Cross radiation calibration method and device and electronic equipment

Abstract

The invention provides a cross radiation calibration method and device and electronic equipment, and the method comprises the steps: building a corresponding BRDF model for each calibration field in a global calibration field database based on the global calibration field database and a reference sensor image; inputting the first observation angle of the to-be-calibrated sensor image into the BRDF model, and performing spectrum matching to obtain the surface reflectance of the to-be-calibrated sensor image at the observation angle; according to the theoretical surface reflectance and the aerosol optical thickness of the to-be-calibrated sensor image at the transit moment, calculating the theoretical apparent reflectance of the to-be-calibrated sensor image; and the change trend of the theoretical apparent reflectivity of the to-be-calibrated sensor image under the long time sequence is obtained so as to carry out cross radiation calibration on the to-be-calibrated sensor in the time sequence. According to the method, on the basis of the global calibration field database, from the perspective of increasing the number of calibration fields, effective observation capable of being used for cross radiometric calibration is increased, so that the calibration frequency is increased.

Description

Technical Field

[0001] The present invention relates to the field of satellite remote sensing technology, and in particular to a cross-radiation calibration method, device and electronic equipment. Background Art

[0002] With the development of aerospace technology, satellite remote sensing data is becoming more and more popular in all walks of life, and the demand for radiation calibration and calibration sites is becoming more and more urgent. Especially in recent years, with the increasing number of satellite launches and the rapid development of drone technology in my country, higher requirements have been put forward for sensor radiation calibration.

[0003] The cross-radiation calibration method is a commonly used on-orbit calibration method for satellite sensors. The traditional cross-radiation calibration method requires the reference sensor and the sensor to be calibrated to pass through at the same time and the atmospheric conditions are good. The radiation performance of the sensor to be calibrated is corrected to the level of the reference sensor by matching image pairs. The constraints on angle and observation time are high, and the image pairs that can be obtained are limited, resulting in a low calibration frequency. Summary of the invention

[0004] The present invention provides a cross-radiation calibration method, device and electronic equipment to solve the problem in the prior art that the radiation performance of a sensor to be calibrated is corrected to the level of a reference sensor by matching image pairs, the constraints on angles and observation time are high, the image pairs that can be obtained are limited, and the calibration frequency is low.

[0005] The present invention provides a cross radiation calibration method, comprising the following steps: Based on a global calibration field database and a reference sensor image, construct a corresponding BRDF model for each calibration field in the global calibration field database; For each calibration field, a sensor image to be calibrated that passes through the calibration field is acquired, and a target reference sensor image is matched for the sensor image to be calibrated according to the transit time; Inputting the first observation angle of the sensor image to be calibrated into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the first observation angle; Obtaining a theoretical surface reflectance of the sensor image to be calibrated at the observation angle according to the surface reflectance and the spectral matching coefficient of the target reference sensor image at the first observation angle; According to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit, the theoretical apparent reflectivity of the sensor image to be calibrated is calculated; and the variation trend of the theoretical apparent reflectivity of the sensor image to be calibrated in a long time series is obtained to perform cross-radiation calibration on the sensor to be calibrated.

[0006] According to the cross-radiance calibration method provided by the present invention, the method of constructing a corresponding BRDF model for each calibration field in the global calibration field database based on the global calibration field database and the reference sensor image specifically includes: For each calibration field in the global calibration field database, obtaining a reference sensor image passing through the calibration field; Identify clean pixels in the reference sensor image; and perform atmospheric correction on the clean pixels to obtain a surface reflectance dataset of the clean pixels at different observation angles; A corresponding benchmark BRDF model is configured for each calibration field; and according to the surface reflectance data set, the model coefficients of the benchmark BRDF model are fitted to obtain the BRDF model corresponding to each calibration field.

[0007] According to the cross-radiation calibration method provided by the present invention, the identifying of clean pixels in the reference sensor image specifically includes: Dividing a plurality of observation angle ranges according to the observation angle of the reference sensor image; The angle corresponding to when the apparent reflectivity of the reference sensor image reaches a minimum value within each observation angle range is identified, and the reference sensor image pixel at the corresponding angle is used as the clean pixel.

[0008] According to the cross-radiation calibration method provided by the present invention, matching the target reference sensor image for the sensor image to be calibrated according to the transit time specifically includes: For each calibration field, obtaining a reference sensor image passing through the calibration field; The transit time of the reference sensor image passing through the calibration field is obtained, and the reference sensor image whose transit time is less than a preset transit time threshold is used as the target reference sensor image.

[0009] According to the cross-radiation calibration method provided by the present invention, the method further includes obtaining the spectral matching coefficient, specifically including: Acquiring a continuous spectrum curve of the surface of the calibration field; Obtaining the spectral response function of the reference sensor and the spectral response function of the sensor to be calibrated; The spectral matching coefficient is obtained according to the surface continuous spectral curve, the spectral response function of the reference sensor and the spectral response function of the sensor to be calibrated.

[0010] According to the cross-radiation calibration method provided by the present invention, the theoretical apparent reflectivity of the sensor image to be calibrated is calculated based on the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit, specifically comprising: Inputting a second observation angle of the target reference sensor image into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the second observation angle; Calculate the aerosol optical thickness of the target reference sensor image at the transit time according to the second observation angle and the surface reflectivity of the target reference sensor image at the second observation angle; The aerosol optical thickness of the target reference sensor image at the time of transit is used as the aerosol optical thickness of the sensor image to be calibrated at the time of transit; The theoretical apparent reflectivity of the sensor image to be calibrated is calculated based on the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit.

[0011] The present invention also provides a cross radiation calibration device, comprising the following parts: A model building module, for building a corresponding BRDF model for each calibration field in the global calibration field database based on the global calibration field database and the reference sensor image; An image matching module, for obtaining, for each calibration field, a sensor image to be calibrated that passes through the calibration field, and matching a target reference sensor image for the sensor image to be calibrated according to a transit time; A model application module, used for inputting the first observation angle of the sensor image to be calibrated into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the first observation angle; A first calculation module is used to obtain a theoretical surface reflectance of the sensor image to be calibrated at the observation angle according to the surface reflectance and spectral matching coefficient of the target reference sensor image at the first observation angle; The second calculation module is used to calculate the theoretical apparent reflectivity of the sensor image to be calibrated according to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit; and obtain the change trend of the theoretical apparent reflectivity of the sensor image to be calibrated over a long time series, so as to perform cross-radiation calibration on the sensor to be calibrated.

[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the lightweight small target pest detection method as described in any one of the above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the cross-radiation calibration method as described above is implemented.

[0014] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the cross-radiation calibration method as described above is implemented.

[0015] The cross-radiation calibration method, device and electronic device provided by the present invention provide a cross-radiation calibration method based on the global calibration field library to solve the problem of low calibration frequency of the traditional cross-radiation calibration method. The present invention combines the advantages of the global calibration field library with a wide distribution range and a large number, and from the perspective of increasing the number of calibration fields, increases the effective observations that can be used for cross-radiation calibration to increase the calibration frequency; at the same time, the present invention provides an idea of ​​constructing a BRDF model for the global calibration field library to reduce the uncertainty of the calibration results caused by the bidirectional reflection characteristics of the surface during the cross-calibration process. The entire process does not rely on measured data, reduces cost investment, improves the degree of automation, and can also realize the calibration of historical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is one of the flow charts of the cross radiation calibration method provided by the present invention.

[0018] Figure 2 This is the second flow chart of the cross radiation calibration method provided by the present invention.

[0019] Figure 3 This is the third flow chart of the cross radiation calibration method provided by the present invention.

[0020] Figure 4 It is a structural schematic diagram of the cross radiation calibration device provided by the present invention.

[0021] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the descriptions used in this way can be interchanged where appropriate, so that the embodiments can be implemented in a sequence other than that illustrated or described in the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of the steps that appear in the present application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved. The division of modules in this application is a logical division. There may be other division methods when it is implemented in actual applications. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between units can be electrical or other similar forms, which are not limited in this application. In addition, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical units, or may be distributed in multiple circuit units, and some or all of the units may be selected according to actual needs to achieve the purpose of the present application.

[0024] The definitions of relevant terms in the embodiments of the present invention are explained below.

[0025] In an embodiment of the present invention, the global calibration field library includes absolute calibration fields and pseudo-invariant calibration fields. The absolute calibration field refers to a calibration site equipped with observation instruments, which can perform on-orbit absolute radiation calibration of sensors by measuring surface spectra, atmospheric parameters, etc.; the pseudo-invariant calibration field refers to a site that is not equipped with observation instruments, but has a stable surface spectrum and spatially uniform, and is mainly used for on-orbit radiation performance monitoring and cross-radiation calibration of sensors, such as large-area uniform and stable surfaces such as deserts, Gobi, and snow; the global calibration field library also includes smaller pseudo-invariant features such as roads, roofs, and bare soil, which can be applied to cross-radiation calibration of very high-resolution remote sensing data such as meter-level and sub-meter-level.

[0026] Combine the following Figure 1-Figure 5 The specific contents of the present invention are described.

[0027] Figure 1It is a flow chart of a cross-radiation calibration method provided by the present invention, including steps S101-S105.

[0028] Step S101 : constructing a corresponding BRDF model for each calibration field in the global calibration field database based on the global calibration field database and the reference sensor image.

[0029] In the embodiment of the present invention, the data of each calibration site includes longitude and latitude, spatial range, radiation range, underlying surface type, etc.

[0030] In a possible implementation, in step S101, based on the global calibration field database and the reference sensor image, a corresponding BRDF model is constructed for each calibration field in the global calibration field database, specifically including steps S201-S203.

[0031] Step S201 : for each calibration site in the global calibration site database, a reference sensor image of the transit calibration site is obtained.

[0032] Specifically, for each calibration site in the global calibration site database, a long-time series of reference sensor images passing through the global calibration site database is obtained and preprocessed.

[0033] Exemplarily, the selected reference sensor has a similar spectral band setting to the sensor to be calibrated and has a rich multi-angle observation data set in the time series; in addition, the reference sensor should have high radiation accuracy and stable and consistent radiation performance over time. Preprocessing includes radiation calibration, geometric normalization, elimination of poor quality reference sensor images, image cropping, image observation angle calculation and extraction, etc. In an embodiment of the present invention, poor quality reference sensor images refer to images with large cloud and cloud shadow coverage or poor meteorological conditions.

[0034] Step S202, identifying clean pixels in the reference sensor image; and performing atmospheric correction on the clean pixels to obtain a surface reflectance dataset of the clean pixels at different observation angles.

[0035] In a possible implementation, in step S202, clean pixels in the reference sensor image are identified, specifically including: dividing the reference sensor image into a plurality of observation angle ranges according to the observation angle of the reference sensor image; identifying the angle corresponding to the minimum value of the apparent reflectance of the reference sensor image within each observation angle range, and using the reference sensor image pixel of the corresponding angle as a clean pixel.

[0036] For example, in the reference sensor image, the detection of clean pixels can be obtained by sorting the apparent reflectance of the pixels at different observation angles in the blue band. Specifically, the low-value part of the apparent reflectance within each observation angle range is extracted as the clean pixel. Considering the influence of the observation angle on the apparent reflectance, the observation angle range can be divided into intervals such as 0~10°, 10~20°, 20~30°, 30~40°, 40~50°, and sorted within the interval.

[0037] For example, the aerosol optical depth of clean pixels can be obtained through literature surveys, high-resolution image inversion, etc. Specifically, for calibration fields with field observation data, the aerosol optical depth can be directly calculated by counting the aerosol optical depth in clear weather; for calibration fields without field observation data, the aerosol optical depth can be obtained through inversion or other reference methods, for example, for calibration fields with dark targets (such as water bodies), it can be calculated using the dark pixel method.

[0038] In an embodiment of the present invention, a radiation transfer model lookup table is constructed through a radiation transfer model, and atmospheric correction is performed on clean pixels through the radiation transfer model lookup table to obtain a surface reflectance data set of the clean pixels at different observation angles.

[0039] In the embodiment of the present invention, the radiation transfer model is a simplified model used to simulate the complex atmospheric radiation transfer equation. By setting different surface parameters, atmospheric parameters, sensor parameters, observation geometry parameters and other model parameters, the apparent radiance and apparent reflectivity at the top of the atmosphere can be accurately simulated. Exemplarily, the radiation transfer models that can be used in the embodiment of the present invention include but are not limited to the 6S model and the MODTRAN model.

[0040] In an embodiment of the present invention, a radiation transfer model lookup table is established according to parameter ranges such as observation angle, surface reflectivity, apparent reflectivity, aerosol optical thickness, and atmospheric water vapor; taking the MODTRAN model as an example, the lookup table input of eight parameters, namely, atmospheric mode, surface reflectivity, aerosol optical thickness, elevation, observation zenith angle, solar zenith angle, relative azimuth, and atmospheric water vapor, can be set to obtain the corresponding relationship between the apparent reflectivity and the surface reflectivity under different observation angles and atmospheric conditions, as shown in Table 1.

[0041] Table 1 Parameter range comparison table

[0042] Subsequently, atmospheric correction is performed on the clean pixels in turn to obtain the surface reflectance dataset of the clean pixels at different observation angles. Specifically, according to the apparent reflectance of the clean pixel image, aerosol optical thickness, atmospheric water vapor, observation angle and other parameters, the surface reflectance of the clean pixel is interpolated by lookup table lookup to obtain the surface reflectance dataset at multiple angles.

[0043] Step S203, configuring a corresponding reference BRDF model for each calibration field; and fitting the model coefficients of the reference BRDF model according to the surface reflectance data set to obtain a corresponding BRDF model for each calibration field.

[0044] Specifically, a suitable benchmark BRDF model is selected for each calibration field. Different empirical statistical models, physical models, semi-empirical models, etc. can be selected based on previous research, or a new model can be established according to the calibration field conditions.

[0045] For calibration fields with different underlying surface types, select appropriate BRDF basic models (such as kernel-driven model, Staylor-Suttle model, Walthal model, etc.). You can also establish a statistical model based on the surface reflectance dataset, or establish a statistical model in the form of an observation angle-reflectance lookup table.

[0046] Exemplarily, a benchmark BRDF model used in an embodiment of the present invention is given, which is a kernel-driven semi-empirical BRDF model.

[0047] The kernel-driven semi-empirical BRDF model is as follows: in, represents the bidirectional reflectivity of the surface, which is the wavelength , Solar zenith angle , sensor observation zenith angle and the sun-sensor relative azimuth The function of , and are isotropic kernels (with kernel coefficients of ), the volume scattering kernel (the kernel coefficient is ) and the geometric optics kernel (the kernel coefficient is ).

[0048] For calibration sites in deserts or other semi-arid areas, the Staylor-Suttles model can also be tried. The formula is as follows: in: In the formula , , and N are free parameters, , , is the solar zenith angle, To observe the zenith angle, is the relative azimuth.

[0049] In an embodiment of the present invention, coefficients of a discrete benchmark BRDF model are fitted according to a surface reflectance dataset.

[0050] Step S102 : for each calibration field, obtaining the sensor image to be calibrated of the transit calibration field, and matching the target reference sensor image for the sensor image to be calibrated according to the transit time.

[0051] In the embodiments of the present invention, the transit time refers to the moment when the satellite moves in its orbit and passes over a specific geographical location (such as a ground observation station or a target area, which is designated as a reference area in the present invention).

[0052] In a possible implementation, in step S102, matching the target reference sensor image for the sensor image to be calibrated according to the transit time specifically includes: for each calibration field, obtaining the reference sensor image of the transit calibration field; obtaining the transit time of the reference sensor image of the transit calibration field, and taking the reference sensor image whose transit time is less than a preset transit time threshold as the target reference sensor image.

[0053] In the embodiment of the present invention, the difference between the transit time of the reference sensor image and the transit time of the sensor image to be calibrated is generally limited to within 1 hour to ensure that the atmospheric parameters remain unchanged.

[0054] Step S103: input the first observation angle of the sensor image to be calibrated into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the first observation angle.

[0055] Step S104, obtaining the theoretical surface reflectance of the sensor image to be calibrated at the observation angle according to the surface reflectance of the target reference sensor image at the first observation angle and the spectral matching coefficient.

[0056] Specifically, the surface reflectance of the reference sensor at the first observation angle is multiplied by the spectral matching coefficient to obtain the theoretical surface reflectance of the sensor image to be calibrated at the observation angle. The calculation formula is: in, is the spectral matching coefficient between the i-th band of the sensor to be calibrated and the j-th band of the reference sensor, is the equivalent surface reflectance of the i-th band of the sensor to be calibrated, is the equivalent surface reflectance of the j-th band of the reference sensor.

[0057] In a possible implementation, the method also includes obtaining a spectral matching coefficient, specifically including: obtaining a continuous surface spectral curve of the calibration field; obtaining a spectral response function of a reference sensor and a spectral response function of the sensor to be calibrated; and obtaining a spectral matching coefficient based on the continuous surface spectral curve, the spectral response function of the reference sensor, and the spectral response function of the sensor to be calibrated.

[0058] According to the spectral response functions of the reference sensor and the sensor to be calibrated, the equivalent surface reflectance at the channel is calculated respectively. The calculation formula is as follows: in, is the equivalent surface reflectivity of the sensor’s i-th band, is the spectral response function of the sensor, It is the continuous spectrum curve of the ground surface of the calibration field.

[0059] The ratio of the equivalent surface reflectance of the corresponding channels of the reference sensor and the sensor to be calibrated is calculated to obtain the spectral matching coefficient.

[0060] Step S105, calculating the theoretical apparent reflectivity of the sensor image to be calibrated according to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit; and obtaining the variation trend of the theoretical apparent reflectivity of the sensor image to be calibrated in a long time series, so as to perform cross-radiation calibration on the sensor to be calibrated.

[0061] In a possible implementation, in step S105, the theoretical apparent reflectivity of the sensor image to be calibrated is calculated according to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit, which specifically includes steps S301-S304.

[0062] Step S301: input the second observation angle of the target reference sensor image into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the second observation angle.

[0063] Specifically, the second observation angle of the reference sensor image is calculated or extracted, including the solar zenith angle, solar azimuth angle, observation zenith angle and observation azimuth angle, which can be obtained by longitude and latitude calculation and image file extraction. The second observation angle is input into the BRDF model to calculate the surface reflectance of the reference sensor image at the second observation angle.

[0064] Step S302, calculating the aerosol optical thickness of the target reference sensor image at the time of transit according to the second observation angle and the surface reflectivity of the target reference sensor image at the second observation angle.

[0065] In an embodiment of the present invention, the aerosol optical thickness of the reference sensor image at the time of transit is calculated based on the radiation transfer model lookup table obtained in the above embodiment and the second observation angle, surface reflectivity, apparent reflectivity, atmospheric water vapor and other parameter values.

[0066] Step S303, taking the aerosol optical thickness of the target reference sensor image at the time of transit as the aerosol optical thickness of the sensor image to be calibrated at the time of transit; Step S304, calculating the theoretical apparent reflectivity of the sensor image to be calibrated according to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit.

[0067] In an embodiment of the present invention, the theoretical apparent reflectance of the sensor image to be calibrated is calculated based on the radiation transfer model lookup table obtained in the above embodiment, according to the theoretical surface reflectance, aerosol optical thickness, atmospheric water vapor, spectral response, first observation angle and other parameters of the sensor image to be calibrated.

[0068] In a possible implementation, the sensor to be calibrated is cross-radiation calibrated according to the variation trend of the theoretical apparent reflectance of the sensor image to be calibrated in a long time series, specifically including: First, draw a scatter plot of the apparent reflectance of the image to be calibrated over a long time series, obtain a trend graph of the apparent reflectance over time, and fit a trend line: )+b, where is the calibration date, is the initial date of the time series, Expressed in days; Secondly, according to the above trend graph and the calibration date of the image to be calibrated, the theoretical apparent reflectance of the image to be calibrated is calculated, and the cross-calibration coefficient is further obtained; the calculation formula of the cross-calibration coefficient is as follows: in, and are the gain and bias values ​​of the calibration coefficients respectively, and L is the apparent radiance, which can be calculated by the following formula: in, is the theoretical apparent reflectance, is the distance between the Earth and the Sun, is the solar altitude angle, is the solar irradiance at the top of the atmosphere.

[0069] The present invention can achieve the following beneficial effects by adopting the above method: 1. The cross-radiation calibration method provided by the global calibration site library is used to solve the problem of low calibration frequency of the traditional cross-radiation calibration method. Combining the advantages of the global calibration site library with a wide distribution range and a large number, from the perspective of increasing the number of calibration sites, increase the effective observations that can be used for cross-radiation calibration to improve the calibration frequency.

[0070] 2. The present invention provides an idea of ​​constructing a BRDF model for the global calibration field library to reduce the uncertainty of the calibration results caused by the bidirectional reflection characteristics of the surface during the cross-calibration process. The entire process does not rely on measured data, reduces cost investment, improves the degree of automation, and can also realize the calibration of historical data.

[0071] 3. It can realize high-frequency, high-precision, high-efficiency, low-cost, long-time series, and fully automatic cross-radiation calibration, and can be applied to the radiation performance monitoring, radiation correction, and radiation normalization of multi-source remote sensing data of low, medium, high, and very high resolution sensors on orbit. Supported by remote sensing big data, the present invention can be used as an effective means of normalized cross-radiation calibration, radiation performance evaluation, and radiation normalization.

[0072] The cross radiation calibration device provided by the present invention is described below. The cross radiation calibration device described below and the cross radiation calibration method described above can be referred to each other.

[0073] Figure 4 A schematic diagram of the structure of a cross-radiation calibration device provided by the present invention includes the following parts: The model building module 410 is used to build a corresponding BRDF model for each calibration field in the global calibration field database based on the global calibration field database and the reference sensor image.

[0074] The image matching module 420 is used to obtain the sensor image to be calibrated of the transit calibration field for each calibration field, and match the sensor image to be calibrated with the target reference sensor image according to the transit time.

[0075] The model application module 430 is used to input the first observation angle of the sensor image to be calibrated into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the first observation angle.

[0076] The first calculation module 440 is used to obtain the theoretical surface reflectance of the sensor image to be calibrated at the observation angle according to the surface reflectance of the target reference sensor image at the first observation angle and the spectral matching coefficient.

[0077] The second calculation module 450 is used to calculate the theoretical apparent reflectance of the sensor image to be calibrated according to the theoretical surface reflectance and the aerosol optical thickness of the sensor image to be calibrated at the time of transit; and obtain the variation trend of the theoretical apparent reflectance of the sensor image to be calibrated in a long time series, so as to perform cross-radiation calibration on the sensor to be calibrated.

[0078] In a possible implementation, the model building module 410 is specifically configured to: For each calibration site in the global calibration site database, obtain a reference sensor image of the transit calibration site; Identify clean pixels in the reference sensor image; perform atmospheric correction on the clean pixels to obtain a surface reflectance dataset of the clean pixels at different observation angles; A corresponding benchmark BRDF model is configured for each calibration field; and the model coefficients of the benchmark BRDF model are fitted according to the surface reflectance dataset to obtain the corresponding BRDF model for each calibration field.

[0079] In a possible implementation, the model building module 410 is specifically configured to: According to the observation angle of the reference sensor image, multiple observation angle ranges are divided; The angle corresponding to the time when the apparent reflectance of the reference sensor image reaches the minimum value within each observation angle range is identified, and the reference sensor image pixel of the corresponding angle is used as a clean pixel.

[0080] In a possible implementation, the image matching module 420 is specifically configured to: For each calibration field, obtain a reference sensor image of the transit calibration field; The transit time of the reference sensor image of the transit calibration field is obtained, and the reference sensor image with a transit time less than a preset transit time threshold is used as the target reference sensor image.

[0081] In a possible implementation manner, the cross radiation calibration device further includes: a third calculation module.

[0082] The third calculation module is used to obtain the surface continuous spectral curve of the calibration field; obtain the spectral response function of the reference sensor and the spectral response function of the sensor to be calibrated; and obtain the spectral matching coefficient according to the surface continuous spectral curve, the spectral response function of the reference sensor and the spectral response function of the sensor to be calibrated.

[0083] In a possible implementation manner, the second calculation module 450 is specifically configured to: The second observation angle of the target reference sensor image is input into the BRDF model to obtain the surface reflectance of the target reference sensor image at the second observation angle; According to the second observation angle and the surface reflectivity of the target reference sensor image at the second observation angle, the aerosol optical thickness of the target reference sensor image at the time of transit is calculated; The aerosol optical thickness of the target reference sensor image at the time of transit is used as the aerosol optical thickness of the sensor image to be calibrated at the time of transit; The theoretical apparent reflectivity of the sensor image to be calibrated is calculated based on the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit.

[0084] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a cross radiation calibration method, which includes: Based on the global calibration field database and reference sensor images, a corresponding BRDF model is constructed for each calibration field in the global calibration field database; For each calibration field, the sensor image to be calibrated of the transit calibration field is obtained, and the target reference sensor image is matched for the sensor image to be calibrated according to the transit time; The first observation angle of the sensor image to be calibrated is input into the BRDF model to obtain the surface reflectance of the target reference sensor image at the first observation angle; According to the surface reflectance and spectral matching coefficient of the target reference sensor image at the first observation angle, the theoretical surface reflectance of the sensor image to be calibrated at the observation angle is obtained; According to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit, the theoretical apparent reflectivity of the sensor image to be calibrated is calculated; and the changing trend of the theoretical apparent reflectivity of the sensor image to be calibrated in a long time series is obtained to perform cross-radiation calibration on the sensor to be calibrated.

[0085] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0086] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute a cross-radiation calibration method provided by the above methods, the method comprising: Based on the global calibration field database and reference sensor images, a corresponding BRDF model is constructed for each calibration field in the global calibration field database; For each calibration field, the sensor image to be calibrated of the transit calibration field is obtained, and the target reference sensor image is matched for the sensor image to be calibrated according to the transit time; The first observation angle of the sensor image to be calibrated is input into the BRDF model to obtain the surface reflectance of the target reference sensor image at the first observation angle; According to the surface reflectance and spectral matching coefficient of the target reference sensor image at the first observation angle, the theoretical surface reflectance of the sensor image to be calibrated at the observation angle is obtained; According to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit, the theoretical apparent reflectivity of the sensor image to be calibrated is calculated; and the changing trend of the theoretical apparent reflectivity of the sensor image to be calibrated in a long time series is obtained to perform cross-radiation calibration on the sensor to be calibrated.

[0087] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the computer program is implemented to perform a cross-radiation calibration method provided by the above methods, the method comprising: Based on the global calibration field database and reference sensor images, a corresponding BRDF model is constructed for each calibration field in the global calibration field database; For each calibration field, the sensor image to be calibrated of the transit calibration field is obtained, and the target reference sensor image is matched for the sensor image to be calibrated according to the transit time; The first observation angle of the sensor image to be calibrated is input into the BRDF model to obtain the surface reflectance of the target reference sensor image at the first observation angle; According to the surface reflectance and spectral matching coefficient of the target reference sensor image at the first observation angle, the theoretical surface reflectance of the sensor image to be calibrated at the observation angle is obtained; According to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit, the theoretical apparent reflectivity of the sensor image to be calibrated is calculated; and the changing trend of the theoretical apparent reflectivity of the sensor image to be calibrated in a long time series is obtained to perform cross-radiation calibration on the sensor to be calibrated.

[0088] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0089] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0090] Finally, it should be noted that 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cross radiation calibration method, characterized in that: include: Based on a global calibration field database and a reference sensor image, construct a corresponding BRDF model for each calibration field in the global calibration field database; For each calibration field, a sensor image to be calibrated that passes through the calibration field is acquired, and a target reference sensor image is matched for the sensor image to be calibrated according to the transit time; Inputting the first observation angle of the sensor image to be calibrated into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the first observation angle; Obtaining a theoretical surface reflectance of the sensor image to be calibrated at the observation angle according to the surface reflectance and the spectral matching coefficient of the target reference sensor image at the first observation angle; The theoretical apparent reflectance of the sensor image to be calibrated is calculated based on the theoretical surface reflectance and the aerosol optical thickness of the sensor image to be calibrated at the time of transit; And obtain the variation trend of the theoretical apparent reflectivity of the image of the sensor to be calibrated in a long time series, so as to perform cross-radiation calibration on the sensor to be calibrated.

2. The cross radiation calibration method according to claim 1, characterized in that: The step of constructing a corresponding BRDF model for each calibration field in the global calibration field database based on the global calibration field database and the reference sensor image specifically includes: For each calibration field in the global calibration field database, obtaining a reference sensor image passing through the calibration field; Identify clean pixels in the reference sensor image; and perform atmospheric correction on the clean pixels to obtain a surface reflectance dataset of the clean pixels at different observation angles; A corresponding benchmark BRDF model is configured for each calibration field; and according to the surface reflectance data set, the model coefficients of the benchmark BRDF model are fitted to obtain the BRDF model corresponding to each calibration field.

3. The cross radiation calibration method according to claim 2, characterized in that: The identifying clean pixels in the reference sensor image specifically includes: Dividing a plurality of observation angle ranges according to the observation angle of the reference sensor image; The angle corresponding to when the apparent reflectivity of the reference sensor image reaches a minimum value within each observation angle range is identified, and the reference sensor image pixel at the corresponding angle is used as the clean pixel.

4. The cross radiation calibration method according to claim 1, characterized in that: According to the transit time, matching the target reference sensor image for the sensor image to be calibrated, specifically including: For each calibration field, obtaining a reference sensor image passing through the calibration field; The transit time of the reference sensor image passing through the calibration field is obtained, and the reference sensor image whose transit time is less than a preset transit time threshold is used as the target reference sensor image.

5. The cross radiation calibration method according to claim 1, characterized in that: The method further includes obtaining the spectrum matching coefficient, specifically including: Acquiring a continuous spectrum curve of the surface of the calibration field; Obtaining the spectral response function of the reference sensor and the spectral response function of the sensor to be calibrated; The spectral matching coefficient is obtained according to the surface continuous spectral curve, the spectral response function of the reference sensor and the spectral response function of the sensor to be calibrated.

6. The cross radiation calibration method according to claim 1, characterized in that: The step of calculating the theoretical apparent reflectivity of the sensor image to be calibrated according to the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit specifically includes: Inputting a second observation angle of the target reference sensor image into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the second observation angle; Calculate the aerosol optical thickness of the target reference sensor image at the transit time according to the second observation angle and the surface reflectivity of the target reference sensor image at the second observation angle; The aerosol optical thickness of the target reference sensor image at the time of transit is used as the aerosol optical thickness of the sensor image to be calibrated at the time of transit; The theoretical apparent reflectivity of the sensor image to be calibrated is calculated based on the theoretical surface reflectivity and the aerosol optical thickness of the sensor image to be calibrated at the time of transit.

7. A cross radiation calibration device, characterized in that: include: A model building module, for building a corresponding BRDF model for each calibration field in the global calibration field database based on the global calibration field database and the reference sensor image; An image matching module, for obtaining, for each calibration field, a sensor image to be calibrated that passes through the calibration field, and matching a target reference sensor image for the sensor image to be calibrated according to a transit time; A model application module, used for inputting the first observation angle of the sensor image to be calibrated into the BRDF model to obtain the surface reflectivity of the target reference sensor image at the first observation angle; A first calculation module is used to obtain a theoretical surface reflectance of the sensor image to be calibrated at the observation angle according to the surface reflectance and spectral matching coefficient of the target reference sensor image at the first observation angle; A second calculation module is used to calculate the theoretical apparent reflectance of the sensor image to be calibrated according to the theoretical surface reflectance and the aerosol optical thickness of the sensor image to be calibrated at the time of transit; And obtain the variation trend of the theoretical apparent reflectivity of the image of the sensor to be calibrated in a long time series, so as to perform cross-radiation calibration on the sensor to be calibrated.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the cross radiation calibration method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the cross-radiation calibration method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the cross-radiation calibration method according to any one of claims 1 to 6 is implemented.

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