Water surface image three-dimensional coordinate calibration method and device based on laser positioning

Abstract

The invention discloses a water surface image three-dimensional coordinate calibration method and device based on laser positioning. The water surface image three-dimensional coordinate calibration method comprises the following steps: acquiring a water level height and a lens focus coordinate by utilizing surveying and mapping equipment; acquiring pixel coordinates of a plurality of laser spot center calibration points formed by the plurality of laser emitters in the video view field and close to the boundary; acquiring actual coordinates or horizontal and vertical overturning angles of a laser spot center calibration point measured at a plurality of different elevation shore bases, and determining actual geodetic projection coordinates corresponding to pixel coordinates of the laser spot center calibration point; performing two-dimensional affine transformation according to the pixel coordinate of the laser spot center calibration point and the actual geodetic projection coordinate to obtain the actual longitude and latitude projection coordinate of the pixel point in the video flow measurement image; and performing three-dimensional calibration according to the water level height, the lens focus coordinate and the actual longitude and latitude projection coordinate to obtain the actual longitude and latitude and elevation coordinate of any pixel point in the video flow measurement image at any water level, thereby realizing the millimeter-level accurate calibration of the shore-base-free water surface image.

Description

Technical Field

[0001] The present application relates to the technical field of video flow measurement, and particularly to a method and device for calibrating three-dimensional coordinates of a water surface image based on laser positioning. Background Art

[0002] Video flow measurement technology is a new non-contact water flow monitoring method. Its basic principle is to calculate the water flow velocity by analyzing the surface texture features (such as ripples, bubbles, and floating debris particles) in the video image. This method calculates the pixel displacement velocity of the water surface texture or particles through an image recognition algorithm, that is, the number of pixels passed by tracking the surface texture or particles per unit time. Therefore, to calculate the actual moving speed of the surface texture or particles, the precise coordinates of each pixel within the video range are required.

[0003] On the premise that the camera direction is fixed, there are many previous methods for calibrating video pixel coordinates, and usually the shore-based calibration method is adopted, that is, solid feature points (or positioning targets) on both banks of the river are calibrated within the video field of view. By establishing the relationship between the pixel coordinates and the actual longitude and latitude coordinates of the feature points, the conversion relationship from pixel coordinates to actual coordinates is obtained, so as to determine the actual coordinates of the pixels on the river surface.

[0004] However, with the gradual popularization and application of video flow measurement methods, it is found that the shore-based calibration method cannot be applied to the situation of a large river width. When the river width is more than 200m, video flow measurement often cannot take into account both a large field of view and the recognition of the water surface texture of the river. To ensure the interpretability of the video image, only partial cross-section monitoring can be abandoned, that is, only part of the river width can be monitored (for example, only the main river channel area is monitored). At this time, the entire video field of view will be the water surface of the river flow, without a land-based surface, and there are no solid feature points available for calibration within the field of view.

[0005] To achieve shoreless video pixel calibration, various methods such as unmanned aerial vehicle hovering, unmanned ship berthing, channel buoys, and floating tracer particles have been used as fixed-point positioning targets in the past. However, due to reasons such as water flow impact and fluctuation on the water surface, the positioning targets cannot be completely fixed, and the positioning accuracy is poor, with errors even reaching dozens to hundreds of centimeters. Summary of the Invention

[0006] Therefore, the present application provides a method and device for calibrating three-dimensional coordinates of a water surface image based on laser positioning to solve the problem of poor positioning accuracy of the existing shoreless video pixel calibration method.

[0007] To achieve the above object, the present application provides the following technical solutions:

[0008] In a first aspect, a method for calibrating three-dimensional coordinates of a water surface image based on laser positioning includes:

[0009] Step 1: Obtain the water level height and the lens focus coordinates using surveying and mapping equipment;

[0010] Step 2: Obtain the pixel coordinates of the calibration points of the centers of multiple laser spots formed by multiple laser emitters within the video field of view and near the boundary;

[0011] Step 3: Obtain the actual coordinates or the horizontal and vertical flipping angles of each calibration point of the center of the laser spot measured by the total station at multiple different elevation shore bases;

[0012] Step 4: Determine the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of laser spots according to the actual coordinates or the horizontal and vertical flipping angles of the calibration points of the centers of laser spots;

[0013] Step 5: Perform two-dimensional affine transformation according to the pixel coordinates and the actual geodetic projection coordinates of multiple calibration points of the centers of laser spots, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image;

[0014] Step 6: Perform three-dimensional calibration according to the water level height, the lens focus coordinates and the actual longitude and latitude projection coordinates to obtain the actual longitude, latitude and elevation coordinates of any pixel point in the video flow measurement image at any water level.

[0015] Preferably, in Step 1, the lens focus coordinates are determined by determining multiple feature points on the outer packaging surface of the video flow measurement lens according to the relationship between the focal length, the position of the center point of the lens and the focus, measuring the relative displacement between the feature points and the focus, and then using the total station to measure the actual coordinates of the feature points, and calculating the accurate coordinates of the lens focus according to the actual coordinates and the relative displacement of the feature points.

[0016] Preferably, Step 4 specifically includes: calculating the measurement average error of each calibration point of the center of the laser spot, and determining whether the average error is within the allowable error; if it is within the allowable error, taking the measurement coordinates of the calibration point of the center of the laser spot as the corresponding actual geodetic projection coordinates; if it is not within the allowable error, calculating the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of laser spots according to the horizontal and vertical flipping angles.

[0017] Preferably, when calculating the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of laser spots according to the horizontal and vertical flipping angles, specifically:

[0018] Select any two shore bases from multiple shore bases at different elevations; respectively determine two straight lines according to the longitude, latitude and elevation of the shore base and the horizontal and vertical flipping angles of the calibration point of the center of the laser spot to be calculated, and calculate the midpoint of the common perpendicular of the two three-dimensional space straight lines as the intersection point, and the intersection point is the actual geodetic projection coordinates of the calibration point of the center of the laser spot to be calculated.

[0019] Preferably, if two straight lines are skew lines, calculate the points that are closest and equal in distance to the two straight lines.

[0020] Preferably, step 5 is specifically as follows:

[0021] Obtain an overdetermined system of equations based on the pixel coordinates and actual geodetic projection coordinates of multiple laser spot center calibration points, and calculate the optimal solution of the overdetermined system of equations; determine the unknowns of the two-dimensional affine transformation according to the optimal solution of the overdetermined system of equations, and obtain the affine transformation formula; calculate the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image according to the affine transformation formula.

[0022] Preferably, the affine transformation formula is:

[0023]

[0024] where m and n respectively represent the row and column where the pixel is located, a, b, c, d, e, and f represent the optimal solution of the overdetermined system of equations, and x and y represent the actual longitude and latitude coordinates of the pixel point in the video flow measurement image.

[0025] Preferably, step 6 specifically includes:

[0026] Determine a straight line according to the lens focus coordinates and the actual longitude and latitude projection coordinates of the pixel points calculated in the video flow measurement image:

[0027]

[0028] where x, y, and z represent the actual longitude, latitude, and elevation coordinates of the pixel point in the video flow measurement image, z = H' represents the actual water level, H represents the obtained water level, O x , O y , O z represents the lens focus coordinates, F x , F y , and H represents the actual longitude and latitude projection coordinates of the pixel point in the video flow measurement image.

[0029] In a second aspect, a three-dimensional coordinate calibration device for a water surface image based on laser positioning, the three-dimensional coordinate calibration device for a water surface image based on laser positioning is used to implement the three-dimensional coordinate calibration method for a water surface image based on laser positioning, and includes:

[0030] A calibration data acquisition module, configured to acquire the water level height and lens focus coordinates by using surveying and mapping equipment;

[0031] A laser calibration point data acquisition module, configured to acquire the pixel coordinates of multiple laser spot center calibration points formed by multiple laser emitters within the video field of view and near the boundary;

[0032] The total station measurement data acquisition module is used to acquire the actual coordinates of the calibration points of the center of each laser spot measured by the total station on the shore base at multiple different elevations, or the horizontal flipping angle and the vertical flipping angle.

[0033] The actual geodetic projection coordinate calculation module is used to determine the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple laser spot center calibration points according to the actual coordinates of the laser spot center calibration points, or the horizontal flipping angle and the vertical flipping angle.

[0034] The two-dimensional affine transformation module is used to perform two-dimensional affine transformation according to the pixel coordinates and the actual geodetic projection coordinates of multiple laser spot center calibration points, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image.

[0035] The three-dimensional affine transformation module is used to perform three-dimensional calibration according to the water level height, the lens focus coordinates and the actual longitude and latitude projection coordinates, so as to obtain the actual longitude, latitude and elevation coordinates of any pixel point in the video flow measurement image at any water level.

[0036] Compared with the prior art, the present application has at least the following beneficial effects:

[0037] The present application provides a method and device for three-dimensional coordinate calibration of a water surface image based on laser positioning, which uses surveying and mapping equipment to acquire the water level height and the lens focus coordinates; acquires the pixel coordinates of the calibration points of the center of multiple laser spots formed by multiple laser emitters within the video field of view and near the boundary; acquires the actual coordinates of the calibration points of the center of each laser spot measured by the total station on the shore base at multiple different elevations, or the horizontal flipping angle and the vertical flipping angle; determines the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple laser spot center calibration points according to the actual coordinates of the laser spot center calibration points, or the horizontal flipping angle and the vertical flipping angle; performs two-dimensional affine transformation according to the pixel coordinates and the actual geodetic projection coordinates of multiple laser spot center calibration points, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image; performs three-dimensional calibration according to the water level height, the lens focus coordinates and the actual longitude and latitude projection coordinates, so as to obtain the actual longitude, latitude and elevation coordinates of any pixel point in the video flow measurement image at any water level. The present application uses high-power lasers to achieve laser positioning on the water surface, and combines a multi-angle total station non-ranging positioning algorithm to achieve millimeter-level precise calibration of the shoreless water surface image. Description of the Drawings

[0038] To more intuitively illustrate the prior art and the present application, exemplary drawings are given below. It should be understood that the specific shapes and structures shown in the drawings generally should not be regarded as limiting conditions when implementing the present application; for example, those skilled in the art are capable of making routine adjustments or further optimizations to the addition / deletion / attribution division, specific shapes, positional relationships, connection methods, dimensional proportional relationships, etc. of certain units (components) based on the technical concepts disclosed in the present application and the exemplary drawings.

[0039] Figure 1 Flowchart of a three-dimensional coordinate calibration method for a water surface image based on laser positioning provided in the first embodiment of the present application;

[0040] Figure 2 Schematic diagram of the measurement layout of a three-dimensional coordinate calibration method for a water surface image based on laser positioning provided in the first embodiment of the present application. Detailed implementation manners

[0041] The present application will be further described in detail below with reference to the drawings through specific embodiments.

[0042] In the description of the present application: Unless otherwise specified, "a plurality" means two or more. Terms such as "first", "second", "third", etc. in the present application are intended to distinguish the objects being referred to and do not have special meanings in terms of technical connotations (for example, they should not be understood as emphasizing the importance level or order, etc.). Expressions such as "including", "comprising", "having", etc. also mean "not limited to" (certain units, components, materials, steps, etc.).

[0043] Terms such as "upper", "lower", "left", "right", "middle", etc. cited in the present application are usually indications of the general relative positional relationship for the convenience of intuitively understanding with reference to the drawings, and are not absolute limitations on the positional relationship in the actual product.

[0044] First embodiment

[0045] Please refer to Figure 1 and Figure 2 , this embodiment provides a three-dimensional coordinate calibration method for a water surface image based on laser positioning, including:

[0046] S1: Obtain the water level height and the lens focus coordinates using surveying and mapping equipment;

[0047] Specifically, before obtaining the water level height and the lens focus coordinates using surveying and mapping equipment, it is necessary to investigate the water level conditions of the river or lake, and select a time period of a cloudy day or night with relatively stable and unchanged water level and weak natural light to start the calibration work.

[0048] During calibration, the surveying and mapping equipment needs to be installed and fixed, and the video field of view needs to be ensured to be fixed. Then, use the surveying and mapping equipment to obtain the water level height H and the lens focus coordinates C. Since the lens focus coordinates C are generally difficult to measure directly, it is necessary to first determine several feature points on the outer packaging surface of the video flow measurement lens according to the relationship between the focal length, the position of the lens center point and the focus, measure the relative displacement between the feature points and the focus. After the installation is completed, use a total station to measure the actual coordinates of the feature points, and then calculate the accurate focus coordinates. In this embodiment, the camera used in the experiment has 5 million pixels and a focal length of 50 mm.

[0049] S2: Obtain the pixel coordinates of the calibration points of the centers of multiple laser spots formed by multiple laser emitters within the video field of view and near the boundary;

[0050] Specifically, for this step, 4 (or more) high-power small-spot laser emitters need to be prepared. Turn on the laser emitters, aim at the points near the boundary of the video field of view and fix them, read and record the pixel coordinates of the calibration points of the centers of the laser spots, denoted as pixel coordinates S1 - S4. The power of the laser emitter should be above 30w, the diameter of the 30m spot is less than 8cm, the angle between the laser line and the water surface is greater than 30°, and the emission distance is less than 100m.

[0051] S3: Obtain the actual coordinates or the horizontal and vertical flipping angles of each calibration point of the center of the laser spot measured by the total station at multiple different elevation shore bases;

[0052] Specifically, about 5 - 7 layout points of total station survey stations with different elevations are selected on the shore base. The precise longitude, latitude and elevation of each survey station are determined by traversing. Measure the calibration points of the centers of the laser spots on the water surface, and record the direct measurement results (i.e., the actual coordinates) and the horizontal and vertical flipping angles. Record the shore base total station layout points as P1 - P7, the direct measurement results are a total of 28, namely C11 - C74, and the horizontal and vertical flipping angles are 28 each, namely La11 - La74, Ha11 - Ha74. The laser emitter should be turned on when aiming and focusing, and the laser emitter should be turned off during measurement.

[0053] S4: Determine the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of the laser spots according to the actual coordinates or the horizontal and vertical flipping angles of the calibration points of the centers of the laser spots;

[0054] Specifically, the actual geodetic projection coordinates corresponding to the pixel coordinates S1 - S4 of the calibration points of the centers of the laser calibration spots can be directly measured by the total station under permitted conditions (i.e., the actual coordinates measured in step S3), and can be judged according to the average error of the measurement results at 7 different survey station positions. If the error is less than the permitted error, it can be directly used. If it cannot be directly measured, it needs to be calculated and determined from the horizontal and vertical flipping angles La11 - La74, Ha11 - Ha74. The calculation process is as follows:

[0055] Suppose the precise coordinates of the total station lenses at 7 measurement stations have been measured as P1 - P7 respectively, and the horizontal and vertical flipping angles are La11 - La74 and Ha11 - Ha74 respectively. Then the actual coordinates of S1 - S4 can be calculated from any two stations. Taking the calculation of S1 as an example, select stations P1 and P2, and the horizontal and vertical flipping angles are La11, Ha11, La21, and Ha21 respectively. Then the straight line passing through point P1 with horizontal and vertical flipping angles La11 and Ha11 respectively can be expressed as:

[0056]

[0057] In formula (1), (x1, y1, z1) represents the longitude, latitude and elevation of P1, with the unit of m; t represents the straight line parameter, which is rewritten in vector parameter form:

[0058]

[0059] Similarly, the straight line passing through point P2 with horizontal and vertical flipping angles La21 and Ha21 respectively can be expressed as:

[0060]

[0061] Under ideal conditions, if there is no error, then the straight lines and must intersect at point S1. Then, by solving the intersection point of the two straight lines, the actual coordinates of S1 can be obtained. However, due to the existence of objective errors in the measurement, and are skew lines. Therefore, it is necessary to solve a point in space such that the distance from this point to the two straight lines is the closest and equal. This point is actually the midpoint of the common perpendicular of the two straight lines in three - dimensional space. The common perpendicular is perpendicular to the straight lines and Then its direction is:

[0062]

[0063] The intersection points of the common perpendicular with the two straight lines can be obtained by solving the following system of equations:

[0064]

[0065] This system of equations has three unknowns t, s, and u, and the vector equation is three - dimensional. By directly solving, the values of t, s, and u can be obtained. Then the two intersection points of the common perpendicular with the two straight lines are respectively:

[0066]

[0067] Suppose is and 's midpoint, then This is the actual coordinate of point S1 we are looking for. The distance from is the solution error. Similarly, among the 7 total station sites, taking any two sites can calculate the actual coordinates of point S1, and a total of 21 calculation results can be obtained. Compare the elevation values of each calculation result with the water surface elevation value, eliminate the items with larger errors, and take the average of the remaining items to obtain the final calculation result of the actual coordinates of point S1. During the process, the calculation error range can be judged through the error items and the sample variance of each calculation result. The actual coordinates of points S2 - S4 can be calculated in the same process.

[0068] It should be noted that when calculating the actual coordinates of each pixel point in this step, first calculate the actual geodetic projection coordinates of the center points S1 - S4 of the laser calibration spots, and then calculate the corresponding relationship between the pixel coordinates and the actual coordinates. Since the water surface has a weak ability to reflect laser, it may be necessary to adjust the parameters of the laser rangefinder or total station to enhance the signal reception ability. If it is impossible to obtain direct measurement results due to reasons such as long distance, water body fluctuation, and low reflectivity, it is necessary to calculate based on the horizontal and vertical flip angles of S1 - S4 at multiple stations.

[0069] S5: Perform a two - dimensional affine transformation based on the pixel coordinates and the actual geodetic projection coordinates of multiple laser spot center calibration points, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image.

[0070] Specifically, after obtaining the actual coordinates of S1 - S4, perform a two - dimensional affine transformation to obtain the actual longitude and latitude projection coordinates of any pixel point.

[0071] Suppose the pixel coordinates of S1 - S4 are (m1, n1), (m2, n2), (m3, n3), (m4, n4) respectively, then the corresponding actual longitude and latitude coordinates are (x1, y1), (x2, y2), (x3, y3), (x4, y4) respectively. The affine transformation to be solved is:

[0072]

[0073] where m and n respectively represent the row and column where the pixel is located. The row is from bottom to top, and the column is from left to right. The affine transformation of Equation 8 needs to solve 6 unknowns. For each known pixel point and its corresponding coordinates, 2 equations can be listed. Therefore, for the coordinate affine transformation in a two - dimensional plane, at least 3 known points are required to form a linear equation system for solution. According to the 4 known points S1 - S4 in this embodiment, the equation system can be listed as follows:

[0074]

[0075] Equation 9 is an overdetermined system of equations. By solving the optimal solution of this system of equations, the affine transformation parameters of Equation 8 can be obtained. Thus, for any pixel point, given the row and column where the pixel is located, its actual projection coordinates can be obtained.

[0076] S6: Perform three-dimensional calibration based on the water level height, the lens focal point coordinates, and the actual longitude and latitude projection coordinates to obtain the actual longitude, latitude, and elevation coordinates of any pixel point in the video flow measurement image at any water level.

[0077] In practice, the problem of fluctuations in the elevation of the measured water surface also needs to be considered. When the water surface rises or falls, the actual three-dimensional coordinates represented by each pixel point will also change accordingly. Assume that the measured water surface is approximately horizontal, and the elevation of any point on the plane is equal. Let the three-dimensional space coordinates of the lens focal point be C(O x , O y , O z ), and the current stable water surface elevation be H. Then, for any current pixel coordinates F(m, n), according to Equation 8, its actual projection coordinates F(F x , F y , H) can be obtained. Given two points C and F in three-dimensional space, a unique straight line can be determined passing through these two points:

[0078]

[0079] In the formula, t is the unique parameter. When the water level of the future measured water surface becomes H′, H′ can be substituted into Equation 10 to solve for the parameter t, that is:

[0080]

[0081] Substitute t into Equation 10, and the longitude x and latitude y of any pixel point at the water level H′ can be solved, thereby obtaining the actual longitude, latitude, and elevation coordinates of any pixel point in the video flow measurement image at any water level.

[0082] A three-dimensional coordinate calibration method for water surface images based on laser positioning provided by this embodiment uses high-power lasers to achieve laser positioning on the water surface. Compared with previous positioning methods such as UAV hovering, unmanned ship berthing, channel buoys, and floating tracer particles, it is not affected by water flow impact and fluctuations of water or air fluids. Combining with the multi-angle total station non-range measurement positioning algorithm, millimeter-level precise calibration of shoreless water surface images is achieved. It solves the problem of precise calibration of actual coordinates of shoreless video flow measurement images, and is of great significance for expanding the application of video flow measurement methods in large river wide channels and improving the interpretation accuracy of video flow measurement.

[0083] Embodiment 2

[0084] This embodiment provides a three-dimensional coordinate calibration device for water surface images based on laser positioning. The three-dimensional coordinate calibration device for water surface images based on laser positioning is used to implement the three-dimensional coordinate calibration method for water surface images based on laser positioning in Embodiment 1, and includes:

[0085] A calibration data acquisition module, configured to acquire the water level height and the lens focus coordinates by using surveying and mapping equipment;

[0086] A laser calibration point data acquisition module, configured to acquire the pixel coordinates of the center calibration points of multiple laser spots formed by multiple laser emitters within the video field of view and near the boundary;

[0087] A total station measurement data acquisition module, configured to acquire the actual coordinates or the horizontal flip angle and the vertical flip angle of the center calibration point of each laser spot measured by the total station at multiple different elevation shore bases;

[0088] An actual geodetic projection coordinate calculation module, configured to determine the actual geodetic projection coordinates corresponding to the pixel coordinates of the center calibration points of multiple laser spots according to the actual coordinates or the horizontal flip angle and the vertical flip angle of the center calibration points of the laser spots;

[0089] A two-dimensional affine transformation module, configured to perform a two-dimensional affine transformation according to the pixel coordinates and the actual geodetic projection coordinates of the center calibration points of multiple laser spots, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image;

[0090] A three-dimensional affine transformation module, configured to perform three-dimensional calibration according to the water level height, the lens focus coordinates and the actual longitude and latitude projection coordinates, so as to obtain the actual longitude, latitude and elevation coordinates of any pixel point in the video flow measurement image at any water level.

[0091] For the specific implementation content of each module in a three-dimensional coordinate calibration device for water surface images based on laser positioning, reference may be made to the limitations on the three-dimensional coordinate calibration method for water surface images based on laser positioning in the above text, which will not be elaborated here.

[0092] The technical features of the above embodiments can be combined arbitrarily (as long as there is no contradiction in the combination of these technical features). For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described; these embodiments not explicitly written out should also be regarded as within the scope described in this specification.

Claims

1. A three-dimensional coordinate calibration method for water surface images based on laser positioning, characterized in that, Including: Step 1: Obtain the water level height and the lens focus coordinates using surveying and mapping equipment; Step 2: Obtain the pixel coordinates of the calibration points of the centers of multiple laser spots formed by multiple laser emitters within the video field of view and near the boundary; Step 3: Obtain the actual coordinates or the horizontal and vertical flipping angles of each calibration point of the center of the laser spot measured by the total station at multiple different elevation shore bases; Step 4: Determine the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of laser spots according to the actual coordinates or the horizontal and vertical flipping angles of the calibration points of the centers of laser spots; Step 5: Perform two-dimensional affine transformation based on the pixel coordinates and the actual geodetic projection coordinates of multiple calibration points of the centers of laser spots, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image; Step 6: Perform three-dimensional calibration according to the water level height, the lens focus coordinates and the actual longitude and latitude projection coordinates, and obtain the actual longitude, latitude and elevation coordinates of any pixel point in the video flow measurement image at any water level.

2. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 1, wherein In Step 1, the lens focus coordinates are determined by determining multiple feature points on the outer packaging surface of the video flow measurement lens according to the relationship between the focal length, the position of the center point of the lens and the focus, measuring the relative displacement between the feature points and the focus, and then using the total station to measure the actual coordinates of the feature points, and calculating the accurate coordinates of the lens focus according to the actual coordinates and the relative displacement of the feature points.

3. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 1, characterized in that Step 4 specifically includes: calculating the measurement average error of each calibration point of the center of the laser spot, and determining whether the average error is within the allowable error; if it is within the allowable error, taking the measurement coordinates of the calibration point of the center of the laser spot as the corresponding actual geodetic projection coordinates; if it is not within the allowable error, calculating the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of laser spots according to the horizontal and vertical flipping angles.

4. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 3, wherein When calculating the actual geodetic projection coordinates corresponding to the pixel coordinates of multiple calibration points of the centers of laser spots according to the horizontal and vertical flipping angles, specifically: Select any two shore bases from multiple shore bases at different elevations; determine two straight lines respectively according to the longitude, latitude and elevation of the shore base and the horizontal and vertical flipping angles of the calibration point of the center of the laser spot to be calculated, and calculate the midpoint of the common perpendicular of the two three-dimensional space straight lines as the intersection point, and the intersection point is the actual geodetic projection coordinates of the calibration point of the center of the laser spot to be calculated.

5. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 4, wherein If the two straight lines are skew lines, calculate the points that are equidistant and closest to the two straight lines.

6. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 1, characterized in that, Step 5 is specifically: Obtain an overdetermined system of equations according to the pixel coordinates and the actual geodetic projection coordinates of multiple calibration points of the centers of laser spots, and calculate the optimal solution of the overdetermined system of equations; determine the unknowns of the two-dimensional affine transformation according to the optimal solution of the overdetermined system of equations, and obtain the affine transformation formula; calculate the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image according to the affine transformation formula.

7. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 6, characterized in that, The affine transformation formula is: where m and n respectively represent the row and column where the pixel is located, a, b, c, d, e and f represent the optimal solution of the overdetermined system of equations, and x and y represent the actual longitude and latitude coordinates of the pixel point in the video flow measurement image.

8. The three-dimensional coordinate calibration method for water surface images based on laser positioning according to claim 1, wherein Step 6 specifically includes: Determine a straight line based on the lens focus coordinates and the actual longitude and latitude projection coordinates of the pixel points in the calculated video flow measurement image: Among them, x, y, and z represent the actual longitude, latitude, and elevation coordinates of pixel points in the video flow measurement image, z = H′ represents the actual water level, H represents the obtained water level, O x , O y , O z represents the lens focus coordinate, F x , F y , and H represents the actual longitude and latitude projection coordinates of pixel points in the video flow measurement image.

9. A three-dimensional coordinate calibration device for water surface images based on laser positioning, characterized in that, The water surface image three-dimensional coordinate calibration device based on laser positioning is used to implement the water surface image three-dimensional coordinate calibration method according to any one of claims 1-8, and includes: A calibration data acquisition module, configured to acquire the water level height and lens focus coordinates by using surveying and mapping equipment; A laser calibration point data acquisition module, configured to acquire the pixel coordinates of the center calibration points of multiple laser spots formed by multiple laser emitters within the video field of view and near the boundary; A total station measurement data acquisition module, configured to acquire the actual coordinates or horizontal and vertical flipping angles of the center calibration points of each laser spot measured by the total station on the shore base at multiple different elevations; An actual geodetic projection coordinate calculation module, configured to determine the actual geodetic projection coordinates corresponding to the pixel coordinates of the center calibration points of multiple laser spots according to the actual coordinates or horizontal and vertical flipping angles of the center calibration points of the laser spots; A two-dimensional affine transformation module, configured to perform two-dimensional affine transformation according to the pixel coordinates and actual geodetic projection coordinates of the center calibration points of multiple laser spots, so as to obtain the actual longitude and latitude projection coordinates of any pixel point in the video flow measurement image; A three-dimensional affine transformation module, configured to perform three-dimensional calibration according to the water level height, lens focus coordinates and actual longitude and latitude projection coordinates, so as to obtain the actual longitude, latitude and elevation coordinates of any pixel point in the video flow measurement image at any water level.

Images