Tower type hyperspectral water quality monitoring image correction method, device and equipment

Abstract

The application provides a tower type hyperspectral water quality monitoring image correction method, device and equipment, and relates to the technical field of hyperspectral image correction. The method comprises the following steps: acquiring a hyperspectral water quality monitoring image collected by a tower type hyperspectral imaging device as a target image; determining the ground projection center coordinates corresponding to each tower station scanning angle according to the tower station geographic coordinates, the tower station pitch angle, the scanning start angle, the scanning end angle and the column number of the image elements in the target image; calculating the row direction resolution of the target image according to the tower height in the tower station geographic coordinates, the tower station pitch angle and the tower station field of view angle; determining the geographic coordinates corresponding to each image element in the target image according to each ground projection center coordinate, the row direction resolution and each tower station scanning angle; and performing interpolation reconstruction on the target image on a regular output grid according to the geographic coordinates corresponding to each image element to obtain the corrected hyperspectral water quality monitoring image. The application can complete geometric correction only by using the imaging geometric parameters of the equipment.

Description

Technical Field

[0001] This invention relates to the field of hyperspectral image correction technology, and in particular to a tower-type hyperspectral water quality monitoring image correction method, apparatus and equipment. Background Technology

[0002] In the field of water quality remote sensing monitoring, tower-type hyperspectral imaging equipment has the advantages of continuous, fixed-point, and long-term observation, enabling high temporal resolution monitoring of the spectral characteristics of water bodies such as lakes, reservoirs, and rivers.

[0003] However, unlike drones or satellite platforms, tower hyperspectral equipment typically uses a pushbroom scanning imaging structure, resulting in images with significant geometric tilt. Due to the homogeneity of water surface reflection characteristics and the lack of obvious control points, existing geographic coordinate-based geometric correction methods, such as Rational Polynomial Coefficients (RPC) models and image registration algorithms, are difficult to apply in water quality monitoring scenarios when there are few ground feature points on the water surface. Consequently, it is difficult to complete traditional geographic registration and geometric correction, leading to spatial offset or distortion in tower hyperspectral water quality monitoring image data. This limits the spatial overlay and analysis accuracy of multi-temporal monitoring results, seriously affecting subsequent water quality parameter inversion, temporal change analysis, and accurate display of scanning results in geographic space. Summary of the Invention

[0004] This invention provides a tower-type hyperspectral water quality monitoring image correction method, device, equipment, and storage medium to solve the problem that traditional geometric correction methods are difficult to apply in water quality monitoring scenarios.

[0005] In a first aspect, embodiments of the present invention provide a tower-type hyperspectral water quality monitoring image correction method, comprising: Acquire hyperspectral water quality monitoring images collected by a tower-type hyperspectral imaging device and record them as target images; Based on the geographical coordinates of the tower station, the tower station elevation angle, the scan start angle, the scan end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging equipment, the ground projection center coordinates corresponding to each tower station scan angle are determined; wherein, the tower station scan angle is the angle corresponding to the scan line where each column of pixels in the target image is located; The row direction resolution of the target image is calculated based on the tower height in the geographical coordinates of the tower station, the tower station elevation angle, and the tower station field of view of the tower hyperspectral imaging device. Based on the ground projection center coordinates corresponding to the scanning angle of each tower station, the row direction resolution, and the scanning angle of each tower station, the geographic coordinates corresponding to each pixel in the target image are determined. The target image is reconstructed by interpolation on a regular output grid based on the geographic coordinates corresponding to each pixel, resulting in a corrected hyperspectral water quality monitoring image.

[0006] In one possible implementation, the ground projection center coordinates corresponding to each tower station scanning angle are determined based on the tower station's geographical coordinates, tower station elevation angle, scan start angle, scan end angle, and the number of columns of pixels in the target image. This includes: Based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging device, the angle corresponding to the scanning line where each column of pixels in the target image is located is determined and recorded as the tower station scanning angle. Based on the tower height and elevation angle in the geographical coordinates of the tower station of the tower hyperspectral imaging equipment, determine the ground projection distance of the imaging center ray of the tower hyperspectral imaging equipment; Based on the X and Y coordinates in the geographic coordinates of the tower station, the ground projection distance, and the scanning angle of each tower station, the ground projection center coordinates corresponding to the scanning angle of each tower station are determined.

[0007] In one possible implementation, based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging device, the angle corresponding to the scan line where each column of pixels in the target image is located is determined and denoted as the tower station scanning angle, including: according to The angle corresponding to the scan line where each column of pixels in the target image is located is determined and recorded as the tower station scan angle; in, The first in the target image The angle corresponding to the scan line where the column pixel is located, that is, the first... Each tower station scanning angle, , The column number of pixels in the target image. The scanning starting angle of the tower hyperspectral imaging device. This refers to the scanning end angle of the tower-type hyperspectral imaging device.

[0008] In one possible implementation, the ground projection distance of the imaging center ray of the tower hyperspectral imaging device is determined based on the tower height and elevation angle in the geographical coordinates of the tower station, including: according to Determine the ground projection distance of the imaging center ray of the tower hyperspectral imaging device; in, The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. The tower height is the geographical coordinate of the tower station for the tower-type hyperspectral imaging device. The elevation angle of the tower station.

[0009] In one possible implementation, the ground projection center coordinates corresponding to each tower station scanning angle are determined based on the X and Y coordinates in the geographical coordinates of the tower station, the ground projection distance, and the scanning angle of each tower station, including: according to Determine the ground projection center coordinates corresponding to the scanning angle of each tower station; in, For the first The ground projection center coordinates corresponding to the scanning angle of each tower station The X-coordinate in the geographic coordinates of the tower station. The Y-coordinate in the geographic coordinates of the tower station. The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. For the first Each tower station scanning angle.

[0010] In one possible implementation, the row direction resolution of the target image is calculated based on the tower height in the geographical coordinates of the tower station, the tower station elevation angle, and the tower station field of view of the tower hyperspectral imaging device, including: Based on the tower station elevation angle and the tower station field of view angle of the tower hyperspectral imaging device, calculate the elevation angle corresponding to the upper boundary ray and the lower boundary ray of the field of view of the tower hyperspectral imaging device. Based on the tower height in the geographical coordinates of the tower station and the elevation angle corresponding to the upper boundary ray of the field of view, calculate the nearest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located; Based on the tower height in the geographical coordinates of the tower station and the pitch angle corresponding to the lower boundary light of the field of view, calculate the farthest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located; Based on the difference between the farthest projection distance and the nearest projection distance, calculate the projection length on the ground corresponding to the scan line where each column of pixels in the target image is located; The row direction resolution of the target image is calculated based on the projection length and the number of rows of pixels in the target image.

[0011] In one possible implementation, determining the geographic coordinates of each pixel in the target image based on the ground projection center coordinates corresponding to each tower station's scan angle, the row direction resolution, and each tower station's scan angle includes: according to Determine the geographic coordinates corresponding to each pixel in the target image; in, The first in the target image Line number The geographic coordinates corresponding to the cells in the column. For the first Each tower station scanning angle The corresponding ground projection center coordinates, The row-direction resolution of the target image. The number of rows of pixels in the target image.

[0012] In one possible implementation, the target image is interpolated and reconstructed on a regular output grid based on the geographic coordinates corresponding to each pixel to obtain a corrected hyperspectral water quality monitoring image, including: Based on the geographic coordinates corresponding to each pixel, determine the range of X and Y coordinates; The size of the rule output grid is determined based on the X coordinate range, the Y coordinate range, and the set output resolution; A two-dimensional linear interpolation algorithm is performed on the spectral values ​​of the target image on the regular output grid to obtain a corrected hyperspectral water quality monitoring image; After obtaining the corrected hyperspectral water quality monitoring images, the following are also included: Output the corrected hyperspectral water quality monitoring images in a preset format.

[0013] Secondly, embodiments of the present invention provide a tower-type hyperspectral water quality monitoring image correction device, comprising: The acquisition module is used to acquire hyperspectral water quality monitoring images collected by the tower hyperspectral imaging device, which are denoted as the target image. The first processing module is used to determine the ground projection center coordinates corresponding to each tower station scanning angle based on the tower station's geographical coordinates, tower station elevation angle, scanning start angle, scanning end angle, and the number of columns of pixels in the target image; wherein, the tower station scanning angle is the angle corresponding to the scanning line where each column of pixels in the target image is located; The second processing module is used to calculate the row direction resolution of the target image based on the tower height in the geographical coordinates of the tower station, the tower station elevation angle, and the tower station field of view of the tower hyperspectral imaging device. The third processing module is used to determine the geographic coordinates of each pixel in the target image based on the ground projection center coordinates corresponding to the scanning angle of each tower station, the row direction resolution, and the scanning angle of each tower station. The interpolation and reconstruction module is used to interpolate and reconstruct the target image on a regular output grid based on the geographic coordinates corresponding to each pixel, so as to obtain the corrected hyperspectral water quality monitoring image.

[0014] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect or any possible implementation thereof.

[0015] In this embodiment of the invention, after acquiring the hyperspectral water quality monitoring image collected by the tower hyperspectral imaging device and recording it as the target image, the ground projection center coordinates corresponding to each tower station scanning angle are determined based on the tower station's geographical coordinates, tower station elevation angle, scanning start angle, scanning end angle, and the number of columns of pixels in the target image. The row direction resolution of the target image is calculated based on the tower height, tower station elevation angle, and tower station field of view of the tower hyperspectral imaging device. The geographical coordinates corresponding to each tower station scanning angle are determined based on the ground projection center coordinates, row direction resolution, and each tower station scanning angle. A geometric mapping model between the tower station scanning angle and the imaging pixels of the target image is constructed. Then, through geometric forward calculation, the corresponding position of each pixel on the ground (i.e., the geographical coordinates corresponding to each pixel) is determined, achieving a precise conversion from image coordinates to geographical coordinates. Based on this, the target image is reconstructed by interpolation on a regular output grid according to the geographic coordinates corresponding to each pixel, resulting in a corrected hyperspectral water quality monitoring image. This completes the reconstruction of each band of the target image on the regular output grid, ensuring geometric and spectral consistency. As a result, geometric correction can be completed without relying on external geographic control points, using only the imaging geometric parameters of the device. This is suitable for spectral monitoring scenarios without obvious ground features, such as lakes, reservoirs, and rivers, and can provide spatially accurate basic data for water body inversion, pollution monitoring, eutrophication analysis, etc. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the implementation of the tower-type hyperspectral water quality monitoring image correction method provided in this embodiment of the invention. Figure 2 This is a schematic diagram of a graphical interface for acquiring hyperspectral water quality monitoring images provided in an embodiment of the present invention; Figure 3 This is a comparison image of hyperspectral water quality monitoring images before and after correction provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of the tower-type hyperspectral water quality monitoring image correction device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0017] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0018] See Figure 1 This document illustrates a flowchart of the implementation of a tower-type hyperspectral water quality monitoring image correction method provided in an embodiment of the present invention. The executing entity of this tower-type hyperspectral water quality monitoring image correction method can be an electronic device with a processor and memory. This electronic device can be integrated into the tower-type hyperspectral imaging device or can be used as an external device to communicate with the tower-type hyperspectral imaging device. For example, when the electronic device is used as an external device, it can be a personal computer, laptop, PDA, cloud server, etc. The tower-type hyperspectral water quality monitoring image correction method is described in detail below: Step 101: Acquire the hyperspectral water quality monitoring image collected by the tower hyperspectral imaging device and record it as the target image.

[0019] In this embodiment, a tower-type hyperspectral imaging scanner can be used to acquire hyperspectral water quality monitoring images in TIFF format. Subsequently, the electronic device executing the tower-type hyperspectral water quality monitoring image correction method can acquire the hyperspectral water quality monitoring image as the target image for subsequent correction processing.

[0020] For example, operators can input hyperspectral water quality monitoring images such as... Figure 2 The "Input Image" location in the graphical user interface (GUI) shown enables the electronic device to acquire the target image that needs correction processing. Furthermore, it can also be based on, for example... Figure 2 The GUI shown retrieves the imaging geometry parameters of the tower hyperspectral imaging device, including: the geographical coordinates of the tower station (corresponding to...). Figure 2 The tower station X coordinate, tower station Y coordinate, tower height), and scan start angle (corresponding to) Figure 2 The scan start angle and scan end angle (corresponding to) Figure 2 (Scan end angle), tower station field of view (corresponding to) Figure 2 (Field of view in the middle), tower station elevation angle (corresponding to) Figure 2 The pitch angle is calculated so that subsequent corrections can be made based on imaging geometry parameters.

[0021] In this embodiment, by developing a visual user interface (GUI), it is possible to realize the input of tower station imaging geometric parameters, file browsing, progress display and automatic saving of output files, thereby facilitating on-site operation and batch processing.

[0022] Step 102: Determine the ground projection center coordinates corresponding to each tower station scanning angle based on the tower station's geographical coordinates, tower station elevation angle, scanning start angle, scanning end angle, and the number of columns of pixels in the target image.

[0023] The tower scanning angle is the angle corresponding to the scan line where each column of pixels in the target image is located.

[0024] In this embodiment, the geographical coordinates of the tower station of the tower-type hyperspectral imaging device are used. Tower station elevation angle Scan start angle End of scan corner and the number of columns of pixels in the target image We constructed the imaging geometric model of the tower-type hyperspectral imaging device.

[0025] Specifically, step 102 includes: Based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging equipment, the angle corresponding to the scanning line where each column of pixels in the target image is located is determined and recorded as the tower station scanning angle.

[0026] Based on the tower height and elevation angle in the geographical coordinates of the tower station of the tower hyperspectral imaging equipment, the ground projection distance of the imaging center ray of the tower hyperspectral imaging equipment is determined.

[0027] Based on the X and Y coordinates in the geographic coordinates of the tower station, the ground projection distance, and the scanning angle of each tower station, determine the ground projection center coordinates corresponding to the scanning angle of each tower station.

[0028] For example, based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging device, the angle corresponding to the scanning line where each column of pixels in the target image is located is determined and denoted as the tower station scanning angle, including: according to The angle corresponding to the scan line where each column of pixels in the target image is located is determined and recorded as the tower station scan angle.

[0029] in, For the target image, the first The angle corresponding to the scan line where the column pixel is located, that is, the first... Each tower station scanning angle, , The number of columns of pixels in the target image. The scanning starting angle of the tower hyperspectral imaging device. This refers to the scanning end angle of the tower-type hyperspectral imaging device.

[0030] For example, determining the ground projection distance of the imaging center ray of the tower hyperspectral imaging device based on the tower height and tower elevation angle in the geographical coordinates of the tower station includes: according to Determine the ground projection distance of the imaging center ray of the tower hyperspectral imaging device.

[0031] in, The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. The tower height is the geographical coordinate of the tower station for the tower-type hyperspectral imaging device. The elevation angle of the tower station.

[0032] For example, based on the X and Y coordinates in the geographic coordinates of the tower station, the ground projection distance, and the scanning angle of each tower station, the ground projection center coordinates corresponding to each tower station's scanning angle are determined, including: according to Determine the ground projection center coordinates corresponding to the scanning angle of each tower station.

[0033] in, For the first The ground projection center coordinates corresponding to the scanning angle of each tower station The X-coordinate in the geographic coordinates of the tower station. The Y-coordinate in the geographic coordinates of the tower station. The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. For the first Each tower station scanning angle.

[0034] In this embodiment, the position, scanning start angle, scanning end angle, field of view, and elevation angle of the tower-type hyperspectral imaging device are all fixed when acquiring hyperspectral water quality monitoring images. That is, the tower-type hyperspectral imaging device is at a fixed height. At this point, a fixed pitch angle is maintained. and scanning angle By performing a sector scan to obtain a hyperspectral water quality monitoring image, the angle corresponding to the scan line where each column of pixels in the hyperspectral water quality monitoring image is located can be obtained as follows: .

[0035] Based on this, the height of the tower And Tower Station Pitch Angle The ground projection distance of the imaging center ray of the tower hyperspectral imaging device can be obtained. Then, for each column of pixels, the corresponding tower station scanning angle According to Calculate the corresponding ground projection center coordinates, thereby establishing a one-to-one mapping relationship between the tower station scanning angle and the ground coordinates.

[0036] Step 103: Calculate the row direction resolution of the target image based on the tower height, tower elevation angle and tower field of view of the tower hyperspectral imaging device in the tower station's geographical coordinates.

[0037] In this embodiment, considering that the tower-type hyperspectral imaging device is in "view-scan" imaging mode, the spacing of row direction pixels on the ground is determined by the tower station's elevation angle and field of view. Therefore, the row direction resolution of the target image is calculated based on the tower height, elevation angle, and field of view in the tower station's geographical coordinates.

[0038] In one embodiment, step 103 includes: Based on the tower station elevation angle and the tower station field of view of the tower hyperspectral imaging device, calculate the elevation angle corresponding to the upper boundary ray and the lower boundary ray of the field of view of the tower hyperspectral imaging device.

[0039] Based on the tower height in the geographical coordinates of the tower station and the elevation angle corresponding to the upper boundary ray of the field of view, calculate the nearest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located.

[0040] Based on the tower height in the geographical coordinates of the tower station and the elevation angle corresponding to the lower boundary light ray of the field of view, calculate the farthest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located.

[0041] Based on the difference between the farthest projection distance and the nearest projection distance, calculate the projection length on the ground corresponding to the scan line containing each column of pixels in the target image.

[0042] The row direction resolution of the target image is calculated based on the projection length and the number of rows of pixels in the target image.

[0043] In this embodiment, specifically, it is assumed that the field of view of the tower station is... (Vertical field of view angle), then the pitch angle corresponding to the upper boundary ray of the field of view. Pitch angle corresponding to the lower boundary ray of the field of view They are respectively: ; Then, during imaging, the nearest projection distance on the ground corresponding to the scan line containing each column of pixels is... for: ; Then, during imaging, the farthest projection distance of the scan line corresponding to each column of pixels on the ground is... for: ; This allows us to calculate the projection length of the scan line containing each pixel on the ground. for: ; Then the line direction resolution It can be represented as: ,in, The number of rows of pixels in the target image.

[0044] In this embodiment, when the tower-type hyperspectral imaging device acquires the elevation angle change of hyperspectral water quality monitoring images, the corresponding row direction resolution can be calculated to achieve dynamic resolution adaptation.

[0045] Step 104: Determine the geographic coordinates of each pixel in the target image based on the ground projection center coordinates, row direction resolution, and scanning angle of each tower station.

[0046] For example, step 104 includes: according to Determine the geographic coordinates corresponding to each pixel in the target image.

[0047] in, For the target image, the first Line number The geographic coordinates corresponding to the cells in the column. For the first Each tower station scanning angle The corresponding ground projection center coordinates, This represents the row-direction resolution of the target image. The number of rows of pixels in the target image.

[0048] From this, the geographic coordinates corresponding to each pixel in the target image can be calculated. Obtain the complete geographic coordinate matrix This forms a mapping table from pixels to ground coordinates.

[0049] In this embodiment, a geographic projection reconstruction based on geometric modeling is performed on the target image. Based on the geometric imaging parameters of the tower station geographic coordinates, scanning start angle, scanning end angle, tower station elevation angle, and tower station field of view of the tower hyperspectral imaging equipment, a geometric mapping model between the corresponding angle of the scanning ray and the imaging pixel is constructed. Through geometric forward calculation, the corresponding position of each pixel on the ground (i.e., geographic coordinates) is determined, thereby achieving accurate conversion from image coordinates to geographic coordinates.

[0050] Step 105: Based on the geographic coordinates corresponding to each pixel, the target image is interpolated and reconstructed on the regular output grid to obtain the corrected hyperspectral water quality monitoring image.

[0051] In this embodiment, the geometric and spectral consistency of the corrected hyperspectral water quality monitoring image is ensured by interpolating and reconstructing the target image on a regular output grid.

[0052] In one embodiment, step 105 includes: Based on the geographic coordinates corresponding to each pixel, determine the range of X and Y coordinates.

[0053] The size of the rule output grid is determined based on the X-coordinate range, Y-coordinate range, and the set output resolution.

[0054] A two-dimensional linear interpolation algorithm is performed on the spectral values ​​of the target image on the regular output grid to obtain the corrected hyperspectral water quality monitoring image.

[0055] After obtaining the corrected hyperspectral water quality monitoring images, the following are also included: Output the corrected hyperspectral water quality monitoring images in a preset format.

[0056] In this embodiment, the geographic coordinate matrix is ​​obtained in the above steps. Then, the output range is obtained based on the geographic coordinate matrix: ; ; in, The range of X coordinates. The range of the Y coordinate.

[0057] Combination Figure 2 The GUI shown can also obtain the set output resolution (corresponding to...) Figure 2 The output resolution is set according to the X-coordinate range, Y-coordinate range, and the set output resolution. Determine the size of the rule output grid (including the width of the rule output grid). and high ): ; Subsequently, a two-dimensional linear interpolation algorithm based on SciPy (such as griddata) can be used to perform spatial interpolation reconstruction on the regular output grid using the following formula: ; in, For the first Bands in regular output grid The spectral values ​​obtained by up-interpolation For the target image, the first The original spectral values ​​of the band.

[0058] This embodiment uses a two-dimensional linear interpolation algorithm to reconstruct images of each band on a regular output grid, so as to ensure the geometric and spectral consistency of the corrected target image.

[0059] Based on this, the geographic coordinate system and affine transformation matrix can also be defined using rasterio: ; This allows the corrected hyperspectral water quality monitoring images, along with their projection coordinates, to be saved in GeoTIFF format, enabling them to be directly overlaid and analyzed in a GIS system.

[0060] For example, a comparison image of hyperspectral water quality monitoring images before and after correction is shown below. Figure 3 As shown, it can be seen that through the correction of the embodiments of the present invention, even without ground feature points, images with geometric distortions at a distance acquired by a tower hyperspectral imaging device (i.e., Figure 3 Image restoration (before correction) yields an image with eliminated geometric distortions and uniform near and far resolution (i.e., ...). Figure 3 (The corrected image).

[0061] This embodiment can be applied to fields such as ecological environment monitoring, geographic remote sensing, water quality remote sensing, environmental monitoring equipment, remote sensing software development, image processing and spatial information systems. It is integrated into the system of the tower hyperspectral imaging equipment. By inputting the imaging geometric parameters of the tower hyperspectral imaging equipment, high-precision geometric correction and geographic reference reconstruction can be achieved without ground control points. This allows for rapid geographic registration and geometric correction to be completed on-site or in the background, providing a reliable geometric basis for water quality remote sensing monitoring and spatially accurate basic data for water body inversion, pollution monitoring, eutrophication analysis, etc. It is suitable for spectral monitoring scenarios such as lakes, reservoirs, and rivers without obvious ground features.

[0062] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0063] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0064] Figure 4 A schematic diagram of the tower-type hyperspectral water quality monitoring image correction device provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below: like Figure 4 As shown, the tower-type hyperspectral water quality monitoring image correction device includes: The acquisition module 41 is used to acquire hyperspectral water quality monitoring images collected by the tower hyperspectral imaging device, which are denoted as target images.

[0065] The first processing module 42 is used to determine the ground projection center coordinates corresponding to each tower station scanning angle based on the tower station's geographical coordinates, tower station elevation angle, scanning start angle, scanning end angle, and the number of columns of pixels in the target image; wherein, the tower station scanning angle is the angle corresponding to the scanning line where each column of pixels in the target image is located.

[0066] The second processing module 43 is used to calculate the row direction resolution of the target image based on the tower height, tower elevation angle and tower field of view of the tower hyperspectral imaging device in the tower station's geographical coordinates.

[0067] The third processing module 44 is used to determine the geographic coordinates of each pixel in the target image based on the ground projection center coordinates, row direction resolution, and scanning angle of each tower station.

[0068] The interpolation and reconstruction module 45 is used to interpolate and reconstruct the target image on the regular output grid according to the geographic coordinates corresponding to each pixel, so as to obtain the corrected hyperspectral water quality monitoring image.

[0069] In one possible implementation, the first processing module 42 is specifically used for: Based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging equipment, the angle corresponding to the scanning line where each column of pixels in the target image is located is determined and recorded as the tower station scanning angle.

[0070] Based on the tower height and elevation angle in the geographical coordinates of the tower station of the tower hyperspectral imaging equipment, the ground projection distance of the imaging center ray of the tower hyperspectral imaging equipment is determined.

[0071] Based on the X and Y coordinates in the geographic coordinates of the tower station, the ground projection distance, and the scanning angle of each tower station, determine the ground projection center coordinates corresponding to the scanning angle of each tower station.

[0072] In one possible implementation, the first processing module 42 is specifically used for: according to The angle corresponding to the scan line where each column of pixels in the target image is located is determined and recorded as the tower station scan angle.

[0073] in, For the target image, the first The angle corresponding to the scan line where the column pixel is located, that is, the first... Each tower station scanning angle, , The number of columns of pixels in the target image. The scanning starting angle of the tower hyperspectral imaging device. This refers to the scanning end angle of the tower-type hyperspectral imaging device.

[0074] In one possible implementation, the first processing module 42 is specifically used for: according to Determine the ground projection distance of the imaging center ray of the tower hyperspectral imaging device.

[0075] in, The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. The tower height is the geographical coordinate of the tower station for the tower-type hyperspectral imaging device. The elevation angle of the tower station.

[0076] In one possible implementation, the first processing module 42 is specifically used for: according to Determine the ground projection center coordinates corresponding to the scanning angle of each tower station.

[0077] in, For the first The ground projection center coordinates corresponding to the scanning angle of each tower station The X-coordinate in the geographic coordinates of the tower station. The Y-coordinate in the geographic coordinates of the tower station. The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. For the first Each tower station scanning angle.

[0078] In one possible implementation, the second processing module 43 is specifically used for: Based on the tower station elevation angle and the tower station field of view of the tower hyperspectral imaging device, calculate the elevation angle corresponding to the upper boundary ray and the lower boundary ray of the field of view of the tower hyperspectral imaging device.

[0079] Based on the tower height in the geographical coordinates of the tower station and the elevation angle corresponding to the upper boundary ray of the field of view, calculate the nearest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located.

[0080] Based on the tower height in the geographical coordinates of the tower station and the elevation angle corresponding to the lower boundary light ray of the field of view, calculate the farthest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located.

[0081] Based on the difference between the farthest projection distance and the nearest projection distance, calculate the projection length on the ground corresponding to the scan line containing each column of pixels in the target image.

[0082] The row direction resolution of the target image is calculated based on the projection length and the number of rows of pixels in the target image.

[0083] In one possible implementation, the third processing module 44 is specifically used for: according to Determine the geographic coordinates corresponding to each pixel in the target image.

[0084] in, For the target image, the first Line number The geographic coordinates corresponding to the cells in the column. For the first Each tower station scanning angle The corresponding ground projection center coordinates, This represents the row-direction resolution of the target image. The number of rows of pixels in the target image.

[0085] In one possible implementation, the interpolation reconstruction module 45 is specifically used for: Based on the geographic coordinates corresponding to each pixel, determine the range of X and Y coordinates.

[0086] The size of the rule output grid is determined based on the X-coordinate range, Y-coordinate range, and the set output resolution.

[0087] A two-dimensional linear interpolation algorithm is performed on the spectral values ​​of the target image on the regular output grid to obtain the corrected hyperspectral water quality monitoring image.

[0088] Interpolation reconstruction module 45 is also used for: Output the corrected hyperspectral water quality monitoring images in a preset format.

[0089] Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. For example... Figure 5 As shown, the electronic device 5 of this embodiment includes a processor 50 and a memory 51. The memory 51 stores a computer program 52. When the processor 50 executes the computer program 52, it implements the steps in the various method embodiments described above. Alternatively, when the processor 50 executes the computer program 52, it implements the functions of each module / unit in the various device embodiments described above.

[0090] For example, computer program 52 may be divided into one or more modules / units, which are stored in memory 51 and executed by processor 50 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 52 in electronic device 5.

[0091] Electronic device 5 may include, but is not limited to, processor 50 and memory 51. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 5 may also include input / output devices, network access devices, buses, etc.

[0092] The processor 50 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0093] The memory 51 can be an internal storage unit of the electronic device 5, such as a hard disk or RAM. The memory 51 can also be an external storage device of the electronic device 5, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 51 can include both internal and external storage units of the electronic device 5. The memory 51 is used to store the computer program 52 and other programs and data required by the electronic device 5. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0094] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0095] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0096] This invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0097] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0098] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0099] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for correcting tower-type hyperspectral water quality monitoring images, characterized in that, include: Acquire hyperspectral water quality monitoring images collected by a tower-type hyperspectral imaging device and record them as target images; Based on the geographical coordinates of the tower station, the tower station elevation angle, the scan start angle, the scan end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging equipment, the ground projection center coordinates corresponding to each tower station scan angle are determined; wherein, the tower station scan angle is the angle corresponding to the scan line where each column of pixels in the target image is located; The row direction resolution of the target image is calculated based on the tower height in the geographical coordinates of the tower station, the tower station elevation angle, and the tower station field of view of the tower hyperspectral imaging device. Based on the ground projection center coordinates corresponding to the scanning angle of each tower station, the row direction resolution, and the scanning angle of each tower station, the geographic coordinates corresponding to each pixel in the target image are determined. The target image is reconstructed by interpolation on a regular output grid based on the geographic coordinates corresponding to each pixel, resulting in a corrected hyperspectral water quality monitoring image.

2. The tower-type hyperspectral water quality monitoring image correction method according to claim 1, characterized in that, Based on the geographical coordinates of the tower station, the tower station elevation angle, the scan start angle, the scan end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging equipment, the ground projection center coordinates corresponding to each tower station scan angle are determined, including: Based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging device, the angle corresponding to the scanning line where each column of pixels in the target image is located is determined and recorded as the tower station scanning angle. Based on the tower height and elevation angle in the geographical coordinates of the tower station of the tower hyperspectral imaging equipment, determine the ground projection distance of the imaging center ray of the tower hyperspectral imaging equipment; Based on the X and Y coordinates in the geographic coordinates of the tower station, the ground projection distance, and the scanning angle of each tower station, the ground projection center coordinates corresponding to the scanning angle of each tower station are determined.

3. The tower-type hyperspectral water quality monitoring image correction method according to claim 2, characterized in that, Based on the scanning start angle, scanning end angle, and the number of columns of pixels in the target image of the tower hyperspectral imaging equipment, the angle corresponding to the scanning line of each column of pixels in the target image is determined and denoted as the tower station scanning angle, including: according to The angle corresponding to the scan line where each column of pixels in the target image is located is determined and recorded as the tower station scan angle; in, The first in the target image The angle corresponding to the scan line where the column pixel is located, that is, the first... Each tower station scanning angle, , The column number of pixels in the target image. The scanning starting angle of the tower hyperspectral imaging device. This refers to the scanning end angle of the tower-type hyperspectral imaging device.

4. The tower-type hyperspectral water quality monitoring image correction method according to claim 2, characterized in that, Based on the tower height and elevation angle in the geographical coordinates of the tower hyperspectral imaging equipment, the ground projection distance of the imaging center ray of the tower hyperspectral imaging equipment is determined, including: according to Determine the ground projection distance of the imaging center ray of the tower hyperspectral imaging device; in, The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. The tower height is the geographical coordinate of the tower station for the tower-type hyperspectral imaging device. The elevation angle of the tower station.

5. The tower-type hyperspectral water quality monitoring image correction method according to claim 2, characterized in that, Based on the X and Y coordinates of the tower station's geographic coordinates, the ground projection distance, and the scanning angle of each tower station, the ground projection center coordinates corresponding to each tower station's scanning angle are determined, including: according to Determine the ground projection center coordinates corresponding to the scanning angle of each tower station; in, For the first The ground projection center coordinates corresponding to the scanning angle of each tower station The X-coordinate in the geographic coordinates of the tower station. The Y-coordinate in the geographical coordinates of the tower station. The ground projection distance of the imaging center ray of the tower hyperspectral imaging device. For the first Each tower station scanning angle.

6. The tower-type hyperspectral water quality monitoring image correction method according to claim 1, characterized in that, Based on the tower height in the geographical coordinates of the tower station, the tower station elevation angle, and the tower station field of view of the tower hyperspectral imaging device, the row direction resolution of the target image is calculated, including: Based on the tower station elevation angle and the tower station field of view angle of the tower hyperspectral imaging device, calculate the elevation angle corresponding to the upper boundary ray and the lower boundary ray of the field of view of the tower hyperspectral imaging device. Based on the tower height in the geographical coordinates of the tower station and the elevation angle corresponding to the upper boundary ray of the field of view, calculate the nearest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located; Based on the tower height in the geographical coordinates of the tower station and the pitch angle corresponding to the lower boundary light of the field of view, calculate the farthest projection distance on the ground corresponding to the scan line where each column of pixels in the target image is located; Based on the difference between the farthest projection distance and the nearest projection distance, calculate the projection length on the ground corresponding to the scan line where each column of pixels in the target image is located; The row direction resolution of the target image is calculated based on the projection length and the number of rows of pixels in the target image.

7. The tower-type hyperspectral water quality monitoring image correction method according to claim 1, characterized in that, Based on the ground projection center coordinates corresponding to the scanning angle of each tower station, the row direction resolution, and the scanning angle of each tower station, the geographic coordinates corresponding to each pixel in the target image are determined, including: according to Determine the geographic coordinates corresponding to each pixel in the target image; in, The first in the target image Line number The geographic coordinates corresponding to the cells in the column. For the first Each tower station scanning angle The corresponding ground projection center coordinates, The row-direction resolution of the target image. The number of rows of pixels in the target image.

8. The tower-type hyperspectral water quality monitoring image correction method according to claim 1, characterized in that, The target image is reconstructed by interpolation on a regular output grid based on the geographic coordinates corresponding to each pixel, resulting in a corrected hyperspectral water quality monitoring image, including: Based on the geographic coordinates corresponding to each pixel, determine the range of X and Y coordinates; The size of the rule output grid is determined based on the X coordinate range, the Y coordinate range, and the set output resolution; A two-dimensional linear interpolation algorithm is performed on the spectral values ​​of the target image on the regular output grid to obtain a corrected hyperspectral water quality monitoring image; After obtaining the corrected hyperspectral water quality monitoring images, the following are also included: Output the corrected hyperspectral water quality monitoring images in a preset format.

9. A tower-type hyperspectral water quality monitoring image correction device, characterized in that, include: The acquisition module is used to acquire hyperspectral water quality monitoring images collected by the tower hyperspectral imaging device, which are denoted as the target image. The first processing module is used to determine the ground projection center coordinates corresponding to each tower station scanning angle based on the tower station's geographical coordinates, tower station elevation angle, scanning start angle, scanning end angle, and the number of columns of pixels in the target image; wherein, the tower station scanning angle is the angle corresponding to the scanning line where each column of pixels in the target image is located; The second processing module is used to calculate the row direction resolution of the target image based on the tower height in the geographical coordinates of the tower station, the tower station elevation angle, and the tower station field of view of the tower hyperspectral imaging device. The third processing module is used to determine the geographic coordinates of each pixel in the target image based on the ground projection center coordinates corresponding to the scanning angle of each tower station, the row direction resolution, and the scanning angle of each tower station. The interpolation and reconstruction module is used to interpolate and reconstruct the target image on a regular output grid based on the geographic coordinates corresponding to each pixel, so as to obtain the corrected hyperspectral water quality monitoring image.

10. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 6.

Images