Optical satellite image data processing method and device
By constructing a joint adjustment model and iteratively solving the attitude micro-vibration parameters, the micro-vibration distortion in optical satellite images is accurately compensated, solving the problem of insufficient image geometric accuracy and sharpness in existing technologies, and realizing efficient image data processing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-03
- Publication Date
- 2026-03-31
AI Technical Summary
Existing technologies struggle to accurately detect and compensate for micro-vibration distortion in optical satellite imagery, leading to a decrease in image geometric accuracy and clarity. Furthermore, existing methods cannot effectively integrate micro-vibration models with the geometric calibration of the satellite platform, resulting in information loss due to the introduction of image resampling processes.
By constructing a joint adjustment model, using optical satellite imagery data from the main band and secondary bands, the connection points are extracted and the attitude micro-vibration parameters are used as variables for iterative solution, thereby correcting the rigorous imaging model, directly correcting the image data, and avoiding secondary resampling.
It achieves precise compensation for micro-vibrations, improves the geometric accuracy and clarity of images, avoids information loss, and enhances the quantitative application potential of imaging products.
Smart Images
Figure CN121761843A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of optical remote sensing satellite technology, and in particular to an optical satellite image data processing method and apparatus. Background Technology
[0002] High-resolution Earth observation satellites provide detailed surface information, and the geometric quality of their images is fundamental for advanced applications such as precision mapping, stereo monitoring, and change detection. However, during satellite operation, moving components such as flywheels and solar panel drive mechanisms generate high-frequency mechanical vibrations, or micro-vibrations. These micro-vibrations are transmitted to payloads such as cameras, causing jitter in the imaging optical path. This introduces geometric distortions such as ripples and jagged edges into the acquired images, severely reducing their geometric accuracy and clarity and limiting their effective applications. Therefore, accurately detecting and compensating for micro-vibration distortions in satellite imagery is a pressing technical challenge in the field of high-resolution remote sensing data processing.
[0003] To address these issues, existing technologies typically employ a separate detection and compensation processing strategy. However, satellite-borne micro-vibrations are often complex motions resulting from the coupling of multiple vibration sources. The simplified parametric models used in existing technologies struggle to accurately describe the true physical processes of these micro-vibrations, especially for high-frequency components, where model fitting accuracy is limited, leading to incomplete correction and residual geometric errors in the image. Secondly, the micro-vibration detection process is independent of the satellite's rigorous imaging geometry model, while the compensation process is performed on an already generated and fixed image product. This inconsistency in processing flow prevents the micro-vibration model's solution accuracy from achieving a unified constraint and optimization with the satellite platform's geometric calibration accuracy, compromising the overall robustness and accuracy of the system. Finally, the secondary processing of the image product inevitably introduces additional image resampling. Multiple resampling operations result in the loss of image radiometric information and blurring of details, reducing image clarity and quantitative application potential. Summary of the Invention
[0004] This invention provides an optical satellite image data processing method and apparatus to solve the technical problems existing in the prior art.
[0005] This invention provides a method for processing optical satellite image data, comprising the following steps: Acquire optical satellite imagery data containing at least a main band and a secondary band, and extract the connection points between the main band and the secondary band; Using the attitude micro-vibration parameters corresponding to the main CCD scan lines in the main band of the optical satellite image data as variables, and aiming to minimize the residuals of the tie point observation equation and the virtual ground control point observation equation, a joint adjustment model is constructed; the attitude micro-vibration parameters include the attitude disturbance angle along the track direction and the attitude disturbance angle perpendicular to the track direction corresponding to each CCD scan line. The joint adjustment model is iteratively solved to obtain the attitude micro-vibration parameters; wherein, during the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is calculated based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence. The rigorous imaging model is corrected based on the attitude micro-vibration parameters, and sensor calibration is performed on the optical satellite image data based on the corrected rigorous imaging model.
[0006] According to an optical satellite imagery data processing method provided by the present invention, the iterative solution of the joint adjustment model includes: Based on the residuals of the observation equations of the connection points solved in the current iteration in the corresponding direction, determine the sensitivity index values in the corresponding direction in the current iteration. Determine whether the sensitivity index value meets the preset convergence condition; If the sensitivity index value does not meet the preset convergence condition, the weight of the connection point observation equation in the corresponding direction is adjusted according to the sensitivity index value in the next iteration. Based on the adjusted weights, continue executing the steps of determining the sensitivity index value in the corresponding direction of the next iteration based on the residual of the connection point observation equation in the corresponding direction under the next iteration, and adjusting the weights of the connection point observation equation in the corresponding direction under the next iteration based on the sensitivity index value, until the sensitivity index value in the corresponding direction meets the preset convergence condition.
[0007] According to the optical satellite image data processing method provided by the present invention, the step of determining the sensitivity index value in the corresponding direction based on the residual of the connection point observation equation solved in the corresponding direction in the current iteration includes: Based on the residuals of the connection points in the corresponding directions obtained in the current iteration, determine the normalized standard deviation of the observation equations of the connection points in the corresponding directions in the current iteration. The theoretical minimum standard deviation is obtained based on the standard deviation of each sub-unit within the preset imaging time window before optimization. Determine the maximum standard deviation of the residuals within the preset imaging time window before optimization; Based on the normalized standard deviation, the theoretical minimum standard deviation, and the maximum standard deviation, determine the sensitivity index value in the corresponding direction for the current iteration round.
[0008] According to an optical satellite image data processing method provided by the present invention, adjusting the weights of the connection point observation equation in the corresponding direction in the next iteration based on the sensitivity index value includes: The weight adjustment step size is determined based on the difference between the sensitivity index value of the corresponding direction in the current iteration and the sensitivity index value of the corresponding direction in the previous iteration. Adjust the step size and the weight of the connection point observation equation in the corresponding direction according to the weights, and adjust the weight of the connection point observation equation in the corresponding direction in the next iteration.
[0009] According to an optical satellite image data processing method provided by the present invention, the connection point observation equation is constructed in the following manner: Convert the latitude and longitude coordinates corresponding to the connection points into spatial rectangular coordinates; Obtain the camera station coordinates corresponding to the imaging time of the CCD scan line, and subtract them from the spatial rectangular coordinates to determine the line-of-sight vector from the camera station to the connection point; The line-of-sight vector is subjected to a first rotation transformation using a rotation matrix from the spatial rectangular coordinates to the camera coordinate system; Based on the attitude micro-vibration parameters to be solved, an angle-compensated rotation matrix is constructed, and a second rotation transformation is performed on the line-of-sight vector after the first rotation transformation. Based on the line-of-sight vector after the second rotation transformation, the theoretical row and column direction pointing angles of the connection point are obtained; Based on the established functional relationship between the theoretical row and column direction pointing angles and the actual observed row and column direction pointing angles of the connection points, the observation equations for the connection points are constructed.
[0010] According to an optical satellite image data processing method provided by the present invention, the virtual ground control point observation equation is constructed in the following manner: By performing intersection calculations between the observation rays at the connection point and the auxiliary digital elevation model, the initial coordinates of the virtual ground control point corresponding to the connection point are obtained. Based on the functional relationship between the coordinates of the virtual ground control point to be solved and the initial value of the virtual ground control point coordinates corresponding to the connection point, the observation equation of the virtual ground control point is constructed.
[0011] The present invention also provides an optical satellite image data processing apparatus, comprising: The acquisition module is used to acquire optical satellite image data containing at least a main band and a secondary band, and to extract the connection points between the main band and the secondary band. The model building module is used to construct a joint adjustment model with the attitude micro-vibration parameters corresponding to the main CCD scan line in the main band of the optical satellite image data as variables, and with the goal of minimizing the residuals of the tie point observation equation and the virtual ground control point observation equation; the attitude micro-vibration parameters include the attitude perturbation angle along the track direction and the attitude perturbation angle perpendicular to the track direction corresponding to each CCD scan line; The iterative solution module is used to iteratively solve the joint adjustment model to obtain the attitude micro-vibration parameters. During the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is calculated based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence. The correction module is used to correct the rigorous imaging model according to the attitude micro-vibration parameters, and to perform sensor correction on the optical satellite image data according to the corrected rigorous imaging model.
[0012] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the optical satellite image data processing method or the cooling method described above.
[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the optical satellite image data processing method or the cooling method described above.
[0014] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the optical satellite image data processing method or the cooling method described above.
[0015] The optical satellite imagery data processing method and apparatus provided by this invention acquires optical satellite imagery data containing at least a main band and a secondary band, and extracts the connection points between them. Using the attitude disturbance angles along the orbit and perpendicular to the orbit corresponding to the main CCD scan line in the main band of the satellite imagery as variables, a joint adjustment model is constructed with the objective of minimizing the residuals of the connection point observation equations and the virtual ground control point observation equations. This model is iteratively solved, and during the iterative solution process, sensitivity indices are calculated based on the residuals of the connection point observation equations in the corresponding directions obtained from the current solution, and the weights of the connection point observation equations in the corresponding directions are updated according to the sensitivity indices until convergence, yielding attitude micro-vibration parameters. Finally, a modified rigorous imaging model is constructed based on these parameters, and sensor calibration is performed accordingly. This invention integrates the attitude micro-vibration parameters into the joint adjustment model for unified solution, enabling accurate calculation of the row-by-row attitude disturbance quantities that reflect the real physical process. This directly constructs a modified rigorous imaging model that incorporates micro-vibration information, thus avoiding image information loss introduced by secondary resampling and improving the geometric accuracy of the final image product. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0017] Figure 1 This is a flowchart illustrating the optical satellite image data processing method provided by the present invention.
[0018] Figure 2 This is a schematic diagram of the structure of the optical satellite image data processing device provided by the present invention.
[0019] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0021] It should be noted that in the description of this invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the system or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0022] The terms "first," "second," etc., used in this invention are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.
[0023] This invention provides a method for processing optical satellite image data. Figure 1 This is a flowchart illustrating the optical satellite image data processing method provided by the present invention, as shown below. Figure 1 As shown, the method includes the following steps 110, 120, 130 and 140.
[0024] Step 110: Acquire optical satellite imagery data containing at least a main band and a secondary band, and extract the connection points between the main band and the secondary band.
[0025] In this embodiment, optical satellite image data refers to raw data acquired by an optical imaging satellite, such as L0 level data. This type of data records the most original sensor counts and auxiliary telemetry information without any geometric correction processing, thus preserving the most authentic information on the effects of micro-vibrations. This optical satellite image data needs to include images acquired by at least two or more parallel or nearly parallel sensor spectral bands arranged at a certain physical distance on the satellite's focal plane.
[0026] Specifically, typically, the spectral band with the highest signal-to-noise ratio and spatial resolution can be selected as the main band, while one or more other spectral bands are designated as secondary bands. Since these CCD sensors for different spectral bands are arranged on the focal plane along or perpendicular to the satellite's flight direction, when the satellite images the same ground feature, there will be a tiny time difference, ranging from microseconds to milliseconds, between the imaging times of different spectral bands. This allows the images from different spectral bands to record different micro-vibration attitudes of the satellite at that moment, thus providing an observational basis for subsequent calculations of these micro-vibrations.
[0027] In this embodiment, a subpixel-level matching algorithm is used, such as window matching based on normalized cross-correlation or a deep learning dense matching algorithm, to establish a pixel-by-pixel correspondence between the main band and each secondary band to obtain the initial matching result. Then, the initial matching result is initially screened, such as removing points with matching confidence below a threshold, and finally retaining the matching points observed in at least 3 images as connection points.
[0028] Step 120: Using the attitude micro-vibration parameters corresponding to the main CCD scan line in the main band of the optical satellite image data as variables, and aiming to minimize the observation equation of the tie point and the observation equation of the virtual ground control point, a joint adjustment model is constructed; the attitude micro-vibration parameters include the attitude disturbance angle along the track direction and the attitude disturbance angle perpendicular to the track direction corresponding to each CCD scan line.
[0029] It should be understood that attitude micro-vibration parameters are the key unknowns to be solved. In this embodiment, attitude micro-vibration parameters are defined as discrete-time series parameters corresponding to each CCD scan line. Specifically, the attitude perturbation angle along the orbit refers to the perturbation caused by a small change in the satellite's pitch angle, and the attitude perturbation angle perpendicular to the orbit refers to the perturbation caused by a small change in the satellite's roll angle. By binding the micro-vibration parameters to each CCD scan line, a refined modeling of the micro-vibration physical process can be achieved.
[0030] In this embodiment, the joint adjustment model is a large-scale nonlinear least-squares optimization model that summarizes all unknowns and all observations. In this embodiment, the joint adjustment model is subject to the common constraints of two types of observation equations: the tie-point observation equation and the virtual ground control point observation equation.
[0031] In one example, the connection point observation equation is constructed as follows: Convert the latitude and longitude coordinates corresponding to the connection points into spatial rectangular coordinates; Obtain the camera station coordinates corresponding to the imaging time of the CCD scan line, and subtract them from the spatial rectangular coordinates to determine the line-of-sight vector from the camera station to the connection point; The line-of-sight vector is subjected to a first rotation transformation using a rotation matrix from the spatial rectangular coordinates to the camera coordinate system; Based on the attitude micro-vibration parameters to be solved, an angle-compensated rotation matrix is constructed, and a second rotation transformation is performed on the line-of-sight vector after the first rotation transformation. Based on the line-of-sight vector after the second rotation transformation, the theoretical row and column direction pointing angles of the connection point are obtained; Based on the established functional relationship between the theoretical row and column direction pointing angles and the actual observed row and column direction pointing angles of the connection points, the observation equations for the connection points are constructed.
[0032] Specifically, the connection point observation equation It can be represented as follows: ; in, , as well as In For adjustment unknowns, This is the elevation value corresponding to that point. The camera station coordinates provided by GPS , This refers to the row and column direction pointing angles obtained by querying or calculating based on the join points. , These are the residuals in their corresponding directions. Convert latitude, longitude, and altitude coordinates into spatial rectangular coordinates. This is the rotation matrix for converting from Cartesian coordinates in WGS84 to coordinates in the camera coordinate system. This is a rotation matrix constructed using the angle compensation values obtained at the corresponding time point of this coordinate. Output a 2-row, 1-column vector, where the first row is the result of dividing the first row of the original input vector by the third row, and the second row is the result of dividing the second row of the original input vector by the third row. and These are the weights for the corresponding directions.
[0033] In this embodiment, the above construction process ensures that the connection point observation equation can accurately and completely describe the satellite imaging physical process including the influence of micro-vibrations.
[0034] In one example, the virtual ground control point observation equation is constructed as follows: By performing intersection calculations between the observation rays at the connection point and the auxiliary digital elevation model, the initial coordinates of the virtual ground control point corresponding to the connection point are obtained. Based on the functional relationship between the coordinates of the virtual ground control point to be solved and the initial value of the virtual ground control point coordinates corresponding to the connection point, the observation equation of the virtual ground control point is constructed.
[0035] Specifically, the virtual ground control point observation equation It can be represented as follows: ; in, , For the adjustment unknowns in the corresponding directions, , These are the residuals in their corresponding directions. , This is for initialization or results obtained from iterative calculations using the parameters in this iteration.
[0036] In this embodiment, for each connection point, its observed coordinates on the image and the satellite's orbit and attitude data at that moment are known. Therefore, an observation ray can be constructed from the satellite imagery center, passing through that image point. Then, this observation ray is intersected with an auxiliary digital elevation model covering the area. The intersection point of the observation ray and the surface of the auxiliary digital elevation model is the initial coordinate value of the virtual ground control point corresponding to that connection point. In some embodiments, to improve the reliability of the initial values, the observations of a connection point on multiple images can be intersected multiple times, and the results can be averaged.
[0037] Ultimately, the goal of the joint adjustment model is to find an optimal set of attitude micro-vibration parameters that minimizes the weighted sum of squared residuals of the residuals of all connection point observation equations and the residuals of the virtual ground control point observation equations, as shown in the following formula.
[0038] ; in, For each imaging time t of the CCD scan line within the region of interest in the attitude micro-vibration parameters, the attitude perturbation angle in the direction of the vertical track is given. The attitude perturbation angle along the track direction at each imaging time t of the CCD scan line within the region of interest in the attitude micro-vibration parameters; and These are the two-dimensional weighting coefficients for the connection point observation equation and the virtual ground control point observation equation, respectively, each including weights corresponding to the track direction and the perpendicular direction. It is a pre-set fixed weight.
[0039] Step 130: Iteratively solve the joint adjustment model to obtain the attitude micro-vibration parameters; wherein, during the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is calculated based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence.
[0040] In this process, initial values are first assigned to all unknowns. For example, the attitude micro-vibration parameters corresponding to all CCD scan lines can be initialized. , The initial values of all values are set to zero, as shown in the following formula: ; Among them, set Defines all imaging times of the CCD scan lines within the region of interest. For each imaging time Discrete attitude micro-vibration parameters are assigned ( , ).
[0041] Similarly, the initial values of the ground feature coordinates at the connection points are set as the initial estimates used in the virtual ground control point observation equations. Then, in each iteration, the nonlinear observation equations are linearized near the current solution, constructing a system of linearized normal equations to solve for all unknowns. The solved solutions are then updated to the current solution, yielding a better set of unknown values. This process is repeated until the preset convergence condition is met. After sufficient iterative convergence, the attitude micro-vibration parameters corresponding to each CCD scan line can be obtained. , ).
[0042] Step 140: Correct the rigorous imaging model according to the attitude micro-vibration parameters, and perform sensor calibration on the optical satellite image data according to the corrected rigorous imaging model.
[0043] In this embodiment, attitude micro-vibration parameters are substituted into the satellite's rigorous imaging model to correct the model. Specifically, the original nominal attitude rotation matrix is corrected using an angle compensation rotation matrix that includes micro-vibration parameters, thereby obtaining a mathematical model that can accurately describe the satellite's true imaging geometry under the influence of micro-vibrations.
[0044] Subsequently, sensor calibration is performed on the optical satellite imagery data based on the corrected rigorous imaging model. Specifically, for each pixel in the original image, its precise geographical location on the ground is calculated using this corrected model through inverse or forward modeling, and then resampled into a standard grid in the target map projection coordinate system. Because the corrected rigorous imaging model already includes compensation information for micro-vibrations, images with micro-vibration distortion eliminated can be directly generated.
[0045] The optical satellite imagery data processing method of this invention acquires optical satellite imagery data containing at least a main band and a secondary band, and extracts the connection points between them. Using the attitude disturbance angles along the orbit and perpendicular to the orbit corresponding to the main CCD scan line in the main band of the satellite imagery as variables, a joint adjustment model is constructed with the objective of minimizing the residuals of the connection point observation equations and the virtual ground control point observation equations. This model is iteratively solved, and during the iterative solution process, sensitivity indices are calculated based on the residuals of the connection point observation equations in the corresponding directions obtained from the current solution, and the weights of the connection point observation equations in the corresponding directions are updated according to the sensitivity indices until convergence, yielding attitude micro-vibration parameters. Finally, a modified rigorous imaging model is constructed based on these parameters, and sensor calibration is performed accordingly. This invention integrates the attitude micro-vibration parameters into the joint adjustment model for unified solution, enabling accurate calculation of the row-by-row attitude disturbance quantities that reflect the real physical process. This directly constructs a modified rigorous imaging model that incorporates micro-vibration information, thus avoiding image information loss introduced by secondary resampling and improving the geometric accuracy of the final image product.
[0046] It should be noted that each implementation method of this application can be freely combined, rearranged, or executed individually, and does not need to rely on or depend on a fixed execution order.
[0047] In some embodiments, the iterative solution of the joint adjustment model includes: Based on the residuals of the observation equations of the connection points solved in the current iteration in the corresponding direction, determine the sensitivity index values in the corresponding direction in the current iteration. Determine whether the sensitivity index value meets the preset convergence condition; If the sensitivity index value does not meet the preset convergence condition, the weight of the connection point observation equation in the corresponding direction is adjusted according to the sensitivity index value in the next iteration. Based on the adjusted weights, continue executing the steps of determining the sensitivity index value in the corresponding direction of the next iteration based on the residual of the connection point observation equation in the corresponding direction under the next iteration, and adjusting the weights of the connection point observation equation in the corresponding direction under the next iteration based on the sensitivity index value, until the sensitivity index value in the corresponding direction meets the preset convergence condition.
[0048] In this embodiment, for the iterative solution process in each direction, in one iteration, the residual of the observation equation of the connection point in the corresponding direction is first calculated based on the unknowns obtained in the current iteration. This residual is the vector difference between the theoretical calculated position of the connection point and its actual observed position, directly reflecting the degree of fit between the current model and the real observation data.
[0049] Subsequently, based on the residuals of the connection point observation equations solved in the corresponding directions under the current iteration, the sensitivity index value for the corresponding direction under the current iteration is determined. Here, the sensitivity index (SI) is a numerical indicator used to quantitatively evaluate the effectiveness of the current adjustment solution. The value range of the sensitivity index is usually between 0 and 1. A large sensitivity index value indicates that the current solution is far from the theoretical optimal solution, the model residual is large, and micro-vibrations have not been effectively suppressed; while a small sensitivity index value indicates that the current solution is very close to the theoretical optimal solution.
[0050] In one example, before determining the sensitivity index value for the corresponding direction in the iteration round based on the residual of the connection point in the corresponding direction, the calculated residual can be compared with a predefined threshold, and connection points whose residual exceeds the predefined threshold can be iteratively removed.
[0051] Next, it is determined whether the sensitivity index meets the preset convergence conditions. If not, the weights of the tie-point observation equations in the corresponding directions are adjusted based on the sensitivity index values. It should be understood that the weights determine the influence of the tie-point observation equations in the entire joint adjustment model. For example, the weights of the tie-point observation equations in the corresponding directions can be increased or decreased based on the current sensitivity index value, according to a preset adjustment strategy. In this way, the optimization algorithm can control the geometric constraints of the tie points in real time based on its own convergence state.
[0052] This process is repeated until the sensitivity index value meets a preset convergence condition. Here, the preset convergence condition can be that the absolute value of the sensitivity index value in the corresponding direction is less than a preset minimum value, or that the relative rate of change of the sensitivity index value in the corresponding direction between two consecutive iterations is less than a preset tolerance. When either condition is met, the iteration is considered to have converged, and the optimization process terminates.
[0053] The optical satellite image data processing method of this invention introduces a sensitivity index value and dynamically adjusts the weight of the connection point according to the sensitivity index value of the corresponding direction to achieve an adaptive robust optimization strategy, which can effectively suppress noise interference and completely preserve the characteristics of high-frequency micro-vibration signals.
[0054] In some embodiments, determining the sensitivity index value in the corresponding direction based on the residual of the junction observation equation solved in the corresponding direction in the current iteration includes: Based on the residuals of the connection point observation equations solved in the corresponding directions under the current iteration, determine the normalized standard deviation of the connection point observation equations in the corresponding directions under the current iteration. The theoretical minimum standard deviation is obtained based on the standard deviation of each sub-unit within the preset imaging time window before optimization. Determine the maximum standard deviation of the residuals within the preset imaging time window before optimization; Based on the normalized standard deviation, the theoretical minimum standard deviation, and the maximum standard deviation, determine the sensitivity index value in the corresponding direction for the current iteration round.
[0055] First, based on the residuals obtained in the corresponding direction under each iteration, determine the normalized standard deviation of all residuals in the corresponding direction under each iteration, denoted as . . It is a statistical measure of the dispersion of the residuals of all effective connection points after the current iteration round, reflecting the overall goodness of fit of the current model.
[0056] Next, based on the standard deviation of each sub-unit within the preset imaging time window before optimization, the theoretical minimum standard deviation is obtained, denoted as . . This represents the best-fit level the model can achieve before iterative optimization begins. In one specific acquisition method, the entire imaging time window, such as thousands of scan lines, can be divided into several non-overlapping, extremely small sub-units, for example, every 20 scan lines per sub-unit. Since the time span of each sub-unit is extremely short, it can be assumed that the influence of micro-vibrations within it is negligible. Under this assumption, the standard deviation of its residuals is calculated, and finally, the standard deviations of all sub-units are averaged to obtain the final value. .
[0057] Furthermore, the maximum standard deviation of the residuals within the preset imaging time window before optimization is obtained, denoted as... . It is the standard deviation of the residuals of all connection points within the entire time window, calculated before the iterative optimization begins.
[0058] Finally, based on the normalized standard deviation Theoretical minimum standard deviation and maximum standard deviation Determine the sensitivity index value for the corresponding direction under each iteration round. .
[0059] The optical satellite image data processing method of this invention achieves accurate quantitative evaluation of the adjustment results by normalizing the normalized standard deviation of the current residual between the theoretical minimum standard deviation and the maximum standard deviation, and then dynamically adjusts the weight of the tie points based on the sensitivity index value obtained from the quantitative evaluation.
[0060] In some embodiments, adjusting the weights of the connection point observation equation in the corresponding direction in the next iteration based on the sensitivity index value includes: The weight adjustment step size is determined based on the difference between the sensitivity index value of the corresponding direction in the current iteration and the sensitivity index value of the corresponding direction in the previous iteration. Adjust the step size and the weight of the connection point observation equation in the corresponding direction according to the weights, and adjust the weight of the connection point observation equation in the corresponding direction in the next iteration.
[0061] In this embodiment, after calculating the sensitivity index value for the corresponding direction in the current iteration, the sensitivity index value for the corresponding direction in the previous iteration is extracted. Then, the difference between the two sensitivity index values is calculated. If the difference indicates a significant improvement in the current iteration (e.g., the difference is greater than a preset first difference threshold), the original weight adjustment step size for the corresponding direction is retained. This weight adjustment step size is then increased based on the weight of the connection point observation equation in the corresponding direction under the current iteration, and used as the weight of the connection point observation equation in the corresponding direction under the next iteration. If the difference indicates no significant improvement in the current iteration, but the iteration termination condition is not met (e.g., the difference is less than a preset second difference threshold), the original weight adjustment step size is adjusted. For example, the original weight adjustment step size is multiplied by a preset reduction coefficient to obtain the adjusted weight adjustment step size. This adjusted weight adjustment step size is then increased based on the weight of the connection point observation equation in the corresponding direction under the current iteration, and used as the weight of the connection point observation equation in the corresponding direction under the next iteration.
[0062] The optical satellite imagery data processing method of this invention ensures that the iterative updates of the joint adjustment model continuously converge toward the optimal weights through a dynamic weight adjustment mechanism.
[0063] The optical satellite image data processing apparatus provided by the present invention is described below. The optical satellite image data processing apparatus described below corresponds to and is similar to the optical satellite image data processing method described above. The optical satellite image data processing apparatus of the present invention, as shown in the embodiments, is... Figure 2 As shown, it includes the following modules: The acquisition module 210 is used to acquire optical satellite image data containing at least a main band and a secondary band, and to extract the connection points between the main band and the secondary band. The model building module 220 is used to construct a joint adjustment model with the attitude micro-vibration parameters corresponding to the main CCD scan line in the main band of the optical satellite image data as variables, and with the goal of minimizing the residuals of the connection point observation equation and the virtual ground control point observation equation; the attitude micro-vibration parameters include the attitude perturbation angle along the track direction and the attitude perturbation angle perpendicular to the track direction corresponding to each CCD scan line; The iterative solution module 230 is used to iteratively solve the joint adjustment model to obtain the attitude micro-vibration parameters; wherein, during the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is obtained based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence. The correction module 240 is used to correct the rigorous imaging model according to the attitude micro-vibration parameters, and to perform sensor correction on the optical satellite image data according to the corrected rigorous imaging model.
[0064] The optical satellite imagery data processing apparatus of this embodiment acquires optical satellite imagery data containing at least a main band and a secondary band, and extracts the connection points between them. Using the attitude disturbance angles along the orbit and perpendicular to the orbit corresponding to the main CCD scan line in the main band of the satellite imagery as variables, a joint adjustment model is constructed with the objective of minimizing the residuals of the connection point observation equation and the virtual ground control point observation equation. This model is iteratively solved, and during the iterative solution process, sensitivity indices are calculated based on the residuals of the connection point observation equation in the corresponding direction obtained from the current solution, and the weights of the connection point observation equation in the corresponding direction are updated according to the sensitivity indices until convergence, yielding attitude micro-vibration parameters. Finally, a modified rigorous imaging model is constructed based on these parameters, and sensor calibration is performed accordingly. This invention integrates attitude micro-vibration parameters into a joint adjustment model for unified solution, which can accurately calculate the attitude perturbation quantity that reflects the real physical process and changes line by line. This directly constructs a corrected rigorous imaging model that incorporates micro-vibration information, thus avoiding the loss of image information introduced by secondary resampling and improving the geometric accuracy of the final image product.
[0065] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute an optical satellite image data processing method, which includes: Acquire optical satellite imagery data containing at least a main band and a secondary band, and extract the connection points between the main band and the secondary band; Using the attitude micro-vibration parameters corresponding to the main CCD scan line in the main band of the optical satellite image data as variables, and aiming to minimize the residuals of the connection point observation equation and the virtual ground control point observation equation, a joint adjustment model is constructed; the attitude micro-vibration parameters include the attitude disturbance angle along the track direction and the attitude disturbance angle perpendicular to the track direction corresponding to each CCD scan line. The joint adjustment model is iteratively solved to obtain the attitude micro-vibration parameters; wherein, during the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is calculated based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence. The rigorous imaging model is corrected based on the attitude micro-vibration parameters, and sensor calibration is performed on the optical satellite image data based on the corrected rigorous imaging model.
[0066] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., any medium capable of storing program code.
[0067] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is capable of executing the optical satellite image data processing method provided by each of the above methods, the method comprising: Acquire optical satellite imagery data containing at least a main band and a secondary band, and extract the connection points between the main band and the secondary band; Using the attitude micro-vibration parameters corresponding to the main CCD scan line in the main band of the optical satellite image data as variables, and aiming to minimize the residuals of the connection point observation equation and the virtual ground control point observation equation, a joint adjustment model is constructed; the attitude micro-vibration parameters include the attitude disturbance angle along the track direction and the attitude disturbance angle perpendicular to the track direction corresponding to each CCD scan line. The joint adjustment model is iteratively solved to obtain the attitude micro-vibration parameters; wherein, during the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is calculated based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence. The rigorous imaging model is corrected based on the attitude micro-vibration parameters, and sensor calibration is performed on the optical satellite image data based on the corrected rigorous imaging model.
[0068] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the optical satellite image data processing method provided by each of the above methods, the method comprising: Acquire optical satellite imagery data containing at least a main band and a secondary band, and extract the connection points between the main band and the secondary band; Using the attitude micro-vibration parameters corresponding to the main CCD scan line in the main band of the optical satellite image data as variables, and aiming to minimize the residuals of the connection point observation equation and the virtual ground control point observation equation, a joint adjustment model is constructed; the attitude micro-vibration parameters include the attitude disturbance angle along the track direction and the attitude disturbance angle perpendicular to the track direction corresponding to each CCD scan line. The joint adjustment model is iteratively solved to obtain the attitude micro-vibration parameters; wherein, during the iterative solution process, the residual sensitivity index of the connection point observation equation in the corresponding direction is calculated based on the current solution, and the weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence. The rigorous imaging model is corrected based on the attitude micro-vibration parameters, and sensor calibration is performed on the optical satellite image data based on the corrected rigorous imaging model.
[0069] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.
[0070] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.
[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in each of the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.
Claims
1. A method for processing optical satellite image data, characterized in that, The method comprises the following steps: acquiring optical satellite image data containing at least a main band and a sub-band, and extracting a connection point between the main band and the sub-band; constructing a joint adjustment model by taking attitude micro-vibration parameters corresponding to main band main CCD scan lines in the optical satellite image data as variables and taking minimizing residual errors of the connection point observation equation and residual errors of a virtual ground control point observation equation as a target, wherein the attitude micro-vibration parameters include an along-track attitude disturbance angle and a cross-track attitude disturbance angle corresponding to each CCD scan line; iteratively solving the joint adjustment model to obtain the attitude micro-vibration parameters, wherein in the iterative solving process, a sensitivity index is calculated based on residual errors of the connection point observation equation in a corresponding direction at a current iteration, and a weight of the connection point observation equation in the corresponding direction is updated according to the sensitivity index in the corresponding direction until convergence is achieved; correcting a rigorous imaging model according to the attitude micro-vibration parameters, and performing sensor correction on the optical satellite image data according to the corrected rigorous imaging model.
2. The method of claim 1, wherein, The iterative solving of the joint adjustment model comprises the following steps: determining a sensitivity index value in a corresponding direction at a current iteration according to residual errors of the connection point observation equation in the corresponding direction at the current iteration; judging whether the sensitivity index value meets a preset convergence condition; in a case where the sensitivity index value does not meet the preset convergence condition, adjusting a weight of the connection point observation equation in the corresponding direction at a next iteration according to the sensitivity index value; continuing to perform the steps of determining a sensitivity index value in a corresponding direction at a next iteration according to residual errors of the connection point observation equation in the corresponding direction at the next iteration, and adjusting a weight of the connection point observation equation in the corresponding direction at the next iteration according to the sensitivity index value, until the sensitivity index value in the corresponding direction meets the preset convergence condition, according to the adjusted weight.
3. The method of claim 2, wherein, The determination of a sensitivity index value in a corresponding direction at a current iteration according to residual errors of the connection point observation equation in the corresponding direction at the current iteration comprises the following steps: determining a normalized standard deviation of the connection point observation equation in the corresponding direction at the current iteration according to the residual errors of the connection point observation equation in the corresponding direction at the current iteration; acquiring a theoretical minimum standard deviation according to standard deviations of each sub-unit within a preset imaging time window before optimization; determining a maximum standard deviation of residual errors within the preset imaging time window before optimization; determining a sensitivity index value in the corresponding direction at the current iteration according to the normalized standard deviation, the theoretical minimum standard deviation and the maximum standard deviation.
4. The method of claim 2, wherein, The adjustment of a weight of the connection point observation equation in a corresponding direction at a next iteration according to a sensitivity index value comprises the following steps: determining a weight adjustment step according to a difference between the sensitivity index value in the corresponding direction at the current iteration and a sensitivity index value in the corresponding direction at a previous iteration. Adjust the weight of the connection point observation equation in the corresponding direction in the next iteration round according to the weight adjustment step and the weight of the connection point observation equation in the corresponding direction in the current iteration round.
5. The method of claim 1, wherein, The connection point observation equation is constructed by the following method: Convert the latitude and longitude coordinates of the connection point into spatial rectangular coordinates; Obtain the station coordinates corresponding to the imaging moment of the CCD scan line, and subtract the spatial rectangular coordinates to determine the line-of-sight vector from the station to the connection point; Perform a first rotation transformation on the line-of-sight vector using the rotation matrix from the spatial rectangular coordinates to the camera coordinate system; According to the attitude micro-vibration parameters to be solved, construct an angle compensation rotation matrix, and perform a second rotation transformation on the line-of-sight vector after the first rotation transformation; According to the line-of-sight vector after the second rotation transformation, obtain the theoretical row and column direction pointing angle of the connection point; According to the function relationship between the theoretical row and column direction pointing angle and the actual observed row and column direction pointing angle of the connection point, the connection point observation equation is constructed.
6. The method of claim 1, wherein, The virtual ground control point observation equation is constructed by the following method: Obtain the initial value of the virtual ground control point coordinates corresponding to the connection point by intersecting the observed light ray of the connection point with the auxiliary digital elevation model; According to the function relationship between the to-be-solved virtual ground control point coordinates corresponding to the connection point and the initial value of the virtual ground control point coordinates, the virtual ground control point observation equation is constructed.
7. An optical satellite image data processing apparatus, characterized by comprising: It includes: An acquisition module is configured to acquire optical satellite image data including at least a main band and a secondary band, and extract connection points between the main band and the secondary band; A model construction module is configured to construct a joint adjustment model by taking attitude micro-vibration parameters corresponding to a main CCD scan line in the main band of the optical satellite image data as variables, and taking minimizing residuals of the connection point observation equation and residuals of the virtual ground control point observation equation as an objective. An iterative solution module is configured to iteratively solve the joint adjustment model to obtain the attitude micro-vibration parameters. A correction module is configured to correct a strict imaging model according to the attitude micro-vibration parameters, and perform sensor correction on the optical satellite image data according to the corrected strict imaging model.
8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor executes the computer program to implement the optical satellite image data processing method of any one of claims 1-6. 9.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the optical satellite image data processing method of any one of claims 1-6.
10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the optical satellite image data processing method of any one of claims 1-6.