A monitoring precision control method of a coastal zone shore-based digital image monitoring system

Abstract

The present application relates to a kind of coastal zone shore-based digital image monitoring system's monitoring precision control method, using monitoring precision estimation method, the spatial distribution of the spatial resolution of coastal zone shore-based digital image monitoring system is calculated;According to monitoring precision demand, the position of monitoring equipment is selected;Adjust the installation angle of monitoring equipment, so that the image collected by monitoring equipment meets the requirements;Lay out monitoring precision verification point, carry out monitoring system precision verification, if not meet the precision demand, utilize multi-parameter optimization algorithm to optimize imaging model parameter;High-precision image recognition algorithm is used to extract the pixel coordinates of monitoring index, according to the monitoring precision demand, the projection resolution of geographic correction is set, and the high-precision geographic positioning of monitoring index is realized;Lay out permanent monitoring precision control point and record actual geographic coordinates, periodically calibrate imaging model parameter, maintain the monitoring precision of monitoring system in long-term operation.The present application realizes the whole cycle monitoring precision control of covering coastal zone shore-based digital image monitoring system from design, construction to long-term operation, meets the fine monitoring evaluation and digital management and protection demand of coastal zone evolution.

Description

Technical Field

[0001] This invention relates to a method for controlling the monitoring accuracy of a coastal zone shore-based digital image monitoring system, belonging to the field of coastal zone monitoring technology. Background Technology

[0002] The coastal zone is an active area of ​​interaction between land and sea, and also a region of intensive human activity, serving as a vital spatial resource for high-quality economic and social development. Under the dual influence of natural factors such as climate change and human activities such as engineering construction, coastal zones are experiencing increasingly dramatic changes. Efficient and accurate monitoring of the dynamic changes in the coastal zone is a key focus for coastal zone protection and restoration, disaster prevention and mitigation, and integrated management.

[0003] Traditional coastal zone monitoring primarily relies on scattered, manual beach-running measurements, which suffer from limitations such as limited monitoring range, low data density, inability to conduct measurements in adverse weather conditions, insufficient temporal continuity, single monitoring targets, and high personnel safety risks. These limitations make it difficult to meet the current demands for refined monitoring and assessment of coastal zone evolution and digital management. Therefore, coastal zone shoreline digital image monitoring systems have emerged as a new approach in the field of coastal zone monitoring. This method comprehensively utilizes digital image monitoring and interpretation technologies, combined with advanced theories of coastal dynamics, sediment, and geomorphological evolution, to achieve simultaneous monitoring of multiple coastal dynamic and topographical elements. It features all-weather, long-term, continuous, real-time, large-scale, and unattended operation, making it suitable for coastal zone monitoring in various application scenarios and with diverse objectives.

[0004] For example, patent CN110213536B provides a monitoring method for a coastal zone shore-based digital image monitoring system. It discloses a specific method for achieving long-term real-time coastal topographic and dynamic observation based on the system, but does not disclose any technology or method for controlling monitoring accuracy. In reality, the monitoring accuracy of a coastal zone shore-based digital image monitoring system is affected by various factors such as optical sensor parameters, lens parameters, equipment height, monitoring distance, beach slope, and image processing algorithms, making it difficult to predict and causing difficulties in system design and construction. During the construction of a coastal zone shore-based digital image monitoring system, technicians typically use a two-step calibration method to determine imaging model parameters. This method, based on the least squares method, has a large error and is prone to getting trapped in local optima, resulting in low system monitoring accuracy. During long-term operation, environmental factors such as strong winds and equipment aging can cause changes in lens parameters and equipment angles, leading to a decrease in system monitoring accuracy. How to effectively control these influencing factors in the complex and diverse coastal environment, ensure the monitoring accuracy of the coastal zone shore-based digital image monitoring system, and achieve long-term accurate monitoring of coastal areas is a significant problem that plagues relevant technical personnel.

[0005] Therefore, it is necessary to provide a method for controlling the monitoring accuracy of a coastal zone shore-based digital image monitoring system to ensure the monitoring accuracy of long-term coastal monitoring. Summary of the Invention

[0006] This invention provides a method for controlling the monitoring accuracy of a coastal zone shore-based digital image monitoring system, enabling full-cycle monitoring accuracy control of the coastal zone shore-based digital image monitoring system from design and construction to long-term operation, and meeting the needs for refined monitoring and assessment and digital management of coastal zone evolution.

[0007] The technical solution adopted by this invention to solve its technical problem is:

[0008] A method for controlling the monitoring accuracy of a coastal zone shore-based digital image monitoring system, specifically including the following steps:

[0009] Step S1: Based on the equipment parameters designed for the coastal zone shore-based digital image monitoring system and the topographic features of the target monitoring area, establish a monitoring accuracy estimation formula and calculate the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system.

[0010] Step S2: Based on the spatial distribution results calculated in step S1, the location of the monitoring equipment is determined according to the monitoring accuracy requirements.

[0011] Step S3: Adjust the installation angle of the monitoring equipment so that the skyline in the acquired image remains horizontal, and the target monitoring area is located in the center of the image, so that the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system meets the prediction.

[0012] Step S4: Deploy accuracy verification points. Collect pixel coordinates of the accuracy verification points through the coastal zone shore-based digital image monitoring system. Based on the imaging model parameters obtained by the traditional system calibration method, convert the pixel coordinates of the accuracy verification points into projected geographic coordinates. Compare these coordinates with the actual geographic coordinates of the accuracy verification points to verify the monitoring accuracy of the coastal zone shore-based digital image monitoring system.

[0013] If the monitoring accuracy requirements are met, proceed directly to step S5;

[0014] If the monitoring accuracy requirement is not met, then the parameters are optimized until the monitoring accuracy requirement is met, and then step S5 is performed.

[0015] Step S5: Based on the coastal zone shore-based digital image monitoring system that meets the monitoring accuracy requirements determined in step S4, a high-precision image recognition algorithm is used to extract the pixel coordinates of the target monitoring indicators. The projection resolution for geographic correction is set according to the monitoring accuracy requirements to achieve high-precision geographic positioning of the target monitoring indicators. Among them, the extracted target monitoring indicators include the waterline and the coastal dynamic geomorphological features of the wave break point.

[0016] Step S6: Deploy permanent monitoring accuracy control points and record actual geographic coordinates; periodically calibrate the parameters of the imaging model to maintain the monitoring accuracy of the coastal zone shore-based digital image monitoring system during long-term operation.

[0017] Furthermore, in step S1, the established formula for estimating monitoring accuracy is as follows:

[0018]

[0019] In formula (1), Ac represents the monitoring accuracy of the coastal zone shore-based digital image monitoring system, k is the accuracy coefficient for identifying target monitoring indicators, P is the pixel size, H is the height of the monitoring equipment, f is the lens focal length, a is the downward angle of the monitoring equipment, and β is the terrain slope.

[0020] Furthermore, in step S1, the monitoring accuracy is estimated using formula (1), which is then further derived as a function with the distance between the monitoring equipment and the target monitoring beach as the independent variable. This function represents the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system, and the formula is:

[0021]

[0022] In formula (2), F(r) is the spatial resolution at a distance r from the coastal zone shore-based digital image monitoring system;

[0023] Furthermore, in step S2, the location for installing the monitoring equipment is determined by limiting the spatial resolution in formula (2), that is, setting the spatial resolution at point r to be less than or equal to the required monitoring accuracy, then the location for installing the monitoring equipment satisfies:

[0024]

[0025] In formula (3), Δ represents the required monitoring accuracy;

[0026] Furthermore, in step S4, the specific steps for verifying the monitoring accuracy of the coastal zone shore-based digital image monitoring system are as follows:

[0027] Step S41: Collect the pixel coordinates (u,v) and actual geographic coordinates (x,y,z) of N precision verification points;

[0028] Step S42: Based on the imaging model parameters, convert the pixel coordinates (u,v) of the accuracy verification point into planar projected geographic coordinates (x,v) with elevation z. t ,y t The conversion method is as follows:

[0029]

[0030] Among them, (un ,v n The pixel coordinates (u,v) of the accuracy verification point satisfy the following equation, which can be solved iteratively:

[0031]

[0032] In formulas (4)-(7), (X) c ,Y c Z c The coordinates of the monitoring equipment are shown in the diagram. T1-T8, m1-m9, and w are parameters used in the conversion process and have no special meaning. u0, v0, and f are also mentioned. x f y , θ, τ, d1, d2, d3, d4, and d5 are all imaging model parameters, which were obtained through system calibration during the construction phase of the coastal zone shore-based digital image monitoring system.

[0033] Step S43, calculate the projected geographic coordinates (x, y) obtained in step S42. t ,y t The root mean square error between the coordinates (x, y, z) and the actual geographic coordinates (x, y, z) is used to obtain the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system, and then to determine whether the monitoring accuracy requirements are met.

[0034]

[0035] In formula (8), σ g The root mean square error between the projected geographic coordinates and the actual geographic coordinates of the accuracy verification point;

[0036] Step S44: Using the imaging model parameters as variables, the pixel coordinates (u,v) and actual geographic coordinates (x,y,z) of the accuracy verification point as parameters, and formula (8) as the analytical expression, construct the objective function:

[0037]

[0038] Step S45: Using unconstrained nonlinear multivariate optimization, find the global optimal solution that minimizes the constructed objective function, i.e.:

[0039]

[0040] Furthermore, in step S43, based on different actual working conditions, the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system can also be represented by the root mean square error of the projected pixel coordinates of the accuracy verification points:

[0041]

[0042] In formula (11), (ut ,v t The coordinates of the projected pixels are obtained from step S42. Therefore, the objective function constructed in step S44 is...

[0043]

[0044] Furthermore, in step S5, the high-precision image recognition algorithm is an edge detection algorithm with sub-pixel accuracy, and the geographically corrected projection resolution should meet Δ D ≤Δ, Δ D Δ represents the projection resolution for geographic correction, and Δ represents the required monitoring accuracy.

[0045] By employing the above technical solutions, the present invention has the following beneficial effects compared to the prior art:

[0046] 1. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system provided by the present invention can predict the spatial distribution of the system's spatial resolution during the design stage of the coastal zone shore-based digital image monitoring system, and reasonably select the installation location of the monitoring system, thus providing a basis for the construction of such systems;

[0047] 2. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system provided by the present invention overcomes the problems of large error and easy trapping in local optimum solution of the two-step calibration method through accuracy verification and imaging model parameter optimization, and can significantly improve the monitoring accuracy of such systems.

[0048] 3. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system provided by the present invention can overcome the problem of accuracy loss caused by lens aging and viewing angle shift through permanent accuracy control points and periodic parameter calibration, thus ensuring the long-term monitoring accuracy of such systems. Attached Figure Description

[0049] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0050] Figure 1 This is a flowchart of the monitoring accuracy control method for the coastal zone shore-based digital image monitoring system provided by the present invention;

[0051] Figure 2 This is a schematic diagram of the monitoring accuracy estimation method for the coastal zone shore-based digital image monitoring system provided by the present invention;

[0052] Figure 3 This is a spatial distribution map of the spatial resolution of the coastal zone shore-based digital image monitoring system according to a preferred embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram illustrating the accuracy verification results of the coastal zone shore-based digital image monitoring system according to a preferred embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram illustrating the process and results of optimizing imaging model parameters according to a preferred embodiment of the present invention. Detailed Implementation

[0055] The present invention will now be described in further detail with reference to the accompanying drawings. In the description of this application, it should be understood that the terms "left side," "right side," "upper part," "lower part," etc., indicating the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. "First," "second," etc., do not indicate the importance of the components, and therefore should not be construed as a limitation of the present invention. The specific parameters and dimensions used in this embodiment are only for illustrating the technical solution and do not limit the scope of protection of the present invention.

[0056] As described in the background section, coastal zone shore-based digital image monitoring systems, as a novel approach in coastal zone monitoring, have not adequately considered the impact of various factors such as optical sensor parameters, lens parameters, equipment height, monitoring distance, beach slope, and image processing algorithms on their monitoring accuracy. This leads to problems such as difficulty in predicting, guaranteeing, and maintaining monitoring accuracy. Therefore, this application addresses these issues by providing a monitoring accuracy control method for coastal zone shore-based digital image monitoring systems. This method can achieve full-cycle monitoring accuracy control covering system design, construction, and long-term operation, ensuring the monitoring accuracy of long-term coastal monitoring.

[0057] Figure 1 As shown, the specific steps include:

[0058] Step S1: Based on the equipment parameters designed for the coastal zone shore-based digital image monitoring system and the topographic features of the target monitoring area, establish a monitoring accuracy estimation formula and calculate the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system.

[0059] The established formula for estimating monitoring accuracy is as follows:

[0060]

[0061] In formula (1), Ac represents the monitoring accuracy of the coastal zone shore-based digital image monitoring system, k is the accuracy coefficient for identifying target monitoring indicators, P is the pixel size, H is the height of the monitoring equipment, f is the lens focal length, α is the downward angle of the monitoring equipment, and β is the terrain slope.

[0062] Through geometric transformation, Ac in formula (1) is further derived into a function with the distance between the monitoring equipment and the target monitoring beach as the independent variable, which is the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system, and the formula is:

[0063]

[0064] In formula (2), F(r) is the spatial resolution at a distance r from the coastal zone shore-based digital image monitoring system.

[0065] Step S2: Based on the spatial distribution results calculated in step S1, the location of the monitoring equipment is determined according to the monitoring accuracy requirements.

[0066] The specific solution method is to determine the location of the monitoring equipment by limiting the spatial resolution in formula (2). The constraint is that the spatial resolution at point r is less than or equal to the required monitoring accuracy. Then the location of the monitoring equipment satisfies the following conditions:

[0067]

[0068] In formula (3), Δ represents the required monitoring accuracy.

[0069] Step S3: Adjust the installation angle of the monitoring equipment so that the skyline in the acquired image remains horizontal, and the target monitoring area is located in the center of the image, so that the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system meets the prediction.

[0070] Step S4: Deploy a series of marker points, i.e., accuracy verification points, in the target area of ​​the coastal zone monitoring. Collect the pixel coordinates of the accuracy verification points using the coastal zone shore-based digital image monitoring system. Based on the imaging model parameters obtained by the traditional system calibration method, convert the pixel coordinates of the accuracy verification points into projected geographic coordinates. Compare these coordinates with the actual geographic coordinates of the accuracy verification points to verify the monitoring accuracy of the coastal zone shore-based digital image monitoring system. The specific verification steps are as follows:

[0071] Step S41: Collect the pixel coordinates (u,v) and actual geographic coordinates (x,y,z) of N precision verification points;

[0072] Step S42: Based on the imaging model parameters, convert the pixel coordinates (u,v) of the accuracy verification point into planar projected geographic coordinates (x,v) with elevation z. t ,y t The conversion method is as follows:

[0073]

[0074]

[0075] Among them, (u n ,v n The pixel coordinates (u,v) of the accuracy verification point satisfy the following equation, which can be solved iteratively:

[0076]

[0077] In formulas (4)-(7), (X) c ,Y c Z c The coordinates of the monitoring equipment are shown in the diagram. T1-T8, m1-m9, and w are parameters used in the conversion process and have no special meaning. u0, v0, and f are also mentioned. x f y , θ, τ, d1, d2, d3, d4, and d5 are all parameters of the imaging model, which were obtained through system calibration during the construction phase of the coastal zone shore-based digital image monitoring system.

[0078] Step S43, calculate the projected geographic coordinates (x, y) obtained in step S42. t ,y t The root mean square error (RMSE) of the projected geographic coordinates (x, y, z) compared to the actual geographic coordinates (x, y, z) is used to determine the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system, and thus to judge whether it meets the monitoring accuracy requirements. The projected geographic coordinates are the measured values ​​of the geographic coordinates of the accuracy verification points obtained through the coastal zone shore-based digital image monitoring system. Comparing these values ​​with the true values ​​(x, y) of the accuracy verification point geographic coordinates yields the error of the monitoring system, i.e.:

[0079]

[0080] In formula (8), σ g The root mean square error between the projected geographic coordinates and the actual geographic coordinates of the accuracy verification point;

[0081] If the monitoring accuracy requirement is met, proceed directly to step S5; if the monitoring accuracy requirement is not met, use a multi-parameter optimization algorithm to optimize the imaging model parameters and continue to step S44 until the monitoring accuracy requirement is met before proceeding to step S5.

[0082] Step S44: Using the imaging model parameters as variables, and the pixel coordinates (u,v) and actual geographic coordinates (x,y,z) of the accuracy verification point as parameters, and the projected geographic coordinates (x,y,z) of the accuracy verification point... t ,y t The root mean square error σ between (x, y, z) and the actual geographic coordinates (x, y, z) g For analytical expression, construct the objective function:

[0083] f(X) = σ g (X) (9)

[0084]

[0085] Step S45: Using unconstrained nonlinear multivariate optimization, find the global optimal solution that minimizes the constructed objective function, i.e.:

[0086]

[0087] It should be noted that in step S43, depending on the actual working conditions, the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system can also be expressed using the root mean square error of the projected pixel coordinates of the accuracy verification points:

[0088]

[0089] In formula (11), (u t ,v t The coordinates of the projected pixels can also be obtained from step S42, that is, by taking u, v, and x from formulas (4) and (7). t ,y t Replace each with u t ,v t Given x, y, the objective function constructed in step S44 is:

[0090]

[0091] After the accuracy verification and imaging model parameter optimization meet the monitoring accuracy requirements of the coastal zone shore-based digital image monitoring system, steps S5-S6 are provided to maintain the monitoring accuracy of the monitoring system during long-term operation, since the system needs to operate stably for a long time.

[0092] Step S5: Based on the coastal zone shore-based digital image monitoring system that meets the monitoring accuracy requirements determined in step S4, a high-precision image recognition algorithm is used to extract the pixel coordinates of the target monitoring indicators. The projection resolution for geographic correction is set according to the monitoring accuracy requirements to achieve high-precision geographic positioning of the target monitoring indicators. Among them, the extracted target monitoring indicators include coastal dynamic geomorphological features such as the waterline and wave-breaking point.

[0093] In this step, the high-precision image recognition algorithm is an edge detection algorithm with sub-pixel accuracy. To ensure the monitoring accuracy of the coastal zone shore-based digital image monitoring system, the projection resolution for geographic correction is limited to meet Δ. D ≤Δ, Δ D The projection resolution is for geographic correction, and Δ represents the required monitoring accuracy. This limitation can prevent the projection from causing a loss of monitoring accuracy.

[0094] Step S6: Deploy permanent monitoring accuracy control points and record their actual geographic coordinates. Regularly calibrate the parameters of the imaging model to maintain the monitoring accuracy of the coastal zone shore-based digital image monitoring system during long-term operation.

[0095] Example:

[0096] To further demonstrate the superiority of the monitoring accuracy control method of the coastal zone shore-based digital image monitoring system provided in this application, a specific embodiment is provided:

[0097] A coastal zone shore-based digital image monitoring system is designed with an image acquisition device having a resolution of 3840×2160 pixels, an optical sensor size of 1 / 1.8 inches, a lens focal length of 8mm, a monitoring device height of 30m, a beach slope of 1:20, and a required monitoring accuracy of 0.10m. This embodiment utilizes, as follows: Figure 1 The steps shown enable control over the monitoring accuracy of the system.

[0098] Step S1: Based on the equipment parameters designed for the coastal zone shore-based digital image monitoring system and the topographic features of the target monitoring area, utilize, for example... Figure 2 The monitoring accuracy estimation method shown calculates the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system:

[0099]

[0100] Step S2: Based on the spatial distribution results calculated in Step S1, and according to the monitoring accuracy requirements, determine the location for installing the monitoring equipment.

[0101]

[0102] Figure 3 As shown, in this embodiment, the monitoring equipment should be installed no more than 259.19 meters away from the target beach.

[0103] During the system construction phase, steps S3 and S4 are used to evaluate and improve the actual monitoring accuracy of the monitoring system. Specifically, in step S3, the installation angle of the monitoring equipment is adjusted so that the skyline in the image acquired by the monitoring equipment remains horizontal and the target beach area is presented in the center of the image.

[0104] Step S4: Deploy accuracy verification points to verify the monitoring accuracy of the coastal zone shore-based digital image monitoring system. Optimize the imaging model parameters using a multi-parameter optimization algorithm. The specific implementation steps are as follows:

[0105] Step S41: Set up and collect the coordinates of 6 accuracy verification points, as shown in Table 1:

[0106] Table 1 shows the coordinates of the accuracy verification points in the embodiments.

[0107] Serial Number Pixel coordinates Actual geographic coordinates 1 (940.27,2040.08) (30.979,70.458,2.433) 2 (2012.48,1756.18) (50.317,83.537,1.573) 3 (2795.36,1779.04) (58.192,78.647,1.347) 4 (3080.96,2106.36) (47.105,58.822,2.404) 5 (3625.48,2106.18) (51.229,55.677,2.434) 6 (3787.30,1790.12) (67.130,70.503,1.517)

[0108] Step S42: According to the system calibration results, the imaging model parameters in this embodiment are u0 = 1920, v0 = 1080, f x =8210,f y =7590, d1=-0.02, d2=0.02, d3=0.01, d4=-0.06, d5=0.04, θ=1.483, τ=

[0109] 0.011, the projected geographic coordinates (x, y) of the accuracy verification point are calculated using formulas (4)-(7). t ,y t The result is as follows Figure 4 As shown.

[0110] Step S43: Calculate the root mean square error of the projected geographic coordinates of the accuracy verification point to represent the monitoring accuracy of the monitoring system.

[0111]

[0112] Step S44: Using the imaging model parameters as variables, the pixel coordinates and actual geographic coordinates of the accuracy verification points as parameters, and the root mean square error of the accuracy verification points as the analytical expression, construct the objective function. Preferably, in this embodiment, the root mean square error of the projected geographic coordinates of the accuracy verification points is used as the objective function:

[0113] f(X) = σ g (X)

[0114]

[0115] Step S45: Using unconstrained nonlinear multivariate optimization, find the global optimal solution that minimizes the objective function.

[0116]

[0117] Specifically, a genetic algorithm is used to find the global optimum, with the system calibration result as the initial solution. The population size is 300, and convergence is achieved after 5086 generations. The convergence process is detailed below. Figure 5 The optimal solution for the imaging model parameters in 5a is [1931.137,1622.335,8399.666,8328.628,-0.427,-1.000,-1.000,-0.064,-0.005,0.532,1.406,0.012]. Figure 5 As shown in 5b. After optimization, the root mean square error of the projected geographic coordinates of the accuracy verification point is 0.075m, as shown in Figure 5b. Figure 5 As shown in 5c, once the required monitoring accuracy is achieved, the next step can be carried out.

[0118] To maintain the monitoring accuracy of the long-term operating monitoring system, step S5 involves using an edge detection algorithm with sub-pixel accuracy to extract monitoring indicators such as coastline, wave rise, and wave break zone range, and then performing geographic correction on the projection resolution Δ. D =0.10m, to avoid loss of monitoring accuracy.

[0119] Step S6: Deploy permanent monitoring accuracy control points and record their actual geographic coordinates. Regularly calibrate the parameters of the imaging model to maintain the monitoring accuracy of the coastal zone shore-based digital image monitoring system during long-term operation.

[0120] In summary, this application addresses the problems of difficulty in predicting monitoring accuracy, low imaging model accuracy, and long-term accuracy loss in coastal zone shore-based digital image monitoring systems. It provides a method for controlling the monitoring accuracy of such systems. The method utilizes a monitoring accuracy estimation method to calculate the spatial distribution of the system's spatial resolution. Based on the required monitoring accuracy, the method selects the installation location for the monitoring equipment. The installation angle of the equipment is adjusted to ensure the skyline remains horizontal in the acquired images, and the target monitoring area is centered in the image. Monitoring accuracy verification points are established to verify the system's accuracy. If the accuracy requirements are not met, a multi-parameter optimization algorithm is used to optimize the imaging model parameters. A high-precision image recognition algorithm is employed to extract the pixel coordinates of the monitoring indicators. A geographic correction projection resolution is set according to the required monitoring accuracy to achieve high-precision geographic positioning of the monitoring indicators. Permanent monitoring accuracy control points are established and their actual geographic coordinates are recorded. The imaging model parameters are periodically calibrated to maintain the monitoring accuracy of the system during long-term operation. This invention enables full-cycle monitoring accuracy control of coastal zone shore-based digital image monitoring systems, from design and construction to long-term operation, meeting the needs for refined monitoring and assessment of coastal zone evolution and digital management.

[0121] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0122] The meaning of "and / or" as used in this application includes situations where each exists alone or both exist simultaneously.

[0123] The term "connection" as used in this application can mean a direct connection between components or an indirect connection between components through other components.

[0124] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for controlling the monitoring accuracy of a coastal zone shore-based digital image monitoring system, characterized in that: Specifically, the following steps are included: Step S1: Based on the equipment parameters designed for the coastal zone shore-based digital image monitoring system and the topographic features of the target monitoring area, establish a monitoring accuracy estimation formula, calculate the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system, and derive the monitoring accuracy of the monitoring accuracy estimation formula into a function with the distance between the monitoring equipment and the target monitoring beach as the independent variable, which serves as the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system. The established formula for estimating monitoring accuracy is as follows: (1)， In formula (1), This represents the monitoring accuracy of the coastal zone shore-based digital image monitoring system. The accuracy coefficient for identifying target monitoring indicators. For pixel size, To monitor the height of the equipment, For the lens focal length, The angle of depression of the monitoring equipment, The slope of the terrain; Step S2: Based on the spatial distribution results calculated in Step S1, and according to the monitoring accuracy requirements, determine the location for installing the monitoring equipment; the location for installing the monitoring equipment must satisfy the distance requirements of the coastal zone shore-based digital image monitoring system. Spatial resolution at that location Monitoring accuracy requirements; Step S3: Adjust the installation angle of the monitoring equipment so that the skyline in the acquired image remains horizontal, and the target monitoring area is located in the center of the image, so that the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system meets the prediction. Step S4: Deploy accuracy verification points. Collect pixel coordinates of the accuracy verification points through the coastal zone shore-based digital image monitoring system. Based on the imaging model parameters obtained by the traditional system calibration method, convert the pixel coordinates of the accuracy verification points into projected geographic coordinates. Compare these coordinates with the actual geographic coordinates of the accuracy verification points to verify the monitoring accuracy of the coastal zone shore-based digital image monitoring system. If the monitoring accuracy requirements are met, proceed directly to step S5; If the monitoring accuracy requirement is not met, then the parameters are optimized until the monitoring accuracy requirement is met, and then step S5 is performed. Step S5: Based on the coastal zone shore-based digital image monitoring system that meets the monitoring accuracy requirements determined in step S4, a high-precision image recognition algorithm is used to extract the pixel coordinates of the target monitoring indicators. The projection resolution for geographic correction is set according to the monitoring accuracy requirements to achieve high-precision geographic positioning of the target monitoring indicators. Among them, the extracted target monitoring indicators include the waterline and the coastal dynamic geomorphological features of the wave break point. Step S6: Deploy permanent monitoring accuracy control points and record their actual geographic coordinates. Regularly calibrate the parameters of the imaging model to maintain the monitoring accuracy of the coastal zone shore-based digital image monitoring system during long-term operation.

2. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system according to claim 1, characterized in that: In step S1, the monitoring accuracy is estimated using formula (1), and further derived as a function with the distance between the monitoring equipment and the target monitoring beach as the independent variable. This is the spatial distribution of the spatial resolution of the coastal zone shore-based digital image monitoring system, and the formula is: (2)， In formula (2), The distance to the coastal zone shore-based digital image monitoring system is Spatial resolution at that location.

3. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system according to claim 2, characterized in that: In step S2, the location for installing the monitoring equipment is determined by limiting the spatial resolution in formula (2), that is, setting... Spatial resolution at that location To meet the monitoring accuracy requirements, the location of the monitoring equipment must satisfy the following: (3)， In formula (3), To meet the requirements of monitoring accuracy.

4. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system according to claim 1, characterized in that: In step S4, the specific steps for verifying the monitoring accuracy of the coastal zone shore-based digital image monitoring system are as follows: Step S41, collect Pixel coordinates of each precision verification point ( u , v ) and actual geographic coordinates ( x , y , z ); Step S42, based on the imaging model parameters, determine the pixel coordinates of the accuracy verification points ( u , v Convert to elevation Planar projection geographic coordinates ( x t , y t The conversion method is as follows: ， ，（4） ，（5) ，(6) in,( u n , v n ) and pixel coordinates of accuracy verification points ( u , v The following equations can be solved iteratively: ， ， ，(7) Formula (4)-Formula (7), ( X c , Y c , Z c ( ) represents the geographical coordinates of the monitoring equipment. , , These are all parameters used in the conversion process and have no special meaning. , , , , , , , , , , , These are all imaging model parameters, obtained through system calibration during the construction phase of the coastal zone shore-based digital image monitoring system. Step S43, calculate the projected geographic coordinates obtained in step S42. x t , y t , z ) and actual geographic coordinates ( x , y , z The root mean square error of the image is used to obtain the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system, and then to determine whether the monitoring accuracy requirements are met. （8）， In formula (8), The root mean square error between the projected geographic coordinates and the actual geographic coordinates of the accuracy verification point; Step S44, using the imaging model parameters as variables, and the pixel coordinates of the accuracy verification point ( u , v ) and actual geographic coordinates ( x , y , z Using ) as parameters and formula (8) as the analytical expression, construct the objective function: ， ，(9) Step S45: Using unconstrained nonlinear multivariate optimization, find the global optimal solution that minimizes the constructed objective function, i.e.: ，(10)。 5. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system according to claim 4, characterized in that: In step S43, based on different actual working conditions, the actual monitoring accuracy of the coastal zone shore-based digital image monitoring system is expressed using the root mean square error of the projected pixel coordinates of the accuracy verification points: ，(11) In formula (11), ( , The coordinates of the projected pixels are obtained from step S42. Therefore, the objective function constructed in step S44 is... ， ，(12)。 6. The monitoring accuracy control method of the coastal zone shore-based digital image monitoring system according to claim 1, characterized in that: In step S5, the high-precision image recognition algorithm is an edge detection algorithm with sub-pixel accuracy, and the geographically corrected projection resolution should meet the following requirements. , For geo-corrected projection resolution. To meet the requirements of monitoring accuracy.

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