Remote sensing surveying and mapping data enhancement method and system for real estate surveying and mapping

Abstract

The invention relates to the technical field of image enhancement, in particular to a remote sensing surveying and mapping data enhancement method and system for real estate surveying and mapping, and the method comprises the steps: obtaining all target surveying and mapping images corresponding to an area to be surveyed and mapped; setting a virtual control point for each target surveying and mapping image, and determining correction coordinates corresponding to pixel points in each target surveying and mapping image; screening overlapped pixel points representing the same geographic position from all the target surveying and mapping images, and positioning missing pixel points with missing geographic positions; the RGB values corresponding to the overlapped pixel points and the missing pixel points are corrected and supplemented; and constructing an enhanced overall surveying and mapping image according to the adjusted RGB values corresponding to the overlapped pixel points and the missing pixel points and the unadjusted RGB values corresponding to the other pixel points. According to the invention, enhancement of the unmanned aerial vehicle remote sensing surveying and mapping data is realized, and the enhancement effect of the unmanned aerial vehicle remote sensing surveying and mapping data is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image enhancement, and specifically relates to a method and system for enhancing remote sensing mapping data for real estate surveying and mapping. Background Art

[0002] Compared with the total station measurement technology, the new UAV mapping technology has the characteristics of high flexibility, high efficiency, low cost, etc., so it is widely used in the process of real estate surveying and mapping. However, due to reasons such as lens distortion, UAV skew, and weather, the collected image data often has various forms of geometric distortion. In order to ensure the application of surveying and mapping data and the complete restoration of the regional model, it is often necessary to correct the image data to achieve the enhancement of the image data.

[0003] Currently, the geometric rectification theory is mainly used to correct image distortion. Specifically, first, ground control points are selected in the surveying and mapping area; the distortion parameters are determined according to the transformation of the corresponding control points in the image, and then the corrected positions of all pixel points in the image are determined in combination with the transformation of the control points, that is, the geometric correction model; then, the pixel points with position changes and the pixel points with vacant positions are interpolated and supplemented through pixel resampling to complete the geometric correction. However, for remote sensing images, the amount of information contained in pixel points is huge, and information loss may often occur whether the nearest neighbor interpolation method or the bilinear interpolation method is used in the pixel resampling step. Due to the flexibility of UAVs, there are various types of distortions in remote sensing images, and the distortion degrees are different, which often leads to the inability to unify the geometric correction model, and there are often a large number of images in the surveying and mapping process, thus often resulting in poor enhancement effects of UAV remote sensing surveying and mapping data. Summary of the Invention

[0004] In order to solve the technical problem of poor enhancement effect of UAV remote sensing surveying and mapping data, the present invention proposes a method and system for enhancing remote sensing surveying and mapping data for real estate surveying and mapping.

[0005] In the first aspect, the present invention provides a method for enhancing remote sensing surveying and mapping data for real estate surveying and mapping, and the method includes: Obtain all target surveying and mapping images corresponding to the area to be surveyed, wherein the union of all target surveying and mapping images covers the area to be surveyed, and different target control points are set in the area to be surveyed; Based on the target control points, set virtual control points for each target surveying and mapping image, and determine the corrected coordinates corresponding to the pixel points between the virtual control points and the corresponding control points in each target surveying and mapping image based on the surveying coordinates and corrected coordinates corresponding to the target control points, and the surveying coordinates corresponding to the virtual control points; For the pixel points other than the control points and the pixel points between their connections in the target surveying and mapping image, determine the corrected coordinates corresponding to the pixel points based on the smallest quadrilateral to which the pixel point belongs; According to the calibration coordinates corresponding to all pixel points in all target surveying and mapping images, select the overlapping pixel points representing the same geographical location from all target surveying and mapping images, and locate the missing pixel points with missing geographical locations; Correct and supplement the RGB values corresponding to the overlapping pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points; Construct an enhanced overall surveying and mapping image according to the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points, and the RGB values before adjustment corresponding to other pixel points.

[0006] Combined with the first aspect above, in a possible implementation manner, the method for setting target control points includes: Perform quadrilateral connection processing starting from each initial control point in the to-be-surveyed area to obtain a sub-network corresponding to each initial control point; Form the union of the sub-networks corresponding to all initial control points to form an initial four-corner network, and determine each initial control point within the initial four-corner network as a reference control point; Determine each initial control point in the to-be-surveyed area except for all reference control points as a temporary control point; Perform control point supplementation based on the reference control points and each temporary control point; If the included angle between two adjacent sides in the initial four-corner network is greater than a preset angle, use these two adjacent sides as the sides of a parallelogram, construct a parallelogram, and supplement the newly formed endpoints as new control points; Determine the average value of the areas of all quadrilaterals in the initial four-corner network as the area representative factor; Select the quadrilaterals corresponding to areas greater than the area representative factor from the initial four-corner network as the quadrilaterals to be supplemented with control points; Set a reduced version of the quadrilateral to be supplemented with control points within each quadrilateral to be supplemented with control points, and supplement each endpoint of the reduced version of the quadrilateral to be supplemented with control points as a new control point; Record each initial control point and each newly supplemented control point as target control points.

[0007] Combined with the first aspect above, in a possible implementation manner, the performing quadrilateral connection processing starting from each initial control point in the to-be-surveyed area to obtain a sub-network corresponding to each initial control point includes: Determine any one of the initial control points as the marked control point, and select the three non-collinear initial control points closest to the marked control point from the area to be surveyed and mapped as the standard control points. Based on these three standard control points and the marked control point, construct a quadrilateral, denoted as the marked quadrilateral; Determine each side of the marked quadrilateral as a marked line segment, and form the set of initial control points between two adjacent marked line segments with the two non-intersection endpoints among the three initial control points on the two adjacent marked line segments; If the included angle between two adjacent marked line segments is less than the preset angle, then determine the set of initial control points between the two adjacent marked line segments as the marked set of initial control points. Select the initial control point closest to the marked set of initial control points from all the initial control points in the area to be surveyed and mapped except the four endpoints of the marked quadrilateral as the reference control point, and connect the reference control point with each initial control point in the marked set of initial control points to obtain the quadrilateral between the two adjacent marked line segments; Among them, the method for obtaining the initial control point closest to the marked set of initial control points is as follows: Determine each initial control point in the area to be surveyed and mapped except the four endpoints of the marked quadrilateral as a candidate control point, determine the distance between each candidate control point and each initial control point in the marked set of initial control points as the reference distance, obtain the set of reference distances corresponding to each candidate control point, and determine the sum of all the reference distances in the set of reference distances corresponding to each candidate control point as the overall distance corresponding to each candidate control point. Denote the candidate control point with the smallest corresponding overall distance as the initial control point closest to the marked set of initial control points; Form the union of the marked quadrilateral and the quadrilaterals between all adjacent marked line segments to constitute the sub-network corresponding to the marked control point.

[0008] Combined with the first aspect above, in a possible implementation, the supplementing of control points based on the reference control points and each temporary control point includes: Determine any one of the temporary control points as the to-be-determined control point; Select the reference control point closest to the to-be-determined control point from all the reference control points as the reference control point corresponding to the to-be-determined control point; Connect the to-be-determined control point with its corresponding reference control point to obtain the reference line segment; Arbitrarily select two reference control points from all the reference control points adjacent to the reference control point corresponding to the to-be-determined control point as the template control points, and starting from each template control point, draw line segments with the same direction and length as the direction and length of the reference line segment, denoted as the target line segments, to obtain two target line segments; Supplement the endpoints of the two target line segments other than the reference control points as new control points.

[0009] Combined with the above first aspect, in a possible implementation manner, setting virtual control points for each target mapping image based on the target control points includes: Determine any one target mapping image as the marked mapping image, where the edge connection method between the target control points in the marked mapping image copies the edge connection method when the target control points are obtained; If the figure formed by all the target control points in the marked mapping image is not a closed figure, connect the target control points at the opening of the figure formed by all the target control points in the marked mapping image so that the figure formed by all the target control points in the marked mapping image is a closed figure; Determine the closed figure formed by all the target control points in the marked mapping image as the marked closed figure; Perform scaling or enlargement processing on the marked closed figure to generate a new figure, and determine each endpoint of all the new figures generated at this time as a virtual control point.

[0010] Combined with the above first aspect, in a possible implementation manner, determining the correction coordinates corresponding to the pixels between the virtual control points and the corresponding control point connection lines in each target mapping image based on the mapping coordinates and correction coordinates corresponding to the target control points, and the mapping coordinates corresponding to the virtual control points includes: Screen out the smallest figure from the marked closed figure and all the new figures as the reference figure, and determine any one control point in the reference figure as the target origin, where the control point is a target control point or a virtual control point; Connect the target origin to all its corresponding control points to obtain the first target straight line; Determine the straight line passing through the target origin and perpendicular to the first target straight line as the second target straight line; Construct a marked coordinate system with the target origin as the origin, the first target straight line as the vertical axis, and the second target straight line as the horizontal axis; Determine the correction coordinates corresponding to each virtual control point according to the mapping coordinates and correction coordinates corresponding to the target control points corresponding to each virtual control point, and the mapping coordinates corresponding to each virtual control point, where the virtual control point and its corresponding target control point are corresponding points obtained by scaling or enlarging the figure, and the mapping coordinates are the coordinates in the marked coordinate system; Connect the corresponding control points to obtain candidate line segments. Based on the surveying coordinates and calibration coordinates of the target control points on each candidate line segment, determine the calibration coordinates of each non-control point on each candidate line segment. Among them, the non-control points on the candidate line segments are the pixel points between the connections of the corresponding control points. The formula for the calibration coordinates corresponding to the non-control points on the candidate line segments is as follows: ; ; where and are the abscissa and ordinate of the calibration coordinates corresponding to the j-th non-control point on the s-th candidate line segment respectively; s is the serial number of the candidate line segment; j is the serial number of the non-control point on the s-th candidate line segment; is the correction factor corresponding to the j-th non-control point on the s-th candidate line segment; is cosine value; is sine value; is the angle between the surveying line segment and the calibration line segment corresponding to the target control point on the s-th candidate line segment; the surveying line segment corresponding to the target control point is the line segment obtained by connecting the surveying coordinates corresponding to the target control point and the target origin; the calibration line segment corresponding to the target control point is the line segment obtained by connecting the calibration coordinates corresponding to the target control point and the target origin; and are the abscissa and ordinate of the surveying coordinates corresponding to the j-th non-control point on the s-th candidate line segment respectively; is the translation distance of the target control point on the s-th candidate line segment; is the distance between the j-th non-control point on the s-th candidate line segment and the target origin; is the distance between the target control point on the s-th candidate line segment and the target origin; is the GPS distance between the target control point and the target origin corresponding to each other in the actual scene on the s-th candidate line segment.

[0011] Combined with the above first aspect, in a possible implementation manner, for the pixel points in the target surveying image except for the pixel points between the control points and their connections, determining the calibration coordinates corresponding to the pixel points based on the smallest quadrilateral to which the pixel point belongs includes: Determine any pixel point in the target surveying image except for the pixel points between the control points and their connections as a marked pixel point, and determine the smallest quadrilateral to which the marked pixel point belongs as a reference quadrilateral; Determine the straight line where the connection of any group of corresponding control points in the two groups of corresponding control points in the reference quadrilateral is located as the first temporary straight line, and determine the straight line where the connection of the other group of corresponding control points is located as the second temporary straight line; Determine the straight line where the connection line of any two non - corresponding control points adjacent to each other in the reference quadrilateral is located as the third temporary straight line; Translate the third temporary straight line so that it passes through the marked pixel point to obtain the fourth temporary straight line, and determine the intersection point of the fourth temporary straight line and the first temporary straight line as the first marked intersection point; Connect the marked pixel point and the first marked intersection point to obtain the fifth temporary straight line, and determine the included angle between the first temporary straight line and the fifth temporary straight line as the first temporary included angle; Determine the included angle between the first temporary straight line and the second temporary straight line as the second temporary included angle; Determine the intersection point of the first temporary straight line and the second temporary straight line as the second marked intersection point; According to the distance between the marked pixel point and the first marked intersection point, the distance between the marked pixel point and the second marked intersection point, and the first temporary included angle and the second temporary included angle, the formula for determining the corrected coordinates corresponding to the marked pixel point is: ; ; ; where, and are respectively the abscissa and ordinate of the corrected coordinates corresponding to the marked pixel point; is the cosine value of; is the sine value of; is equal to ; and are respectively the abscissa and ordinate of the surveying and mapping coordinates corresponding to the marked pixel point; is the translation distance of the control point on the reference quadrilateral closest to the marked pixel point; is the first temporary included angle; is the second temporary included angle; is the distance between the marked pixel point and the first marked intersection point; is the distance between the marked pixel point and the second marked intersection point.

[0012] Combined with the above - mentioned first aspect, in a possible implementation manner, the correcting and supplementing the RGB values corresponding to the coincident pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the coincident pixel points and the missing pixel points includes: Determine the area composed of consecutive coincident pixel points or consecutive missing pixel points as the reference area; Determine the region formed by the preset neighborhoods corresponding to all the edge pixel points of each reference region as the overall neighborhood corresponding to each reference region; Form the surrounding representative region corresponding to each reference region with the pixel points within the overall neighborhood corresponding to each reference region except for that reference region itself; According to the surrounding representative region corresponding to each reference region, the formula for determining the information importance corresponding to each reference region is: ; ; where is the information importance corresponding to the a-th reference region; a is the serial number of the reference region; is the normalization function; is the number of types of R values corresponding to all the pixel points within the surrounding representative region corresponding to the a-th reference region; is the number of types of G values corresponding to all the pixel points within the surrounding representative region corresponding to the a-th reference region; is the number of types of B values corresponding to all the pixel points within the surrounding representative region corresponding to the a-th reference region; is the number of pixel points within the surrounding representative region corresponding to the a-th reference region; t and v are the serial numbers of different pixel points within the surrounding representative region corresponding to the a-th reference region; is the pixel difference between the t-th pixel point and the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the absolute value function; is the R value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the R value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the G value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the G value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the B value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the B value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; According to the information importance corresponding to each reference region, determine the information importance factor corresponding to each pixel point within the surrounding representative region corresponding to each reference region; Adjust the R value corresponding to the overlapping pixel points representing the same geographical location according to the information importance factors corresponding to all the pixel points within the reference regions to which the overlapping pixel points belong; Similarly, according to the information importance factors corresponding to all the pixels within the reference region to which the overlapping pixels representing the same geographical location belong, adjust the G value and B value corresponding to the overlapping pixels representing the same geographical location; The formula for adjusting the R value corresponding to each missing pixel according to the information importance factors corresponding to all the pixels within the reference region to which the missing pixel belongs is: ; ; where is the adjusted R value corresponding to the h-th missing pixel; h is the serial number of the missing pixel; is the number of pixels within the reference region to which the h-th missing pixel belongs; b is the serial number of the pixel within the reference region to which the h-th missing pixel belongs; is the R value corresponding to the b-th pixel within the reference region to which the h-th missing pixel belongs; is the information importance factor corresponding to the b-th pixel within the reference region to which the h-th missing pixel belongs; is the natural exponential function; is the distance between the h-th missing pixel and the b-th pixel within its reference region; Similarly, according to the information importance factors corresponding to all the pixels within the reference region to which each missing pixel belongs, adjust the G value and B value corresponding to each missing pixel.

[0013] Combined with the first aspect above, in a possible implementation, the formula for adjusting the R value corresponding to the overlapping pixels representing the same geographical location according to the information importance factors corresponding to all the pixels within the reference region to which the overlapping pixels representing the same geographical location belong is: ; ; where is the adjusted R value corresponding to the overlapping pixels representing the same geographical location; E is the number of overlapping pixels representing the same geographical location; f is the serial number of the overlapping pixels representing the same geographical location; T is the number of pixels within the reference region to which the overlapping pixels representing the same geographical location belong; k is the serial number of the pixels within the reference region to which the overlapping pixels representing the same geographical location belong; is the R value before adjustment corresponding to the f-th overlapping pixel representing the same geographical location; is the information importance factor corresponding to the k-th pixel within the reference region to which the f-th overlapping pixel representing the same geographical location belongs; is the natural exponential function; is the distance between the f-th overlapping pixel representing the same geographical location and the k-th pixel within its reference region; is an absolute value function; is the R value corresponding to the f-th pixel point within the reference area to which the f-th coincident pixel point representing the same geographical location belongs.

[0014] In a second aspect, the present invention provides a remote sensing mapping data enhancement system for real estate mapping. The system includes: A mapping image acquisition module for acquiring all target mapping images corresponding to the area to be mapped. Among them, the union of all target mapping images covers the area to be mapped, and different target control points are set within the area to be mapped; A setting determination module for setting virtual control points for each target mapping image based on the target control points, and determining the correction coordinates corresponding to the pixel points between the virtual control points and the corresponding control point connections in each target mapping image based on the mapping coordinates and correction coordinates corresponding to the target control points, as well as the mapping coordinates corresponding to the virtual control points; A correction coordinate determination module for determining the correction coordinates corresponding to the pixel points other than the pixel points between the control points and their connections in the target mapping image based on the smallest quadrilateral to which the pixel point belongs; A screening and positioning module for screening out the coincident pixel points representing the same geographical location from all target mapping images according to the correction coordinates corresponding to all pixel points in all target mapping images, and positioning the missing pixel points where the geographical location is missing; An RGB adjustment module for correcting and supplementing the RGB values corresponding to the coincident pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the coincident pixel points and the missing pixel points; A mapping image enhancement module for constructing an enhanced overall mapping image according to the adjusted RGB values corresponding to the coincident pixel points and the missing pixel points, and the unadjusted RGB values corresponding to other pixel points.

[0015] In a third aspect, a server is provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the method in the first aspect or any possible implementation manner of the first aspect.

[0016] In a fourth aspect, a computer program product is provided. The computer program product includes: computer program code, which when running on a computer, causes the computer to execute the method in the first aspect or any possible implementation manner of the first aspect.

[0017] Fifth aspect, there is provided a computer-readable storage medium storing computer program code which, when run on a computer, causes the computer to execute the method in the first aspect or any possible implementation manner of the first aspect above.

[0018] The present invention has the following beneficial effects: The remote sensing mapping data enhancement method for real estate mapping of the present invention realizes the enhancement of UAV remote sensing mapping data, solves the technical problem of poor enhancement effect of UAV remote sensing mapping data, and improves the enhancement effect of UAV remote sensing mapping data. Specifically, for the problem that when remote sensing mapping images are distorted and corrected through geometric precise correction theory, due to the large amount of information contained in the mapping images and the easy occurrence of information loss, and the diverse distortion situations of the mapping images, resulting in poor enhancement effect of the mapping images, different target control points are first set in the area to be mapped, and multiple features related to the distortion of the mapping images are comprehensively considered, such as the mapping coordinates and correction coordinates corresponding to the target control points, the mapping coordinates corresponding to the virtual control points, quadrilaterals, overlapping pixel points and missing pixel points, thereby realizing the enhancement of mapping data, which is beneficial to improving the quality of mapping data and is beneficial to the subsequent reconstruction and analysis of the mapping area. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0020] Figure 1 is a flowchart of the remote sensing mapping data enhancement method for real estate mapping of the present invention; Figure 2 is a schematic structural diagram of the composition of the remote sensing mapping data enhancement system for real estate mapping of the present invention; Figure 3 is a schematic structural diagram of a computer device of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following will, in conjunction with the drawings and preferred embodiments, detail the specific implementation manners, structures, features and effects of the technical solutions proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs.

[0023] The GPS coordinate distance network structure between control points is a real network structure. However, due to distortion in the mapping image, the network structure of the control points in the camera coordinate system in the image is deformed. By correcting the control points towards the real structure direction and correcting the remaining pixel points according to the correction direction of the adjacent control points, a more accurate image can be obtained.

[0024] However, in this process, due to the irregular layout of the control points, if only local correction is considered, deformation will occur in the adjacent areas with corrections in different directions. Therefore, the mapping image should be regarded as a whole. The deformation of the mapping image from the center to the edge becomes more and more serious. Therefore, gradient control lines can be set through the control points. As the control lines spread outwards, the correction degree of the pixel points is greater, thus ensuring the smoothness of the whole image.

[0025] On the other hand, in the process of the pixel points completing the shift correction to obtain the corrected image, there are problems of coordinate coincidence and pixel point loss. Existing methods often perform interpolation, and the overlapping pixel points obtain the final RGB value through the mean value. However, remote sensing images contain a large amount of information, and interpolation often leads to problems such as pixelation effects and discontinuous gray levels, resulting in the loss of effective information. Therefore, the present invention analyzes the effective information in the image and focuses on retaining the edges of the effective information during interpolation and pixel point fusion.

[0026] Reference Figure 1 , which shows the flow of some embodiments of the remote sensing mapping data enhancement method for real estate mapping according to the present invention. The remote sensing mapping data enhancement method for real estate mapping includes the following steps: Step S1, obtaining all target mapping images corresponding to the area to be mapped.

[0027] Among them, the area to be mapped can be the area to be mapped. The target mapping images can be mapping images representing different parts of the area to be mapped. The union of all target mapping images can cover the area to be mapped, and different target control points can be set in the area to be mapped. The target control points can be control points set finally for the convenience of mapping.

[0028] It should be noted that multiple surveying and mapping images of the area to be surveyed can be obtained through an unmanned aerial vehicle (UAV) surveying and mapping system, which are denoted as target surveying and mapping images. The UAV surveying and mapping system can include: a UAV, a flight control system, remote sensing equipment, a ground control station, and a data post-processing system. The UAV can include: the airframe of the aircraft, power supply, sensors, a navigator, propulsion equipment, etc. The flight control system can include: a GPS (Global Positioning System) receiver, a rotational speed sensor, an IMU / GPS system, etc. The remote sensing equipment can include: a high-resolution digital camera, a multispectral imager, a lidar, an infrared scanner, etc. The ground control station can include: flight monitoring and control, data acquisition, etc. The data post-processing system can include: processing sensor data, positioning and solving, etc.

[0029] The specific method for obtaining multiple surveying and mapping images of the area to be surveyed can be: designing an S-shaped UAV flight path; designing the layout of ground control points; and obtaining multiple surveying and mapping images at 30 fps through a high-resolution digital camera during the UAV flight process.

[0030] Geometric correction is to calculate the geographic coordinate information of each pixel point on the image using control points according to a certain mathematical model. Therefore, the layout and accuracy of the control points affect the correction result. Control points should be set at positions with relatively obvious structural and color characteristics, and the GPS coordinates of any control point should be obtained.

[0031] Image distortion is mainly divided into trapezoidal distortion, pincushion distortion, and barrel distortion. By taking the control points as the intersection points on the grid, the deformation network of the surveying and mapping image can be obtained. However, due to the uneven layout of the control points, there is a problem that there are too few control points on the surveying and mapping image to draw the network. Therefore, control point supplementation is required first. The distortion gradually becomes more serious from the center to the edge of the image. Therefore, the surveying and mapping image is divided into several circular regions, and there are differences in the distortion degree between the circular regions, that is, the distortion gradient. Therefore, the method of correcting the pixel points in each circular region according to the distortion degree they are in is the gradient geometric correction model.

[0032] As an example, the method for setting target control points can include the following steps: The first step is to perform quadrilateral connection processing starting from each initial control point in the area to be surveyed above, and obtain a sub-network corresponding to each initial control point.

[0033] Among them, the initial control points can be control points pre-set in the area to be surveyed through artificial experience for the convenience of surveying and mapping.

[0034] For example, obtaining the sub-network corresponding to each initial control point can include the following sub-steps: In the first sub-step, any one of the initial control points is determined as the marked control point, and the three non-collinear initial control points closest to the marked control point are selected from the area to be surveyed as the standard control points. Based on these three standard control points and the marked control point, a quadrilateral is constructed and denoted as the marked quadrilateral.

[0035] Among them, the four vertices of the marked quadrilateral can include: the marked control point and the three standard control points.

[0036] It should be noted that when constructing the quadrilateral, the perimeter of the quadrilateral can be made as small as possible.

[0037] In the second sub-step, each side of the marked quadrilateral is determined as the marked line segment, and the two non-intersection endpoints among the three initial control points on the adjacent two marked line segments form the set of initial control points between the adjacent two marked line segments.

[0038] It should be noted that there are usually three endpoints on the adjacent two marked line segments. Among them, one endpoint is the intersection point of the adjacent two marked line segments, and the other two endpoints are not the intersection points of the adjacent two marked line segments. These two endpoints that are not the intersection points of the adjacent two marked line segments can be called non-intersection endpoints.

[0039] In the third sub-step, if the included angle between the adjacent two marked line segments is less than the preset angle, the set of initial control points between the adjacent two marked line segments is determined as the marked set of initial control points; the initial control point closest to the marked set of initial control points is selected from all the initial control points in the area to be surveyed except the four endpoints of the marked quadrilateral as the reference control point, and the reference control point is connected to each initial control point in the marked set of initial control points to obtain the quadrilateral between the adjacent two marked line segments.

[0040] Among them, the preset angle can be a pre-set angle, which can be 180°. The method for obtaining the initial control point closest to the marked set of initial control points is as follows: each initial control point in the area to be surveyed except the four endpoints of the marked quadrilateral is determined as a candidate control point, the distance between each candidate control point and each initial control point in the marked set of initial control points is determined as the reference distance, and the set of reference distances corresponding to each candidate control point is obtained. The sum of all the reference distances in the set of reference distances corresponding to each candidate control point is determined as the overall distance corresponding to each candidate control point, and the candidate control point with the smallest corresponding overall distance is denoted as the initial control point closest to the marked set of initial control points.

[0041] In the fourth sub-step, the union of the marked quadrilateral and the quadrilaterals between all adjacent two marked line segments forms the sub-network corresponding to the marked control point.

[0042] In the second step, the union of the sub-networks corresponding to all the initial control points forms an initial four-corner network, and each initial control point within the above-mentioned initial four-corner network is determined as a reference control point.

[0043] In the third step, each initial control point within the area to be surveyed and mapped except for all the reference control points is determined as a temporary control point.

[0044] In the fourth step, the supplement of control points based on the reference control points and each temporary control point may include the following sub-steps: In the first sub-step, any one of the temporary control points is determined as a to-be-determined control point.

[0045] In the second sub-step, the reference control point closest to the to-be-determined control point is selected from all the reference control points as the reference control point corresponding to the to-be-determined control point.

[0046] In the third sub-step, the to-be-determined control point is connected to its corresponding reference control point to obtain a reference line segment.

[0047] In the fourth sub-step, two reference control points are arbitrarily selected from all the reference control points adjacent to the reference control point corresponding to the to-be-determined control point as template control points, obtaining two template control points. Taking each template control point as a starting point, line segments with the same direction and length as the direction and length of the above-mentioned reference line segment are drawn and denoted as target line segments, obtaining two target line segments.

[0048] Among them, two control points on the same side within the initial four-corner network can be two adjacent control points, that is to say, two adjacent control points are often the two endpoints of the same side within the initial four-corner network. The template control point can be an endpoint of the target line segment. The target line segment can be the same line segment as the reference line segment.

[0049] In the fifth sub-step, the endpoints other than the reference control points among all the endpoints of the two target line segments are supplemented as new control points.

[0050] In the fifth step, if the included angle between two adjacent sides in the above-mentioned initial four-corner network is greater than a preset angle, these two adjacent sides are used as the sides of a parallelogram to construct a parallelogram, and the newly formed endpoints are supplemented as new control points.

[0051] Among them, the preset angle can be a pre-set angle, and it can be 180°.

[0052] It should be noted that in the embodiments of the present invention, the sides in the initial four-corner network are the line segments that make up the initial four-corner network.

[0053] Step 6: Determine the average area of all quadrilaterals in the above initial four-corner network as the area representative factor.

[0054] Step 7: Screen out the quadrilaterals in the above initial four-corner network whose corresponding areas are greater than the above area representative factor as the quadrilaterals to be supplemented with control points.

[0055] Step 8: Set a reduced version of the quadrilateral to be supplemented with control points within each quadrilateral to be supplemented with control points, and supplement each endpoint of the reduced version of the quadrilateral to be supplemented with control points as a new control point.

[0056] Among them, the size of the reduced version of the quadrilateral to be supplemented with control points can be half of the size of the original quadrilateral to be supplemented with control points.

[0057] It should be noted that the corresponding endpoints on the quadrilateral to be supplemented with control points and its reduced version can be connected.

[0058] Step 9: Record each initial control point and each newly supplemented control point as target control points.

[0059] Step S2: Based on the target control points, set virtual control points for each target surveying and mapping image, and determine the correction coordinates corresponding to the pixel points between the virtual control points and the corresponding control point connections in each target surveying and mapping image based on the surveying and mapping coordinates and correction coordinates corresponding to the target control points, as well as the surveying and mapping coordinates corresponding to the virtual control points.

[0060] Among them, the target control points and virtual control points can be collectively referred to as control points.

[0061] As an example, this step may include the following steps: Step 1: Determine any one of the target surveying and mapping images as the marked surveying and mapping image.

[0062] Among them, the edge connection method between the target control points in the above marked surveying and mapping image can copy the edge connection method when obtaining the target control points.

[0063] Step 2: If the figure formed by all the target control points in the above marked surveying and mapping image is not a closed figure, connect the target control points at the opening of the figure formed by all the target control points in the above marked surveying and mapping image so that the figure formed by all the target control points in the above marked surveying and mapping image is a closed figure.

[0064] Step 3: Determine the closed figure formed by all the target control points in the above marked surveying and mapping image as the marked closed figure.

[0065] Step 4: Perform scaling or enlargement processing on the above marked closed figure to generate a new figure, and determine each endpoint of all the new figures generated at this time as a virtual control point.

[0066] For example, reduce the marked closed figure to 1 / 2 of its original size to obtain a new figure, and enlarge the marked closed figure to 2 times its original size to obtain another new figure. The endpoints on these two new figures can be recorded as virtual control points.

[0067] In the fifth step, select the smallest figure from the above-mentioned marked closed figure and all new figures as the reference figure, and determine any control point in the above-mentioned reference figure as the target origin.

[0068] Among them, the control point can be a target control point or a virtual control point.

[0069] In the sixth step, connect the above-mentioned target origin with all its corresponding control points to obtain the first target line.

[0070] Among them, the target origin and its corresponding control point can be the corresponding points obtained after the marked closed figure is scaled or enlarged. The first target line can represent the connection line of the distortion gradient where the target origin is located.

[0071] In the seventh step, determine the line passing through the above-mentioned target origin and perpendicular to the above-mentioned first target line as the second target line.

[0072] In the eighth step, with the above-mentioned target origin as the origin, the above-mentioned first target line as the vertical axis, and the above-mentioned second target line as the horizontal axis, construct a marked coordinate system.

[0073] In the ninth step, determine the correction coordinate corresponding to each virtual control point according to the surveying and mapping coordinate and correction coordinate corresponding to the target control point corresponding to each virtual control point, and the surveying and mapping coordinate corresponding to each virtual control point.

[0074] Among them, the virtual control point and its corresponding target control point can be the corresponding points obtained after the figure is scaled or enlarged, for example, they can be the points representing the position of the same object. The surveying and mapping coordinate corresponding to a pixel point can represent the position of the pixel point in the captured surveying and mapping image, and it can be the coordinate in the marked coordinate system. The correction coordinate can be the coordinate representing the actual position of the object obtained after correcting the surveying and mapping coordinate.

[0075] It should be noted that since the target control point is a position point set in the area to be surveyed for the convenience of surveying and mapping, the actual position of the target control point in the area to be surveyed is often known. For example, through GPS (Global Positioning System), the GPS coordinate corresponding to the target control point can be obtained, and thus the GPS distance corresponding to the target control point can be obtained. Scaling the GPS distance of the target control point to the image size can obtain the correction coordinate corresponding to the target control point.

[0076] For example, determining the calibration coordinates corresponding to each virtual control point based on the surveying coordinates and calibration coordinates of the target control point corresponding to each virtual control point, and the surveying coordinates of each virtual control point may include the following sub-steps: The first sub-step: Based on the surveying coordinates and calibration coordinates of the target control point corresponding to each virtual control point, determine the first parameter and the second parameter corresponding to each virtual control point through the affine transformation formula of the target control point corresponding to each virtual control point.

[0077] For example, the affine transformation formula of the target control point corresponding to the virtual control point may be: ; where is the cosine value of. is the sine value of. i is the serial number of the virtual control point. is the first parameter corresponding to the i-th virtual control point, which is equal to the angle between the surveying line segment and the calibration line segment of the target control point corresponding to the i-th virtual control point. The surveying line segment of the target control point is the line segment connecting the surveying coordinates of the target control point and the target origin. The calibration line segment of the target control point is the line segment connecting the calibration coordinates of the target control point and the target origin. and are respectively the abscissa and ordinate of the surveying coordinates of the target control point corresponding to the i-th virtual control point. is the second parameter corresponding to the i-th virtual control point, which is equal to the translation distance of the target control point corresponding to the i-th virtual control point. and are respectively the abscissa and ordinate of the calibration coordinates of the target control point corresponding to the i-th virtual control point.

[0078] The second sub-step: Based on the surveying coordinates, the first parameter, and the second parameter corresponding to each virtual control point, determine the calibration coordinates corresponding to each virtual control point through the affine transformation formula of each virtual control point.

[0079] For example, the affine transformation formula of the virtual control point may be: ; where is the cosine value of. is the sine value of. i is the serial number of the virtual control point. is the first parameter corresponding to the i-th virtual control point, which is equal to the angle between the surveying line segment and the calibration line segment of the target control point corresponding to the i-th virtual control point. and They are respectively the abscissa and ordinate of the surveying and mapping coordinates corresponding to the i-th virtual control point. It is the second parameter corresponding to the i-th virtual control point, which is equal to the translation distance of the target control point corresponding to the i-th virtual control point. and They are respectively the abscissa and ordinate of the corrected coordinates corresponding to the i-th virtual control point.

[0080] Step 10: Connect the corresponding control points to obtain candidate line segments. According to the surveying and mapping coordinates and corrected coordinates of the target control points on each candidate line segment, determine the corrected coordinates of each non-control point on each candidate line segment.

[0081] Among them, the corresponding control points can be the corresponding points obtained by scaling or expanding the graph. For example, they can be the points representing the positions of the same object. The non-control points on the candidate line segments can represent the pixel points between the connections of the corresponding control points. The non-control points can be the pixel points other than the control points. The formula for the corrected coordinates corresponding to the non-control points on the candidate line segments can be: ; ; where and They are respectively the abscissa and ordinate of the corrected coordinates corresponding to the j-th non-control point on the s-th candidate line segment. s is the serial number of the candidate line segment. j is the serial number of the non-control point on the s-th candidate line segment. It is the correction factor corresponding to the j-th non-control point on the s-th candidate line segment. is the cosine value of. is the sine value of. It is the angle between the surveying and mapping line segment and the corrected line segment corresponding to the target control point on the s-th candidate line segment. The surveying and mapping line segment corresponding to the target control point is the line segment connecting the surveying and mapping coordinates corresponding to the target control point and the target origin. The corrected line segment corresponding to the target control point is the line segment connecting the corrected coordinates corresponding to the target control point and the target origin. and They are respectively the abscissa and ordinate of the surveying and mapping coordinates corresponding to the j-th non-control point on the s-th candidate line segment. It is the translation distance of the target control point on the s-th candidate line segment. It is the distance between the j-th non-control point on the s-th candidate line segment and the target origin. It is the distance between the target control point and the target origin on the s-th candidate line segment. It is the GPS distance between the target control point and the target origin corresponding to each other in the actual scene on the s-th candidate line segment.

[0082] Step S3: For the pixel points in the target surveying and mapping image other than the pixel points between the control points and their connecting lines, based on the smallest quadrilateral to which the pixel point belongs, determine the corrected coordinates corresponding to the pixel point.

[0083] As an example, this step may include the following steps: First step: Determine any one pixel point in the target surveying and mapping image other than the pixel points between the control points and their connecting lines as the marked pixel point, and determine the smallest quadrilateral to which the above-mentioned marked pixel point belongs as the reference quadrilateral.

[0084] Among them, the four endpoints of the reference quadrilateral often include 2 groups of corresponding control points. One group of corresponding control points can be the corresponding points obtained by scaling or expanding the figure. For example, they can be the points representing the positions of the same object.

[0085] Second step: Determine the straight line where any one group of corresponding control points in the above-mentioned two groups of corresponding control points in the reference quadrilateral is connected as the first temporary straight line, and determine the straight line where the other group of corresponding control points is connected as the second temporary straight line.

[0086] Third step: Determine the straight line where any two adjacent non-corresponding control points in the above-mentioned reference quadrilateral are connected as the third temporary straight line.

[0087] Fourth step: Translate the above-mentioned third temporary straight line so that it passes through the above-mentioned marked pixel point to obtain the fourth temporary straight line, and determine the intersection point of the fourth temporary straight line and the first temporary straight line as the first marked intersection point.

[0088] Fifth step: Connect the above-mentioned marked pixel point and the above-mentioned first marked intersection point to obtain the fifth temporary straight line, and determine the included angle between the above-mentioned first temporary straight line and the fifth temporary straight line as the first temporary included angle.

[0089] Sixth step: Determine the included angle between the above-mentioned first temporary straight line and the second temporary straight line as the second temporary included angle.

[0090] Seventh step: Determine the intersection point of the above-mentioned first temporary straight line and the second temporary straight line as the second marked intersection point.

[0091] Eighth step: The formula for determining the corrected coordinates corresponding to the above-mentioned marked pixel point according to the distance between the above-mentioned marked pixel point and the first marked intersection point, the distance between the above-mentioned marked pixel point and the second marked intersection point, and the first temporary included angle and the second temporary included angle is: ; ; ; where and They are respectively the abscissa and ordinate of the corrected coordinates corresponding to the marked pixel points. is the cosine value of. is the sine value of. equals . and They are respectively the abscissa and ordinate of the mapping coordinates corresponding to the marked pixel points. is the translation distance of the control point closest to the marked pixel point on the reference quadrilateral. is the first temporary included angle. is the second temporary included angle. is the distance between the marked pixel point and the first marked intersection point. is the distance between the marked pixel point and the second marked intersection point.

[0092] It should be noted that the overall correction method from the control point to the connection line between control points and then to the connection line area surface can obtain the corrected coordinates of all pixel points. At the same time, since the control points are arranged according to the mapping area information, to a certain extent, it can avoid separating and correcting the effective information, resulting in information loss, and ensure the correction effect.

[0093] Step S4, according to the corrected coordinates corresponding to all pixel points in all target mapping images, screen out the overlapping pixel points representing the same geographical location from all target mapping images, and locate the missing pixel points with missing geographical locations.

[0094] It should be noted that since the movement of pixel points will cause the corrected coordinates of some pixel points to overlap and there will also be pixel point vacancies in the corrected image. For the overlapping pixel points, if they belong to the background area with less information content such as grassland and woods, and the RGB values of the overlapping pixel points have small differences, then directly use the average value of the RGB values of the overlapping pixel points as the value at the position of the pixel point in the corrected image. If the RGB values of the overlapping pixel points have large differences and some of the pixel points contain important information, then the pixel points with higher information content should be prioritized to avoid blurring the information in the corrected image. For the missing pixel points, the more important neighboring pixel points should also be used as a reference to ensure information transmission.

[0095] As an example, pixel points with the same corrected coordinates in all target surveying and mapping images can be determined as overlapping pixel points representing the same geographical location. In actual situations, since the photographed area is continuous, the corrected coordinates corresponding to all pixel points in all target surveying and mapping images should normally also be continuous. However, due to image distortion, some position points in the photographed area may be lost. Therefore, the position points corresponding to the lost corrected coordinates can be screened out from all target surveying and mapping images. For example, if there are a total of 3 corrected coordinates, which are (1, 1), (1, 2), and (1, 4) respectively, then the missing position point (1, 3) can represent the missing pixel point.

[0096] Step S5: Correct and supplement the RGB values corresponding to the overlapping pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points.

[0097] As an example, this step may include the following steps: First step: Determine the area composed of continuous overlapping pixel points or continuous missing pixel points as the reference area.

[0098] For example, based on the corrected coordinates corresponding to all pixel points in all target surveying and mapping images, a corrected image can be obtained, where the coordinate points in the corrected image can be represented by the corrected coordinates. The area composed of overlapping pixel points with continuous corrected coordinates in the corrected image can be determined as the reference area; and the area composed of missing pixel points with continuous corrected coordinates in the corrected image can be determined as the reference area.

[0099] Second step: Determine the area composed of the preset neighborhoods corresponding to all edge pixel points of each reference area as the overall neighborhood corresponding to each reference area.

[0100] Among them, the preset neighborhood can be a pre-set neighborhood, which can be an eight-neighborhood.

[0101] Third step: The pixel points in the overall neighborhood corresponding to each reference area except for the reference area itself form the surrounding representative area corresponding to each reference area.

[0102] Fourth step: According to the surrounding representative area corresponding to each reference area, the formula for determining the information importance corresponding to each reference area is: ; ; where is the information importance corresponding to the a-th reference area. a is the serial number of the reference area. is the normalization function. is the number of types of R values corresponding to all pixel points in the surrounding representative area corresponding to the a-th reference area. is the number of types of G values corresponding to all pixel points within the surrounding representative region corresponding to the a-th reference region. is the number of types of B values corresponding to all pixel points within the surrounding representative region corresponding to the a-th reference region. is the number of pixel points within the surrounding representative region corresponding to the a-th reference region. t and v are the sequence numbers of different pixel points within the surrounding representative region corresponding to the a-th reference region. is the pixel difference between the t-th pixel point and the v-th pixel point within the surrounding representative region corresponding to the a-th reference region. is the absolute value function. is the R value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region. is the R value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region. is the G value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region. is the G value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region. is the B value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region. is the B value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region.

[0103] Step 5. According to the information importance corresponding to each reference region, determining the information importance factor corresponding to each pixel point within the surrounding representative region corresponding to each reference region may include the following sub-steps: The first sub-step: Designate any one reference region as the marked reference region, designate any one pixel point within the surrounding representative region corresponding to the marked reference region as the reference pixel point, and designate the region within the surrounding representative region corresponding to the marked reference region except for the reference pixel point as the target sub-region.

[0104] The second sub-step: Determine the information importance corresponding to the marked reference region according to the surrounding representative region corresponding to the marked reference region.

[0105] The third sub-step: Determine the non-importance degree corresponding to the reference pixel point according to the target sub-region. The acquisition method thereof may refer to the acquisition method of the above-mentioned information importance. Specifically, it may be: Regard the target sub-region as the surrounding representative region corresponding to the marked reference region, execute the second sub-step of Step 5 of Step S5, and record the information importance obtained at this time as the non-importance degree corresponding to the reference pixel point.

[0106] The fourth sub-step: Determine the absolute value of the difference between the non-importance degree corresponding to the reference pixel point and the information importance corresponding to the marked reference region as the information importance factor corresponding to the reference pixel point.

[0107] Step 6. According to the information importance factors corresponding to all the pixel points within the reference region to which the overlapping pixel points representing the same geographical location belong, the formula for adjusting the R value corresponding to the overlapping pixel points representing the same geographical location can be: ; ; where is the adjusted R value corresponding to the overlapping pixel points representing the same geographical location. E is the number of overlapping pixel points representing the same geographical location. f is the serial number of the overlapping pixel points representing the same geographical location. T is the number of pixel points within the reference region to which the overlapping pixel points representing the same geographical location belong. k is the serial number of the pixel points within the reference region to which the overlapping pixel points representing the same geographical location belong. is the R value before adjustment corresponding to the f-th overlapping pixel point representing the same geographical location. is the information importance factor corresponding to the f-th pixel point within the reference region to which the f-th overlapping pixel point representing the same geographical location belongs. is the natural exponential function. is the distance between the f-th overlapping pixel point representing the same geographical location and the f-th pixel point within its reference region. is the absolute value function. is the R value corresponding to the f-th pixel point within the reference region to which the f-th overlapping pixel point representing the same geographical location belongs.

[0108] It should be noted that can be used as 's weight. When is larger, it often indicates that the difference in R values is smaller and the distance is smaller, and it often indicates that the weight of the f-th overlapping pixel point is larger.

[0109] Step 7. Similarly, according to the information importance factors corresponding to all the pixel points within the reference region to which the overlapping pixel points representing the same geographical location belong, adjust the G value and B value corresponding to the overlapping pixel points representing the same geographical location.

[0110] Step 8. According to the information importance factors corresponding to all the pixel points within the reference region to which each missing pixel point belongs, the formula for adjusting the R value corresponding to each missing pixel point is: ; ; where is the adjusted R value corresponding to the h-th missing pixel point. h is the serial number of the missing pixel point. is the number of pixel points within the reference region to which the h-th missing pixel point belongs. b is the serial number of the pixel points within the reference region to which the h-th missing pixel point belongs. is the R value corresponding to the b-th pixel within the reference region to which the h-th missing pixel belongs. is the information importance factor corresponding to the b-th pixel within the reference region to which the h-th missing pixel belongs. is the natural exponential function. is the distance between the h-th missing pixel and the b-th pixel within its belonging reference region.

[0111] Step 9. Similarly, according to the information importance factors corresponding to all pixels within the reference region to which each missing pixel belongs, adjust the G value and B value corresponding to each missing pixel.

[0112] Step S6. According to the adjusted RGB values corresponding to the overlapping pixels and missing pixels, and the unadjusted RGB values corresponding to other pixels, construct an enhanced overall mapping image.

[0113] As an example, the RGB values of the pixels at all missing positions and overlapping positions can be calculated, and the RGB values of the remaining positions are retained to obtain the true correction image of any mapping image. By registering and stitching all the correction images using the SIFT algorithm, a complete image of the area to be measured can be obtained as the mapping data for subsequent analysis and modeling.

[0114] In summary, the present invention corrects the entire image by establishing a gradient geometric correction model. For the missing or overlapping parts, numerical calculations are completed by analyzing the corresponding information importance, ensuring the information integrity of the mapping image and enhancing the mapping data.

[0115] Reference Figure 2 , based on the same inventive concept as the above method embodiment, the present invention provides a remote sensing mapping data enhancement system for real estate mapping. The system includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the remote sensing mapping data enhancement method for real estate mapping, which may specifically include: A mapping image acquisition module 201, configured to acquire all target mapping images corresponding to the area to be mapped, wherein the union of all target mapping images covers the area to be mapped, and different target control points are set within the area to be mapped; A setting determination module 202, configured to set virtual control points for each target mapping image based on the target control points, and determine the correction coordinates corresponding to the pixels between the virtual control points and the corresponding control point connection lines in each target mapping image based on the mapping coordinates and correction coordinates corresponding to the target control points, and the mapping coordinates corresponding to the virtual control points; The calibration coordinate determination module 203 is configured to determine, for the pixel points other than the pixel points between the control points and their connecting lines in the target surveying and mapping image, the calibration coordinates corresponding to the pixel points based on the smallest quadrilateral to which the pixel point belongs; The screening and positioning module 204 is configured to screen out the overlapping pixel points representing the same geographical location from all the target surveying and mapping images according to the calibration coordinates corresponding to all the pixel points in all the target surveying and mapping images, and locate the missing pixel points with missing geographical locations; The RGB adjustment module 205 is configured to correct and supplement the RGB values corresponding to the overlapping pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points; The surveying and mapping image enhancement module 206 is configured to construct an enhanced overall surveying and mapping image according to the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points, and the unadjusted RGB values corresponding to the other pixel points.

[0116] Figure 3 It is a schematic structural diagram of a computer device provided by an embodiment of the present invention. Exemplarily, as Figure 3 shown, the computer device 300 includes: a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and running on the processor 302. Wherein, when the processor 302 executes the computer program 303, the computer device can execute any of the remote sensing surveying and mapping data enhancement methods for real estate surveying and mapping introduced above.

[0117] Based on the same inventive concept as the above method embodiment, the present invention provides a server, including a memory and a processor. The memory is used to store executable program codes, and the processor is used to call and run the executable program codes from the memory, so that the device executes any of the remote sensing surveying and mapping data enhancement methods for real estate surveying and mapping described above.

[0118] Based on the same inventive concept as the above method embodiment, the present invention provides a computer program product, which includes: computer program codes. When the computer program codes run on a computer, the computer executes any of the remote sensing surveying and mapping data enhancement methods for real estate surveying and mapping described above.

[0119] Based on the same inventive concept as the above method embodiment, the present invention provides a computer-readable storage medium, which stores computer program codes. When the computer program codes run on a computer, the computer executes any of the remote sensing surveying and mapping data enhancement methods for real estate surveying and mapping described above.

[0120] In summary, when correcting the distortion of remote sensing mapping images through the geometric rectification theory, due to the large amount of information contained in the mapping images and the easy occurrence of information loss, as well as the diverse distortion situations of the mapping images, resulting in poor enhancement effects of the mapping images, the present invention analyzes the distortion of control points in the mapping images, establishes a gradient geometric rectification model of the mapping images, obtains the rectified images of the mapping images, and combines the characteristics that different distortion types will cause coincidence points and new pixel points in the rectified images to determine the information amount of the positions of the rectification points, so that the rectification points can ensure as much information as possible, obtain the rectified images, which is beneficial to improving the quality of mapping data and is beneficial to the subsequent reconstruction and analysis of the mapping area.

[0121] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and all should be included in the protection scope of the present invention.

Claims

1. A method for enhancing remote sensing mapping data for real estate surveying and mapping, characterized in that, Including the following steps: Obtain all target surveying and mapping images corresponding to the area to be surveyed. Among them, the union of all target surveying and mapping images covers the area to be surveyed, and different target control points are set in the area to be surveyed; Based on the target control points, set virtual control points for each target surveying and mapping image, and determine the calibration coordinates corresponding to the pixel points between the virtual control points and the corresponding control point connections in each target surveying and mapping image based on the surveying coordinates and calibration coordinates corresponding to the target control points, as well as the surveying coordinates corresponding to the virtual control points; For the pixel points in the target surveying and mapping image other than the pixel points between the control points and their connections, determine the calibration coordinates corresponding to the pixel points based on the smallest quadrilateral to which the pixel points belong; According to the calibration coordinates corresponding to all pixel points in all target surveying and mapping images, screen out the overlapping pixel points representing the same geographical location from all target surveying and mapping images, and locate the missing pixel points where the geographical location is missing; Correct and supplement the RGB values corresponding to the overlapping pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points; Construct an enhanced overall surveying and mapping image according to the adjusted RGB values corresponding to the overlapping pixel points and the missing pixel points, and the pre-adjustment RGB values corresponding to other pixel points; 2. The remote sensing mapping data enhancement method for real estate mapping according to claim 1, characterized in that The method for setting target control points includes: Perform quadrilateral connection processing starting from each initial control point in the area to be surveyed to obtain a sub-network corresponding to each initial control point, where the initial control point is a control point preset in the area to be surveyed; Form the union of the sub-networks corresponding to all initial control points to form an initial four-corner network, and determine each initial control point in the initial four-corner network as a reference control point; Determine each initial control point in the area to be surveyed except for all reference control points as a temporary control point; Perform control point supplementation based on the reference control points and each temporary control point; If the included angle between two adjacent sides in the initial four-corner network is greater than a preset angle, use these two adjacent sides as the sides of a parallelogram, construct a parallelogram, and supplement the newly formed endpoints as new control points; Determine the average value of the areas of all quadrilaterals in the initial four-corner network as the area representative factor; Screen out the quadrilaterals corresponding to areas greater than the area representative factor from the initial four-corner network as the quadrilaterals to be supplemented with control points; Set a reduced version of the quadrilateral to be supplemented with control points in each quadrilateral to be supplemented with control points, and supplement each endpoint of the reduced version of the quadrilateral to be supplemented with control points as a new control point; Record each initial control point and each newly supplemented control point as target control points; 3. The remote sensing mapping data enhancement method for real estate mapping according to claim 2, characterized in that The step of performing quadrilateral connection processing starting from each initial control point in the area to be surveyed to obtain a sub-network corresponding to each initial control point includes: Determine any one initial control point as a marked control point, screen out the three non-collinear initial control points closest to the marked control point from the area to be surveyed as standard control points, and construct a quadrilateral based on these three standard control points and the marked control point, denoted as the marked quadrilateral; Each side of the marked quadrilateral is determined as a marked line segment, and two non-intersection endpoints among the three initial control points on two adjacent marked line segments form an initial control point set between the two adjacent marked line segments; If the included angle between two adjacent marked line segments is less than a preset angle, the initial control point set between the two adjacent marked line segments is determined as a marked initial control point set, and the initial control point closest to the marked initial control point set is selected from all the initial control points in the area to be surveyed and mapped except the four endpoints of the marked quadrilateral as a reference control point, and the reference control point is connected to each initial control point in the marked initial control point set to obtain a quadrilateral between the two adjacent marked line segments; Among them, the method for obtaining the initial control point closest to the marked initial control point set is: each initial control point in the area to be surveyed and mapped except the four endpoints of the marked quadrilateral is determined as a candidate control point, the distance between each candidate control point and each initial control point in the marked initial control point set is determined as a reference distance to obtain a reference distance set corresponding to each candidate control point, and the sum value of all the reference distances in the reference distance set corresponding to each candidate control point is determined as the overall distance corresponding to each candidate control point, and the candidate control point with the smallest corresponding overall distance is recorded as the initial control point closest to the marked initial control point set; The union of the marked quadrilateral and the quadrilaterals between all adjacent two marked line segments constitutes the sub-network corresponding to the marked control points.

4. The remote sensing mapping data enhancement method for real estate mapping according to claim 2, characterized in that, The control point supplement based on the reference control points and each temporary control point includes: Any one of the temporary control points is determined as a to-be-determined control point; The reference control point closest to the to-be-determined control point is selected from all the reference control points as the reference control point corresponding to the to-be-determined control point; The to-be-determined control point is connected to its corresponding reference control point to obtain a reference line segment; Two reference control points adjacent to the reference control point corresponding to the to-be-determined control point are randomly selected as template control points, and line segments with the same direction and length as the reference line segment are drawn starting from each template control point, which are recorded as target line segments, and two target line segments are obtained; The endpoints of the two target line segments except the reference control points are supplemented as new control points.

5. The remote sensing mapping data enhancement method for real estate mapping according to claim 2, wherein Based on the target control points, virtual control points are set for each target surveying and mapping image, including: Any one of the target surveying and mapping images is determined as a marked surveying and mapping image, where the edge connection method between the target control points in the marked surveying and mapping image copies the edge connection method during the acquisition of the target control points; If the figure formed by all the target control points in the marked surveying and mapping image is not a closed figure, the target control points at the opening of the figure formed by all the target control points in the marked surveying and mapping image are connected to make the figure formed by all the target control points in the marked surveying and mapping image a closed figure; The closed figure formed by all the target control points in the marked surveying and mapping image is determined as a marked closed figure; Scale or expand the marked closed figure to generate a new figure, and determine each endpoint of all the new figures generated at this time as a virtual control point.

6. The remote sensing mapping data enhancement method for real estate mapping according to claim 5, characterized in that Determining the correction coordinates corresponding to the pixel points between the virtual control points and the corresponding control point connections in each target surveying and mapping image based on the surveying and mapping coordinates and correction coordinates corresponding to the target control points, and the surveying and mapping coordinates corresponding to the virtual control points, includes: Select the smallest figure from the marked closed figure and all the new figures as the reference figure, and determine any one control point in the reference figure as the target origin, where the control point is a target control point or a virtual control point; Connect the target origin to all its corresponding control points to obtain the first target straight line; Determine the straight line passing through the target origin and perpendicular to the first target straight line as the second target straight line; Construct a marked coordinate system with the target origin as the origin, the first target straight line as the vertical axis, and the second target straight line as the horizontal axis; Determine the correction coordinates corresponding to each virtual control point based on the surveying and mapping coordinates and correction coordinates corresponding to the target control points corresponding to each virtual control point, and the surveying and mapping coordinates corresponding to each virtual control point, where the virtual control point and its corresponding target control point are corresponding points obtained by scaling or expanding the figure, and the surveying and mapping coordinates are the coordinates in the marked coordinate system; Connect the corresponding control points to obtain a candidate line segment, and determine the correction coordinates corresponding to each non-control point on each candidate line segment based on the surveying and mapping coordinates and correction coordinates corresponding to the target control points on each candidate line segment, where the non-control points on the candidate line segment are the pixel points between the connections of the corresponding control points, and the formula for the correction coordinates corresponding to the non-control points on the candidate line segment is: ； ; wherein, and are respectively the abscissa and ordinate of the corrected coordinate corresponding to the j-th non-control point on the s-th candidate line segment; s is the serial number of the candidate line segment; j is the serial number of the non-control point on the s-th candidate line segment; is the correction factor corresponding to the j-th non-control point on the s-th candidate line segment; is the cosine value of; is the sine value of; is the angle between the surveyed line segment and the corrected line segment corresponding to the target control point on the s-th candidate line segment; the surveyed line segment corresponding to the target control point is the line segment connecting the surveyed coordinates corresponding to the target control point and the target origin; the corrected line segment corresponding to the target control point is the line segment connecting the corrected coordinates corresponding to the target control point and the target origin; and are respectively the abscissa and ordinate of the surveyed coordinates corresponding to the j-th non-control point on the s-th candidate line segment; is the translation distance of the target control point on the s-th candidate line segment; is the distance between the j-th non-control point and the target origin on the s-th candidate line segment; is the distance between the target control point and the target origin on the s-th candidate line segment; is the GPS distance between the target control point and the target origin corresponding in the actual scene.

7. The remote sensing mapping data enhancement method for real estate mapping according to claim 1, wherein For the pixel points in the target surveying and mapping image other than the pixel points between the control points and their connections, determining the correction coordinates corresponding to the pixel points based on the smallest quadrilateral to which the pixel points belong, includes: Determine any pixel point in the target surveying and mapping image other than the pixel points between the control points and their connections as a marked pixel point, and determine the smallest quadrilateral to which the marked pixel point belongs as the reference quadrilateral; Determine the straight line where any group of corresponding control point connections in the two groups of corresponding control points in the reference quadrilateral is located as the first temporary straight line, and determine the straight line where the other group of corresponding control point connections is located as the second temporary straight line; Determine the straight line where any two adjacent non-corresponding control point connections in the reference quadrilateral are located as the third temporary straight line; Translate the third temporary straight line so that it passes through the marked pixel point to obtain the fourth temporary straight line, and determine the intersection point of the fourth temporary straight line and the first temporary straight line as the first marked intersection point; Connect the marked pixel point and the first marked intersection point to obtain the fifth temporary straight line, and determine the angle between the first temporary straight line and the fifth temporary straight line as the first temporary angle; Determine the angle between the first temporary straight line and the second temporary straight line as the second temporary angle; Determine the intersection point of the first temporary straight line and the second temporary straight line as the second marked intersection point; The formula for determining the corrected coordinates corresponding to the marked pixel points according to the distance between the marked pixel points and the first marked intersection point, the distance between the marked pixel points and the second marked intersection point, and the first temporary angle and the second temporary angle is as follows: ； ； ; wherein, and are respectively the abscissa and ordinate of the calibration coordinates corresponding to the marked pixel points; is 's cosine value; is 's sine value; equals ; and are respectively the abscissa and ordinate of the surveying and mapping coordinates corresponding to the marked pixel points; is the translation distance of the control point on the reference quadrilateral closest to the marked pixel point; is the first temporary angle; is the second temporary angle; is the distance between the marked pixel point and the first marked intersection point; is the distance between the marked pixel point and the second marked intersection point.

8. The remote sensing mapping data enhancement method for real estate mapping according to claim 1, wherein The correction and supplementation of the RGB values corresponding to the coincident pixel points and the missing pixel points to obtain the adjusted RGB values corresponding to the coincident pixel points and the missing pixel points include: Determine the area composed of continuous coincident pixel points or continuous missing pixel points as the reference area; Determine the area composed of the preset neighborhoods corresponding to all edge pixel points of each reference area as the overall neighborhood corresponding to each reference area; The pixel points in the overall neighborhood corresponding to each reference area except for the reference area form the surrounding representative area corresponding to each reference area; The formula for determining the information importance corresponding to each reference area according to the surrounding representative area corresponding to each reference area is as follows: ； ; wherein, is the information importance corresponding to the a-th reference region; a is the serial number of the reference region; is a normalization function; is the number of types of R values corresponding to all pixel points within the surrounding representative region corresponding to the a-th reference region; is the number of types of G values corresponding to all pixel points within the surrounding representative region corresponding to the a-th reference region; is the number of types of B values corresponding to all pixel points within the surrounding representative region corresponding to the a-th reference region; is the number of pixel points within the surrounding representative region corresponding to the a-th reference region; t and v are the serial numbers of different pixel points within the surrounding representative region corresponding to the a-th reference region; is the pixel difference between the t-th pixel point and the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; is an absolute value function; is the R value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the R value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the G value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the G value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the B value corresponding to the t-th pixel point within the surrounding representative region corresponding to the a-th reference region; is the B value corresponding to the v-th pixel point within the surrounding representative region corresponding to the a-th reference region; Determine the information importance factor corresponding to each pixel point in the surrounding representative area corresponding to each reference area according to the information importance corresponding to each reference area; Adjust the R value corresponding to the coincident pixel points representing the same geographical location according to the information importance factors corresponding to all pixel points in the reference area to which the coincident pixel points representing the same geographical location belong; Similarly, adjust the G value and B value corresponding to the coincident pixel points representing the same geographical location according to the information importance factors corresponding to all pixel points in the reference area to which the coincident pixel points representing the same geographical location belong; The formula for adjusting the R value corresponding to each missing pixel point according to the information importance factors corresponding to all pixel points in the reference area to which each missing pixel point belongs is as follows: ； ; wherein, is the adjusted R value corresponding to the h-th missing pixel point; h is the serial number of the missing pixel point; is the number of pixel points within the reference area to which the h-th missing pixel point belongs; b is the serial number of the pixel point within the reference area to which the h-th missing pixel point belongs; is the R value corresponding to the b-th pixel point within the reference area to which the h-th missing pixel point belongs; is the information importance factor corresponding to the b-th pixel point within the reference area to which the h-th missing pixel point belongs; is the natural exponential function; is the distance between the h-th missing pixel point and the b-th pixel point within its reference area; Similarly, adjust the G value and B value corresponding to each missing pixel point according to the information importance factors corresponding to all pixel points in the reference area to which each missing pixel point belongs.

9. The remote sensing mapping data enhancement method for real estate mapping according to claim 8, wherein, The formula for adjusting the R value corresponding to the coincident pixel points representing the same geographical location according to the information importance factors corresponding to all pixel points in the reference area to which the coincident pixel points representing the same geographical location belong is as follows: ； ; wherein, is the adjusted R value corresponding to the overlapping pixel points representing the same geographical location; E is the number of overlapping pixel points representing the same geographical location; f is the serial number of the overlapping pixel points representing the same geographical location; T is the number of pixel points within the reference area to which the overlapping pixel points representing the same geographical location belong; k is the serial number of the pixel points within the reference area to which the overlapping pixel points representing the same geographical location belong; is the R value before adjustment corresponding to the f-th overlapping pixel point representing the same geographical location; is the information importance factor corresponding to the f-th pixel point within the reference area to which the f-th overlapping pixel point representing the same geographical location belongs; is the natural exponential function; is the distance between the f-th overlapping pixel point representing the same geographical location and the f-th pixel point within its reference area; is the absolute value function; is the R value corresponding to the f-th pixel point within the reference area to which the f-th overlapping pixel point representing the same geographical location belongs.

10. A remote sensing mapping data enhancement system for real estate mapping, characterized in that, It includes a processor and a memory. The processor is used to process the instructions stored in the memory to implement the remote sensing mapping data enhancement method for real estate mapping according to any one of claims 1-9.

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