstruction technology, traditional methods mainly rely on single remote sensing image data or ground measurement data for modeling. Although these methods have achieved certain results, they still have many limitations in practical applications. For example, although traditional remote sensing image data can cover a large area, its vertical information acquisition ability is limited, and it is difficult to capture the fine structure and texture information of ground objects, resulting in insufficient detail in the reconstructed model. Although the ground measurement method can obtain high-precision three-dimensional data, it has a long operation cycle, high cost, and is difficult to apply to the rapid reconstruction of large areas.

[0003] The emergence of oblique photogrammetry technology has brought new solutions to the field of three-dimensional reconstruction. This technology carries multiple sensors on the same flying platform to simultaneously acquire image data of ground objects from multiple angles, thereby being able to more comprehensively and realistically reflect the three-dimensional shape of ground objects. However, relying solely on oblique photography data for three-dimensional reconstruction also has certain shortcomings, such as large amounts of data to be processed and high computational complexity.

[0004] Therefore, how to effectively integrate the advantages of remote sensing images and oblique photography data to achieve high-precision and high-efficiency three-dimensional reconstruction of real scenes has become a research hotspot in the current field of three-dimensional reconstruction technology. At present, some studies have attempted to combine these two types of data for three-dimensional reconstruction, but there are still many challenges in data fusion, model construction and optimization. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a real-scene three-dimensional reconstruction technology based on remote sensing images and oblique photography data, and solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solution: a real scene three-dimensional reconstruction technology based on remote sensing images and oblique photography data, comprising:

[0007] Data acquisition module: used to collect basic remote sensing image data, oblique photogrammetry data, 3D reconstruction model parameters, and system monitoring and evaluation indicators of each sub-data area, and transmit the collected data to the data preprocessing module;

[0008] Data preprocessing module: including remote sensing image basic data analysis unit, oblique photogrammetry data analysis unit, 3D reconstruction model parameter analysis unit and system monitoring and evaluation index analysis unit, which are used to analyze the data transmitted by the data acquisition module and transmit the analyzed data to the real scene 3D module modeling module;

[0009] Multi-view image matching and adjustment module: used to process multi-view image data from oblique photography, etc., through feature extraction, feature matching, mismatch elimination and bundle adjustment, etc., to eliminate geometric inconsistencies between images, accurately estimate camera parameters and 3D coordinates of feature points, and generate accurate 3D point cloud data;

[0010] Real scene 3D module modeling module: used to establish a comprehensive analysis model, import the data transmitted by the data preprocessing module into the comprehensive analysis model, calculate the comprehensive abnormal index of the target data area, and transmit it to the real scene 3D module post-processing and optimization module;

[0011] Real scene 3D module post-processing and optimization module: used to establish a comprehensive anomaly index threshold, judge the comprehensive anomaly index of the target data area through the comprehensive anomaly index threshold, and issue a warning signal based on the judgment result;

[0012] The real-scene 3D module output module uses visualization technology to display the comprehensive anomaly index of the target data area and the target real-scene 3D reconstruction quality.

[0013] Preferably, the basic data of remote sensing images include image resolution, image spectral range, image radiation resolution and image geographic positioning accuracy, which are marked as Rm, Rs, Ra and Rg respectively; the oblique photogrammetry data include camera tilt angle, camera focal length, photography instantaneous exposure time and photography point cloud density, which are marked as Oc, 0a, Oe and Op respectively; the three-dimensional reconstruction model parameters include model surface roughness, model texture resolution, model geometric accuracy and model construction time, which are marked as Dm, Dt, Dg and Dc respectively; the system monitoring and evaluation indicators include reconstruction model completeness, data processing time, system resource consumption and deviation between the reconstruction model and the actual scene, which are marked as Sm, Sd, Sr and Sf respectively.

[0014] Preferably, the remote sensing image basic data analysis unit is used to establish a remote sensing image basic data analysis model, import the remote sensing image basic data transmitted by the data acquisition module into the remote sensing image basic data analysis model, and calculate the remote sensing image basic data evaluation value of each sub-data area, which is specifically expressed as: TR i Represents the evaluation value of the remote sensing image basic data of the ith sub-data area, Rm i Represents the image resolution of the ith sub-data area, Rs iRepresents the image spectral range of the i-th sub-data area, Ra i represents the image radiation resolution of the ith sub-data area, Rgi represents the image geographic positioning accuracy of the ith sub-data area, n represents the number of sub-data areas, and μ1 represents other influencing factors of the evaluation value of the remote sensing image basic data.

[0015] Preferably, the oblique photogrammetry data analysis unit is used to establish an oblique photogrammetry data analysis model, import the oblique photogrammetry data transmitted by the data acquisition module into the oblique photogrammetry data analysis model, and calculate the oblique photogrammetry data evaluation value of each sub-data area, which is specifically expressed as: TO i represents the oblique photogrammetry data evaluation value of the ith sub-data area, Oc i represents the camera tilt angle of the ith sub-data area, Oa i represents the focal length of the camera in the ith sub-data area, Oe i represents the photographic instantaneous exposure time of the ith sub-data area, Opi represents the photographic point cloud density of the ith sub-data area, n represents the number of sub-data areas, and μ2 represents other influencing factors of the evaluation value of the oblique photogrammetry data.

[0016] Preferably, the 3D reconstruction model parameter analysis unit is used to establish a 3D reconstruction model parameter analysis model, import the 3D reconstruction model parameters transmitted by the data acquisition module into the 3D reconstruction model parameter analysis model, and calculate the 3D reconstruction model parameter evaluation value of each sub-data area, which is specifically expressed as: TD i represents the 3D reconstruction model parameter evaluation value of the i-th sub-data region, Dm i represents the model surface roughness of the ith sub-data area, Dt i represents the model texture resolution of the ith sub-data area, Dgi represents the model geometric accuracy of the ith sub-data area, and Dc i represents the model building time of the i-th sub-data region, n represents the number of sub-data regions, and μ3 represents other influencing factors of the 3D reconstruction model parameter evaluation value.

[0017] Preferably, the system monitoring and evaluation index analysis unit is used to establish a system monitoring and evaluation index analysis model, import the system monitoring and evaluation index transmitted by the data acquisition module into the system monitoring and evaluation index analysis model, and calculate the system evaluation value of each sub-data area, which is specifically expressed as: TS i represents the system evaluation value of the ith sub-data area, Sm i Indicates the completeness of the reconstruction model of the ith sub-data region, Sd i represents the data processing time of the ith sub-data area, Sri represents the system resource consumption of the ith sub-data area, Sf i represents the deviation between the reconstructed model of the ith sub-data region and the actual scene, n represents the number of sub-data regions, and μ4 represents other influencing factors of the system evaluation value.

[0018] Preferably, the comprehensive analysis model is specifically expressed as: η represents the comprehensive anomaly index of the target data area, TR i represents the evaluation value of the remote sensing image basic data of the ith sub-data area, TO i represents the oblique photogrammetry data evaluation value of the i-th sub-data area, TD i represents the evaluation value of the 3D reconstruction model parameters of the i-th sub-data region, TS i represents the system evaluation value of the ith sub-data area, n represents the number of sub-data areas, and λ represents other influencing factors of the comprehensive anomaly index.

[0019] Preferably, the preset value of the comprehensive abnormality index is marked as η Def , when η Def >η, it means that the preset value of the comprehensive anomaly index is greater than the comprehensive anomaly index of the target data area, indicating that the quality of the target real scene 3D reconstruction is good, then the data acquisition module is returned to keep monitoring the target real scene 3D reconstruction data. When η Def When <η, it means that the preset value of the comprehensive abnormality index is less than the comprehensive abnormality index of the target data area, indicating that the quality of the target real scene 3D reconstruction is abnormal, and an early warning signal is sent to the management terminal.

[0020] Technical effects and advantages of the present invention:

[0021] The present invention uses a data acquisition module to decompose a huge data area into several sub-areas through a refined time division strategy, so that data processing work can be carried out in an orderly manner. This modular processing method not only improves the data processing efficiency, but also makes it possible to conduct in-depth analysis of specific areas, laying a solid foundation for subsequent reconstruction work; various types of key data are collected through the data acquisition module, including remote sensing images, oblique photogrammetry data, 3D reconstruction model parameters, and system monitoring and evaluation indicators. The timely and accurate collection of these data provides strong support for subsequent data analysis and reconstruction work, and ensures the stability and reliability of the entire system; the data preprocessing module uses advanced mathematical models and algorithms to conduct in-depth analysis and processing of the collected data, and through multiple-dimensional analysis of remote sensing image basic data analysis, oblique photogrammetry data analysis, 3D reconstruction model parameter analysis, and system monitoring and evaluation indicator analysis, it can accurately evaluate the data. The quality and reliability of the data can be evaluated, providing a scientific basis for subsequent decision-making and early warning; the results of each analysis unit are summarized and integrated through the real-scene 3D module modeling module, and the comprehensive anomaly index of the target data area is obtained through a complex calculation model, which not only reflects the overall situation of the data area, but also can reveal potential anomalies and problems. The existence of the real-scene 3D module modeling module enables the system to evaluate the quality of the data area more comprehensively and objectively, providing strong support for subsequent early warning and response measures; the real-scene 3D module post-processing and optimization module monitors the operating status of the system in real time according to the comprehensive anomaly index obtained by the real-scene 3D module modeling module. Once an anomaly or potential risk is detected, the real-scene 3D module post-processing and optimization module will immediately trigger the early warning mechanism and send an alarm to the management personnel. This timely early warning mechanism helps managers to respond quickly and take measures to prevent the problem from further expanding, ensuring the stable operation of the system and the accuracy of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] refer to Figure 1The present invention shows a real-scene 3D reconstruction technology based on remote sensing images and oblique photography data, including a data acquisition module, a data preprocessing module, a multi-view image matching and adjustment module, a real-scene 3D modeling module, a real-scene 3D model post-processing and optimization module, and a real-scene 3D model output module.

[0025] The data acquisition module is used to determine the target real scene 3D reconstruction data as the target data area, divide the target data area into various sub-data areas by equal time division, and mark them as 1, 2...n in sequence.

[0026] The data acquisition module is used to collect basic remote sensing image data, oblique photogrammetry data, three-dimensional reconstruction model parameters, and system monitoring and evaluation indicators of each sub-data area, and transmit the collected data to the data preprocessing module.

[0027] The basic data of remote sensing images include image resolution, image spectral range, image radiation resolution and image geographic positioning accuracy, which are marked as Rm, Rs, Ra and Rg respectively. The oblique photogrammetry data include camera tilt angle, camera focal length, photography instantaneous exposure time and photography point cloud density, which are marked as Oc, Oa, Oe and Op respectively. The three-dimensional reconstruction model parameters include model surface roughness, model texture resolution, model geometric accuracy and model construction time, which are marked as Dm, Dt, Dg and Dc respectively. The system monitoring and evaluation indicators include reconstruction model completeness, data processing time, system resource consumption and deviation between the reconstruction model and the actual scene, which are marked as Sm, Sd, Sr and Sf respectively.

[0028] The data preprocessing module includes a remote sensing image basic data analysis unit, an oblique photogrammetry data analysis unit, a three-dimensional reconstruction model parameter analysis unit, and a system monitoring and evaluation index analysis unit, which are used to analyze the data transmitted by the data acquisition module and transmit the analyzed data to the real-scene three-dimensional module modeling module.

[0029] The remote sensing image basic data analysis unit is used to establish a remote sensing image basic data analysis model, import the remote sensing image basic data transmitted by the data acquisition module into the remote sensing image basic data analysis model, and calculate the remote sensing image basic data evaluation value of each sub-data area, which is specifically expressed as: TR i Represents the evaluation value of the remote sensing image basic data of the ith sub-data area, Rm i Represents the image resolution of the ith sub-data area, Rs i Represents the image spectral range of the i-th sub-data area, Ra irepresents the image radiation resolution of the ith sub-data area, Rgi represents the image geographic positioning accuracy of the ith sub-data area, n represents the number of sub-data areas, and μ1 represents other influencing factors of the evaluation value of the remote sensing image basic data.

[0030] The oblique photogrammetry data analysis unit is used to establish an oblique photogrammetry data analysis model, import the oblique photogrammetry data transmitted by the data acquisition module into the oblique photogrammetry data analysis model, and calculate the oblique photogrammetry data evaluation value of each sub-data area, which is specifically expressed as: TO i represents the oblique photogrammetry data evaluation value of the ith sub-data area, Oc i represents the camera tilt angle of the ith sub-data area, Oa i represents the focal length of the camera in the ith sub-data area, Oe i represents the photographic instantaneous exposure time of the ith sub-data area, Opi represents the photographic point cloud density of the ith sub-data area, n represents the number of sub-data areas, and μ2 represents other influencing factors of the evaluation value of the oblique photogrammetry data.

[0031] The 3D reconstruction model parameter analysis unit is used to establish a 3D reconstruction model parameter analysis model, import the 3D reconstruction model parameters transmitted by the data acquisition module into the 3D reconstruction model parameter analysis model, and calculate the 3D reconstruction model parameter evaluation value of each sub-data area, which is specifically expressed as: TD i represents the 3D reconstruction model parameter evaluation value of the i-th sub-data region, Dm i represents the model surface roughness of the ith sub-data area, Dt i represents the model texture resolution of the ith sub-data area, Dgi represents the model geometric accuracy of the ith sub-data area, and Dc i represents the model building time of the i-th sub-data region, n represents the number of sub-data regions, and μ3 represents other influencing factors of the 3D reconstruction model parameter evaluation value.

[0032] The system monitoring and evaluation index analysis unit is used to establish a system monitoring and evaluation index analysis model, import the system monitoring and evaluation index transmitted by the data acquisition module into the system monitoring and evaluation index analysis model, and calculate the system evaluation value of each sub-data area, which is specifically expressed as: TS i represents the system evaluation value of the ith sub-data area, Sm i Indicates the completeness of the reconstruction model of the ith sub-data region, Sd i represents the data processing time of the ith sub-data area, Sr i represents the system resource consumption of the ith sub-data area, Sf irepresents the deviation between the reconstructed model of the ith sub-data region and the actual scene, n represents the number of sub-data regions, and μ4 represents other influencing factors of the system evaluation value.

[0033] The multi-view image matching and adjustment module is used to process multi-view image data from oblique photography, etc., and eliminates geometric inconsistencies between images through steps such as feature extraction, feature matching, mismatch elimination, and bundle adjustment, accurately estimates camera parameters and three-dimensional coordinates of feature points, and generates accurate three-dimensional point cloud data.

[0034] The real-scene 3D module modeling module is used to establish a comprehensive analysis model, import the data transmitted by the data preprocessing module into the comprehensive analysis model, calculate the comprehensive abnormality index of the target data area, and transmit it to the real-scene 3D module post-processing and optimization module.

[0035] The comprehensive analysis model is specifically expressed as: η represents the comprehensive anomaly index of the target data area, TR i represents the evaluation value of the remote sensing image basic data of the ith sub-data area, TO i represents the oblique photogrammetry data evaluation value of the i-th sub-data area, TD i represents the evaluation value of the 3D reconstruction model parameters of the i-th sub-data region, TS i represents the system evaluation value of the ith sub-data area, n represents the number of sub-data areas, and λ represents other influencing factors of the comprehensive anomaly index.

[0036] The real-scene three-dimensional module post-processing and optimization module is used to establish a comprehensive anomaly index threshold, judge the comprehensive anomaly index of the target data area through the comprehensive anomaly index threshold, and issue a warning signal according to the judgment result.

[0037] The preset value of the comprehensive abnormality index is marked as η Def , when η Def >η, it means that the preset value of the comprehensive anomaly index is greater than the comprehensive anomaly index of the target data area, indicating that the quality of the target real scene 3D reconstruction is good, then the data acquisition module is returned to keep monitoring the target real scene 3D reconstruction data. When η Def When <η, it means that the preset value of the comprehensive abnormality index is less than the comprehensive abnormality index of the target data area, indicating that the quality of the target real scene 3D reconstruction is abnormal, and an early warning signal is sent to the management terminal.

[0038] The real scene 3D module output module displays the comprehensive abnormality index of the target data area and the target real scene 3D reconstruction quality through visualization technology.

[0039] The present invention uses a data acquisition module to decompose a huge data area into several sub-areas through a refined time division strategy, so that data processing work can be carried out in an orderly manner. This modular processing method not only improves the data processing efficiency, but also makes it possible to conduct in-depth analysis of specific areas, laying a solid foundation for subsequent reconstruction work; various types of key data are collected through the data acquisition module, including remote sensing images, oblique photogrammetry data, 3D reconstruction model parameters, and system monitoring and evaluation indicators. The timely and accurate collection of these data provides strong support for subsequent data analysis and reconstruction work, and ensures the stability and reliability of the entire system; the data preprocessing module uses advanced mathematical models and algorithms to conduct in-depth analysis and processing of the collected data, and through multiple-dimensional analysis of remote sensing image basic data analysis, oblique photogrammetry data analysis, 3D reconstruction model parameter analysis, and system monitoring and evaluation indicator analysis, it can accurately evaluate the data. The quality and reliability of the data can be evaluated, providing a scientific basis for subsequent decision-making and early warning; the results of each analysis unit are summarized and integrated through the real-scene 3D module modeling module, and the comprehensive anomaly index of the target data area is obtained through a complex calculation model, which not only reflects the overall situation of the data area, but also can reveal potential anomalies and problems. The existence of the real-scene 3D module modeling module enables the system to evaluate the quality of the data area more comprehensively and objectively, providing strong support for subsequent early warning and response measures; the real-scene 3D module post-processing and optimization module monitors the operating status of the system in real time according to the comprehensive anomaly index obtained by the real-scene 3D module modeling module. Once an anomaly or potential risk is detected, the real-scene 3D module post-processing and optimization module will immediately trigger the early warning mechanism and send an alarm to the management personnel. This timely early warning mechanism helps managers to respond quickly and take measures to prevent the problem from further expanding, ensuring the stable operation of the system and the accuracy of the data.

[0040] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0041] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A real scene 3D reconstruction technology based on remote sensing images and oblique photography data, characterized in that: include: Data acquisition module: used to collect basic remote sensing image data, oblique photogrammetry data, 3D reconstruction model parameters, and system monitoring and evaluation indicators of each sub-data area, and transmit the collected data to the data preprocessing module; Data preprocessing module: including remote sensing image basic data analysis unit, oblique photogrammetry data analysis unit, 3D reconstruction model parameter analysis unit and system monitoring and evaluation index analysis unit, which are used to analyze the data transmitted by the data acquisition module and transmit the analyzed data to the real scene 3D module modeling module; Multi-view image matching and adjustment module: used to process multi-view image data from oblique photography, etc., through feature extraction, feature matching, mismatch elimination and bundle adjustment, etc., to eliminate geometric inconsistencies between images, accurately estimate camera parameters and 3D coordinates of feature points, and generate accurate 3D point cloud data; Real scene 3D module modeling module: used to establish a comprehensive analysis model, import the data transmitted by the data preprocessing module into the comprehensive analysis model, calculate the comprehensive abnormal index of the target data area, and transmit it to the real scene 3D module post-processing and optimization module; Real scene 3D module post-processing and optimization module: used to establish a comprehensive anomaly index threshold, judge the comprehensive anomaly index of the target data area through the comprehensive anomaly index threshold, and issue a warning signal based on the judgment result; The real-scene 3D module output module uses visualization technology to display the comprehensive anomaly index of the target data area and the target real-scene 3D reconstruction quality.

2. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The basic data of remote sensing images include image resolution, image spectral range, image radiation resolution and image geographic positioning accuracy, which are marked as Rm, Rs, Ra and Rg respectively. The oblique photogrammetry data include camera tilt angle, camera focal length, photography instantaneous exposure time and photography point cloud density, which are marked as Oc, 0a, 0e and Op respectively. The three-dimensional reconstruction model parameters include model surface roughness, model texture resolution, model geometric accuracy and model construction time, which are marked as Dm, Dt, Dg and Dc respectively. The system monitoring and evaluation indicators include reconstruction model completeness, data processing time, system resource consumption and deviation between the reconstruction model and the actual scene, which are marked as Sm, Sd, Sr and Sf respectively.

3. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The remote sensing image basic data analysis unit is used to establish a remote sensing image basic data analysis model, import the remote sensing image basic data transmitted by the data acquisition module into the remote sensing image basic data analysis model, and calculate the remote sensing image basic data evaluation value of each sub-data area, which is specifically expressed as: TR i Represents the evaluation value of the remote sensing image basic data of the ith sub-data area, Rm i Represents the image resolution of the ith sub-data area, Rs i Represents the image spectral range of the i-th sub-data area, Ra i represents the image radiation resolution of the ith sub-data area, Rgi represents the image geographic positioning accuracy of the ith sub-data area, n represents the number of sub-data areas, and μ1 represents other influencing factors of the evaluation value of the remote sensing image basic data.

4. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The oblique photogrammetry data analysis unit is used to establish an oblique photogrammetry data analysis model, import the oblique photogrammetry data transmitted by the data acquisition module into the oblique photogrammetry data analysis model, and calculate the oblique photogrammetry data evaluation value of each sub-data area, which is specifically expressed as: TO i represents the oblique photogrammetry data evaluation value of the ith sub-data area, Oc i represents the camera tilt angle of the ith sub-data area, Oa i represents the focal length of the camera in the ith sub-data area, Oe i represents the photographic instantaneous exposure time of the ith sub-data area, Opi represents the photographic point cloud density of the ith sub-data area, n represents the number of sub-data areas, and μ2 represents other influencing factors of the evaluation value of the oblique photogrammetry data.

5. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The 3D reconstruction model parameter analysis unit is used to establish a 3D reconstruction model parameter analysis model, import the 3D reconstruction model parameters transmitted by the data acquisition module into the 3D reconstruction model parameter analysis model, and calculate the 3D reconstruction model parameter evaluation value of each sub-data area, which is specifically expressed as: TD i represents the 3D reconstruction model parameter evaluation value of the i-th sub-data region, Dm i represents the model surface roughness of the ith sub-data area, Dt i represents the model texture resolution of the ith sub-data area, Dgi represents the model geometric accuracy of the ith sub-data area, and Dc i represents the model building time of the i-th sub-data region, n represents the number of sub-data regions, and μ3 represents other influencing factors of the 3D reconstruction model parameter evaluation value.

6. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The system monitoring and evaluation index analysis unit is used to establish a system monitoring and evaluation index analysis model, import the system monitoring and evaluation index transmitted by the data acquisition module into the system monitoring and evaluation index analysis model, and calculate the system evaluation value of each sub-data area, which is specifically expressed as: TS i represents the system evaluation value of the ith sub-data area, Sm i Indicates the completeness of the reconstruction model of the ith sub-data region, Sd i represents the data processing time of the ith sub-data area, Sr i represents the system resource consumption of the ith sub-data area, Sf i represents the deviation between the reconstructed model of the ith sub-data region and the actual scene, n represents the number of sub-data regions, and μ4 represents other influencing factors of the system evaluation value.

7. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The comprehensive analysis model is specifically expressed as: η represents the comprehensive anomaly index of the target data area, TR i represents the evaluation value of the remote sensing image basic data of the ith sub-data area, TO i represents the oblique photogrammetry data evaluation value of the i-th sub-data area, TD i represents the evaluation value of the 3D reconstruction model parameters of the i-th sub-data region, TS i represents the system evaluation value of the ith sub-data area, n represents the number of sub-data areas, and λ represents other influencing factors of the comprehensive anomaly index.

8. The real scene 3D reconstruction technology based on remote sensing images and oblique photography data according to claim 1, characterized in that: The preset value of the comprehensive abnormality index is marked as η Def , when η Def >η, it means that the preset value of the comprehensive anomaly index is greater than the comprehensive anomaly index of the target data area, indicating that the quality of the target real scene 3D reconstruction is good, then the data acquisition module is returned to keep monitoring the target real scene 3D reconstruction data. When η Def When <η, it means that the preset value of the comprehensive abnormality index is less than the comprehensive abnormality index of the target data area, indicating that the quality of the target real scene 3D reconstruction is abnormal, and an early warning signal is sent to the management terminal.

Images