A remote sensing image correction method based on optimal atmospheric synchronous correction parameters

Abstract

The present invention discloses a remote sensing image correction method based on optimal atmospheric synchronous correction parameters, including S1, calculating the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the pixel of the load to be corrected; selecting the pixel to be corrected with the smallest distance as the center, setting a rectangular window for screening the atmospheric synchronous correction parameters; determining the optimal atmospheric synchronous correction parameters based on the screened atmospheric synchronous correction parameters; for the pixels without corresponding atmospheric synchronous correction parameters of the load to be corrected, constructing the optimal atmospheric synchronous correction parameters by using the Kriging interpolation method; S2, based on the optimal atmospheric synchronous correction parameters, using the radiation transmission method to perform atmospheric correction on the image to be corrected to obtain the surface reflectivity. The advantage is that it solves the problem that when the atmospheric synchronous correction parameters and the load to be corrected are spatially matched, the atmospheric correction error of the load to be corrected is large due to the use of atmospheric synchronous correction parameters affected by broken clouds and thin clouds or the absence of effective atmospheric synchronous correction parameters.

Description

Technical Field

[0001] The invention relates to the technical field of satellite remote sensing quantitative inversion, and in particular to a remote sensing image correction method based on optimal atmospheric synchronous correction parameters. Background Art

[0002] Due to the absorption and scattering of the atmosphere, during the satellite remote sensing imaging process, on the one hand, the remote sensing image will be blurred, and on the other hand, the spectral characteristics of the objects will be changed, thus affecting the qualitative and quantitative use of the data. Therefore, in order to obtain the true information of the objects, atmospheric correction is required.

[0003] At present, in the atmospheric correction methods of satellite-borne remote sensing images, the atmospheric correction parameters are mainly derived from three sources: 1) ground station observations: for example, the global aerosol automatic monitoring network AERONET, but the ground stations are sparsely and unevenly distributed. Usually, it is difficult to match the image to be corrected to the corresponding ground station; 2) other satellite atmospheric products: for example, aerosol and water vapor products of MODIS, but because the atmosphere changes rapidly over time, different satellite transit times will cause large errors in atmospheric correction parameters; 3) inversion of satellite remote sensing data's own information: this method is suitable for sensors with more band information, such as MODIS sensors, but is not applicable to high-resolution remote sensing images with fewer bands; 4) based on atmospheric synchronous correctors: installing atmospheric synchronous correctors on the same satellite platform to obtain atmospheric correction parameters that are synchronized in time and space with the payload to be corrected, has great advantages and has been widely used, such as LEISA-LAC on the United States' Earth Observation-1 satellite (EO-1), CAVIS on the Worldiew-3 satellite, and TANSO-CAI on the Japanese Greenhouse Gas Monitoring Satellite (GOSAT).

[0004] In July 2020, my country launched the Gaofen Multi-mode Satellite, which is equipped with the Synchronous Atmosphere Polarimeter (SMAC). SMAC can simultaneously obtain intensity and polarization signals for inverting atmospheric synchronous correction parameters. SMAC is shot almost simultaneously with the main payload, using a dual-pixel observation mode, without imaging, imaging 10 times per second, and a spatial resolution of 6.7km. Based on SMAC data, some researchers have used methods such as optimization estimation to invert atmospheric correction parameters and used them for atmospheric correction of the main payload image; some researchers have proposed an atmospheric synchronous correction method (Syn-AC) based on the atmospheric correction parameters inverted from SMAC data to remove the influence of the atmosphere on the image to be corrected. However, due to the coarse spatial resolution and non-imaging of SMAC, it is difficult to accurately identify broken clouds and thin clouds based on its own information, resulting in large errors in the inverted atmospheric synchronous correction parameters. At present, when performing spatial matching of atmospheric synchronous correction parameters and the payload to be corrected, the closest atmospheric parameters are usually used or the matched atmospheric parameters are averaged. This method will introduce atmospheric parameter inversion results affected by broken clouds and thin clouds, thereby affecting the correction accuracy of the payload to be corrected. On the other hand, in areas with heavy cloud cover, the atmospheric correction instrument cannot invert the atmospheric correction parameters, resulting in no atmospheric correction parameters available for the payload to be corrected. Summary of the invention

[0005] The purpose of the present invention is to provide a remote sensing image correction method based on optimal atmospheric synchronization correction parameters, so as to solve the above-mentioned problems existing in the prior art.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A remote sensing image correction method based on optimal atmospheric synchronous correction parameters comprises the following steps:

[0008] S1. Calculate the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the pixel of the load to be corrected; select the pixel to be corrected with the smallest distance as the center and set a rectangular window; filter and retain the atmospheric synchronous correction parameters according to whether the rectangular window contains the cloud pixel of the load to be corrected; determine the optimal atmospheric synchronous correction parameters based on all the retained atmospheric synchronous correction parameters; for the pixels without corresponding atmospheric synchronous correction parameters of the load to be corrected, use the Kriging interpolation method to construct the optimal atmospheric synchronous correction parameters;

[0009] S2. Based on the optimal atmospheric synchronous correction parameters, the radiation transfer method is used to perform atmospheric correction on the image to be corrected to obtain the surface reflectivity.

[0010] Preferably, step S1 specifically includes the following contents:

[0011] S11, performing spatial matching calculation on the atmospheric synchronous correction instrument data and the load data to be corrected according to the latitude and longitude information, and determining the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected;

[0012] S12, selecting the pixel to be corrected that minimizes the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected as the center, and setting a rectangular window;

[0013] S13, judging whether the rectangular window contains the load cloud pixel to be corrected according to the recognition result of the load cloud to be corrected, if so, discarding the atmospheric synchronization correction parameter, otherwise, retaining the atmospheric synchronization correction parameter;

[0014] S14, calculating the atmospheric synchronization correction parameters covered by each pixel of the load to be corrected, and averaging all the retained atmospheric synchronization correction parameters as the optimal atmospheric synchronization correction parameters;

[0015] S15. For pixels without corresponding atmospheric synchronization correction parameters for the load to be corrected, the optimal atmospheric synchronization correction parameters are constructed for them by using the Kriging interpolation method based on the optimal atmospheric synchronization correction parameters.

[0016] Preferably, the distance calculation formula in step S11 is:

[0017]

[0018] in, The distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected; and are the longitudes of the atmospheric synchronous corrector and the payload to be corrected, respectively; and are the latitudes of the atmospheric synchronous corrector and the payload to be corrected, respectively.

[0019] Preferably, the size of the rectangular window in step S12 is , the calculation formula is,

[0020]

[0021] in, is the number of pixels; and are the spatial resolutions of the atmospheric synchronous corrector and the payload to be corrected, respectively.

[0022] Preferably, the calculation formula of the optimal atmospheric synchronization correction parameter in step S14 is:

[0023]

[0024] in, is the optimal atmospheric synchronization correction parameter; The reserved Atmospheric synchronization correction parameters; The number of all retained atmospheric synchronization correction parameters.

[0025] Preferably, the calculation formula of the optimal atmospheric synchronization correction parameter constructed by the Kriging method in step S15 is:

[0026]

[0027] in, The optimal atmospheric synchronization correction parameters constructed using the Kriging interpolation method; is the Kriging interpolation method.

[0028] Preferably, the calculation formula of the surface reflectivity in step S2 is:

[0029]

[0030] in, is the surface reflectivity; is the apparent reflectivity observed for the load to be corrected; is the atmospheric path radiation under the optimal atmospheric synchronous correction parameters; and are the downward and upward atmospheric transmittances under the optimal atmospheric synchronous correction parameters, respectively; is the atmospheric albedo under the optimal atmospheric synchronous correction parameters.

[0031] Preferably, before step S1, the step further includes:

[0032] Obtain the atmospheric synchronous correction parameters and the corresponding central longitude and latitude information inverted from the atmospheric synchronous correction instrument data of the satellite platform; obtain the multi-channel observation apparent reflectivity information, cloud identification results, and the corresponding solar zenith angle, azimuth angle, observation zenith angle, azimuth angle and longitude and latitude information of the payload image to be corrected on the satellite platform.

[0033] The beneficial effect of the present invention is that the present invention provides a method for screening and constructing the optimal atmospheric synchronization correction parameters for atmospheric correction of the load to be corrected in combination with the cloud identification result of the load to be corrected. The problem of large atmospheric correction error of the load to be corrected due to the use of atmospheric synchronization correction parameters affected by broken clouds and thin clouds or the absence of effective atmospheric synchronization correction parameters when the atmospheric synchronization correction parameters and the load to be corrected are matched in space is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of a remote sensing image correction method in an embodiment of the present invention;

[0035] Figure 2 Schematic diagram of the payload to be corrected in the embodiment of the present invention; wherein (a) is a schematic diagram of the atmospheric synchronous corrector and the observation of the payload to be corrected, the true color image is the image of the payload to be corrected, the circle is the observation center point of the atmospheric synchronous corrector, and the rectangular box represents the range of the atmospheric synchronous corrector observation point (P1); (b) is a cloud mask image of the payload to be corrected, and the gray bright spot area is the cloud mask.

[0036] Figure 3 1 is a comparison diagram of the load to be corrected before and after atmospheric correction in an embodiment of the present invention; wherein (a) is a true color image and a partial enlarged image of the load to be corrected before atmospheric correction, and (b) is a true color image and a partial enlarged image of the load to be corrected after atmospheric correction. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation methods described herein are only used to explain the present invention and are not used to limit the present invention.

[0038] like Figure 1 As shown, the present invention provides a remote sensing image correction method based on optimal atmospheric synchronous correction parameters. First, by combining the cloud identification information of the image to be corrected, high-precision atmospheric synchronous correction parameter information is screened from the atmospheric synchronous correction parameter results inverted by the atmospheric synchronous correction instrument; secondly, for the area without inversion results, the Kriging interpolation method is used to construct the optimal atmospheric synchronous correction parameters for it, and finally the accuracy of atmospheric correction of the image to be corrected is improved. In summary, the present invention provides a method for screening the optimal atmospheric correction parameters due to the influence of broken clouds and thin clouds, combined with the cloud identification results of the load to be corrected, and a method for constructing the optimal atmospheric synchronization parameters using the Kriging interpolation method due to the lack of atmospheric synchronous correction parameter inversion results due to factors such as clouds. The remote sensing image correction method provided by the present invention can improve the atmospheric correction accuracy of the image to be corrected and improve the effective atmospheric correction range of the image to be corrected.

[0039] In this embodiment, the execution process of the method of the present invention is specifically described using the high-resolution multi-mode satellite main payload and the atmospheric synchronous correction instrument SMAC remote sensing data.

[0040] 1. If Figure 2 As shown in the figure, for SMAC data, the data used include the atmospheric synchronous correction parameter aerosol model and aerosol optical thickness (AOD) data of the atmospheric synchronous correction instrument, and the corresponding longitude and latitude information; for the main payload data, the apparent reflectance data of four bands including 488, 559, 664, and 831nm, as well as the solar zenith angle, observation zenith angle, relative azimuth angle data, and longitude and latitude information are used.

[0041] 2. Spatially match the SMAC AOD data with the main load data according to the latitude and longitude information, and calculate the distance between the SMAC AOD parameter pixel and the main load pixel; the calculation formula is,

[0042]

[0043] in, is the distance between the SMAC atmospheric synchronous correction parameter pixel and the load pixel to be corrected; and are the longitudes of SMAC and the payload to be corrected, respectively; and are the latitudes of SMAC and the payload to be corrected, respectively.

[0044] 3. Select the pixel to be corrected that minimizes the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected as the center, set a rectangular window, and the size of the rectangular window is , the calculation formula is,

[0045]

[0046] in, is the number of pixels; and are the spatial resolutions of SMAC and the payload to be corrected, which are 6700m and 1.6m respectively. It is 4188.

[0047] 4. According to the main load cloud identification results, judge Whether the window contains cloud pixels. If so, the SMAC atmospheric synchronous correction aerosol parameters are removed. If not, the atmospheric synchronous correction parameters are retained.

[0048] 5. Calculate the SMAC AOD parameters covered by each pixel of the main load, and average all the retained SMAC AOD parameters to obtain the initial optimal atmospheric synchronous correction parameters. The calculation formula is:

[0049]

[0050] in, is the optimal AOD parameter of SMAC; is the first SMAC AOD parameters; is the sum of all SMAC AOD parameters retained in step 4); The number of all retained atmospheric synchronization correction parameters.

[0051] 6. For pixels with no corresponding SMAC AOD parameters for the main load pixels due to factors such as thin clouds and broken clouds, the SMAC optimal AOD parameters calculated in step 5) and the Kriging interpolation method are used to construct new optimal AOD parameters. The calculation formula is:

[0052]

[0053] in, is the optimal AOD parameter constructed using the Kriging interpolation method; is the Kriging interpolation method.

[0054] 7. Based on the optimal AOD parameters, the main payload image is atmospherically corrected based on the radiation transfer method to obtain the surface reflectance. The calculation formula is:

[0055]

[0056] in, is the surface reflectivity; Represents four bands: 488, 559, 664, 831nm; is the apparent reflectivity observed by the main payload; is the atmospheric radiation; and are the downward and upward atmospheric transmittances, respectively, is the atmospheric albedo. The optimal AOD parameters and aerosol model parameters are input into the 6SV radiation transfer model to calculate these atmospheric parameters, and finally the surface reflectivity after atmospheric correction is obtained. Figure 3 As shown in Table 1, it can be seen that the clarity and contrast of each band of the payload to be corrected are significantly improved before and after correction.

[0057] Table 1 Clarity and contrast of each band of the payload to be corrected before and after correction

[0058]

[0059] By adopting the above technical solution disclosed in the present invention, the following beneficial effects are obtained:

[0060] The present invention provides a remote sensing image correction method based on optimal atmospheric synchronous correction parameters, which solves the problem that when the atmospheric synchronous correction parameters and the load to be corrected are spatially matched, the atmospheric correction error of the load to be corrected is large due to the use of atmospheric synchronous correction parameters affected by broken clouds and thin clouds or the absence of effective atmospheric synchronous correction parameters.

[0061] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be considered as the scope of protection of the present invention.

Claims

1. A remote sensing image correction method based on optimal atmospheric synchronous correction parameters, characterized in that: The following steps are included: S1. Calculate the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the pixel of the load to be corrected; select the pixel to be corrected with the smallest distance as the center and set a rectangular window; filter and retain the atmospheric synchronous correction parameters according to whether the rectangular window contains the cloud pixel of the load to be corrected; determine the optimal atmospheric synchronous correction parameters based on all the retained atmospheric synchronous correction parameters; for the pixels without corresponding atmospheric synchronous correction parameters of the load to be corrected, use the Kriging interpolation method to construct the optimal atmospheric synchronous correction parameters; Step S1 specifically includes the following contents: S11, performing spatial matching calculation on the atmospheric synchronous correction instrument data and the load data to be corrected according to the latitude and longitude information, and determining the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected; S12, selecting the pixel to be corrected that minimizes the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected as the center, and setting a rectangular window; S13, judging whether the rectangular window contains the load cloud pixel to be corrected according to the recognition result of the load cloud to be corrected, if so, discarding the atmospheric synchronization correction parameter, otherwise, retaining the atmospheric synchronization correction parameter; S14, calculating the atmospheric synchronization correction parameters covered by each pixel of the load to be corrected, and averaging all the retained atmospheric synchronization correction parameters as the optimal atmospheric synchronization correction parameters; S15. For pixels without corresponding atmospheric synchronization correction parameters for the load to be corrected, the optimal atmospheric synchronization correction parameters are constructed for them by using the Kriging interpolation method based on the optimal atmospheric synchronization correction parameters; S2. Based on the optimal atmospheric synchronous correction parameters, the radiation transfer method is used to perform atmospheric correction on the image to be corrected to obtain the surface reflectivity.

2. The remote sensing image correction method based on optimal atmospheric synchronous correction parameters according to claim 1, characterized in that: The calculation formula of the distance in step S11 is: Where D is the distance between the atmospheric synchronous correction parameter pixel of the atmospheric synchronous correction instrument and the load pixel to be corrected; Lon S and Lon H are the longitudes of the atmospheric synchronous correction instrument and the payload to be corrected, respectively; Lat S and Lat H are the latitudes of the atmospheric synchronous corrector and the payload to be corrected, respectively.

3. The remote sensing image correction method based on optimal atmospheric synchronous correction parameters according to claim 1, characterized in that: The size of the rectangular window in step S12 is w*w, and the calculation formula is: w=R s / R H Where w is the number of pixels; R s and R H are the spatial resolutions of the atmospheric synchronous corrector and the payload to be corrected, respectively.

4. The remote sensing image correction method based on optimal atmospheric synchronous correction parameters according to claim 1, characterized in that: The calculation formula of the optimal atmospheric synchronization correction parameter in step S14 is: Among them, Atm b is the optimal atmospheric synchronization correction parameter; Atm i is the i-th atmospheric synchronous correction parameter retained; N is the number of all retained atmospheric synchronous correction parameters.

5. The remote sensing image correction method based on optimal atmospheric synchronous correction parameters according to claim 4, characterized in that: The calculation formula of the optimal atmospheric synchronization correction parameter constructed by the Kriging method in step S15 is: in, are the optimal atmospheric synchronization correction parameters constructed using the Kriging interpolation method; kring is the Kriging interpolation method.

6. The remote sensing image correction method based on optimal atmospheric synchronous correction parameters according to claim 5, characterized in that: The calculation formula of the surface reflectivity in step S2 is: Where SR is the surface reflectivity; ρ TOA is the apparent reflectivity observed by the load to be corrected; ρ P (Atm b ) is the atmospheric path radiation under the optimal atmospheric synchronous correction parameters; T ↓ (Atm b ) and T ↑ (Atm b ) are the downward and upward atmospheric transmittances under the optimal atmospheric synchronous correction parameters; S (Atm b ) is the atmospheric albedo under the optimal atmospheric synchronous correction parameters.

7. The remote sensing image correction method based on optimal atmospheric synchronous correction parameters according to any one of claims 1 to 6, characterized in that: Before step S1, the method further includes: Obtain the atmospheric synchronous correction parameters and the corresponding central longitude and latitude information inverted from the atmospheric synchronous correction instrument data of the satellite platform; obtain the multi-channel observation apparent reflectivity information, cloud identification results, and the corresponding solar zenith angle, azimuth angle, observation zenith angle, azimuth angle and longitude and latitude information of the payload image to be corrected on the satellite platform.

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