Method and device for acquiring in-orbit relative radiometric calibration coefficient of spaceborne camera

Abstract

The invention provides an on-orbit relative radiometric calibration coefficient obtaining method and device of a spaceborne camera, and the method comprises the steps: obtaining an on-orbit relative radiometric calibration coefficient relation model which is used for representing the relation between on-orbit relative radiometric calibration coefficients under different imaging parameters; determining a bright field uniform area and a dark field uniform area of the spaceborne camera under the first imaging parameter; on the basis of the bright field uniform region and the dark field uniform region, obtaining an on-orbit relative radiation calibration coefficient under the first imaging parameter; on the basis of the on-orbit relative radiometric calibration coefficient relation model and the on-orbit relative radiometric calibration coefficient under the first imaging parameter, on-orbit relative radiometric calibration coefficients under other imaging parameters are obtained, and the technical problem that in the prior art, the on-orbit relative radiometric calibration coefficient obtaining efficiency is low is solved.

Description

Technical Field

[0001] The present application relates to the technical field of satellite-borne cameras, and in particular to a method, device, electronic device and storage medium for obtaining an on-orbit relative radiation calibration coefficient of a satellite-borne camera. Background Art

[0002] High-resolution visible light remote sensing images have played an important role in mapping, urban planning, land use, environmental monitoring, military reconnaissance and other fields, bringing huge economic and military benefits. Countries around the world have launched a large number of high-resolution remote sensing satellites. With the advancement of science and technology, satellite performance has been continuously improved, the cost of developing high-resolution visible light cameras has been reduced, and earth observation has also changed from the traditional single-star mode to the star cluster constellation mode to obtain high-resolution remote sensing images with higher temporal resolution and larger observation range.

[0003] The relative radiometric calibration and correction of images of high-resolution visible light cameras during on-orbit operation are of great significance in target recognition and quantitative application of remote sensing data. Whether it is visible light payload or infrared payload, the acquisition of remote sensing images will be affected by factors such as inconsistent detector response, changes in electronic gain and offset, decay of the optical system, and particle contamination in the focal plane, resulting in the presence of longitudinal stripes, bands, or uneven brightness. For target recognition applications, these stripes and bands reduce the image quality, making it difficult to accurately identify targets from features such as geometry and texture; for quantitative application of remote sensing data, stripes and bands will increase the absolute radiometric calibration error and affect the accuracy of inversion of surface parameters (reflectivity, temperature, etc.). Therefore, it is necessary to perform on-orbit relative radiometric calibration and correction of high-resolution visible light cameras to eliminate stripes, bands, and uneven brightness in remote sensing images, and improve image quality and the quantitative level of remote sensing data.

[0004] In the traditional single-star mode, on-orbit relative radiation calibration is often achieved through the histogram matching method or the uniform field method. The histogram matching method requires statistics on a large amount of data to obtain an effective on-orbit relative radiation calibration coefficient lookup table, and the calibration cycle is relatively long; the uniform field method can only quickly obtain the on-orbit relative radiation calibration coefficient under a certain imaging parameter, and requires manual selection of uniform areas. Obviously, these two methods are difficult to meet the needs of rapid on-orbit relative radiation calibration of multiple stars in the constellation mode in a short period of time.

[0005] Therefore, how to improve the efficiency of on-orbit relative radiometric calibration of satellite-borne high-resolution visible light cameras to meet the needs of rapid calibration applications under multiple satellites and multiple imaging parameters has become a technical problem that needs to be solved urgently. Summary of the invention

[0006] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0007] To this end, the first purpose of the present application is to propose a method for obtaining the on-orbit relative radiation calibration coefficient of a satellite-borne camera, so as to improve the efficiency of the on-orbit relative radiation calibration of a satellite-borne high-resolution visible light camera, and to solve the problem in the related art that the on-orbit relative radiation calibration efficiency of high-resolution visible light cameras in current large-scale star cluster systems is low, and it is difficult to meet the needs of rapid calibration applications under multiple satellites and multiple imaging parameters.

[0008] The second objective of the present application is to provide a device for acquiring the on-orbit relative radiation calibration coefficient of a satellite-borne camera.

[0009] The third objective of the present application is to provide an electronic device.

[0010] A fourth objective of the present application is to provide a computer-readable storage medium.

[0011] A fifth object of the present application is to provide a computer program product.

[0012] To achieve the above-mentioned purpose, the first embodiment of the present application proposes a method for obtaining an on-orbit relative radiation calibration coefficient of a space-borne camera, comprising:

[0013] Acquire an on-orbit relative radiation calibration coefficient relationship model, where the on-orbit relative radiation calibration coefficient relationship model is used to characterize the relationship between on-orbit relative radiation calibration coefficients under different imaging parameters;

[0014] Determining a bright field uniform area and a dark field uniform area of ​​the spaceborne camera under a first imaging parameter;

[0015] Based on the bright field uniform area and the dark field uniform area, acquiring an on-orbit relative radiation calibration coefficient under the first imaging parameter;

[0016] Based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the first imaging parameter, the on-orbit relative radiation calibration coefficient under other imaging parameters is obtained.

[0017] To achieve the above-mentioned purpose, the second embodiment of the present application proposes a device for obtaining an on-orbit relative radiation calibration coefficient of a space-borne camera, comprising:

[0018] A model acquisition module, used to acquire an on-orbit relative radiation calibration coefficient relationship model, wherein the on-orbit relative radiation calibration coefficient relationship model is used to characterize the relationship between the on-orbit relative radiation calibration coefficients under different imaging parameters;

[0019] An area determination module, used to determine a bright field uniform area and a dark field uniform area of ​​the spaceborne camera under a first imaging parameter;

[0020] A coefficient calculation module, used for obtaining an on-orbit relative radiation calibration coefficient under the first imaging parameter based on the bright field uniform area and the dark field uniform area;

[0021] A coefficient deduction module is used to obtain the on-orbit relative radiation calibration coefficient under other imaging parameters based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the first imaging parameter.

[0022] To achieve the above-mentioned purpose, the third aspect embodiment of the present application proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method described in the first aspect.

[0023] To achieve the above-mentioned purpose, the fourth aspect of the present application proposes a computer-readable storage medium, in which computer-readable storage medium is stored computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in the first aspect.

[0024] To achieve the above-mentioned purpose, the fifth aspect of the present application proposes a computer program product, including a computer program, which implements the method described in the first aspect when executed by a processor.

[0025] The present application provides a method, device, electronic device and storage medium for obtaining on-orbit relative radiation calibration coefficients of a satellite camera, obtains an on-orbit relative radiation calibration coefficient relationship model that characterizes the relationship between on-orbit relative radiation calibration coefficients under different imaging parameters, determines the bright field uniform area and the dark field uniform area of ​​the satellite camera under a certain imaging parameter; and based on the bright field uniform area and the dark field uniform area, obtains the on-orbit relative radiation calibration coefficient under the imaging parameter; based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the imaging parameter, obtains the on-orbit relative radiation calibration coefficient under other imaging parameters, realizes the automatic calculation of the on-orbit relative radiation calibration coefficient of the satellite camera, and can realize the deduction of the on-orbit relative radiation calibration parameters under different imaging parameters, improves the efficiency of obtaining the on-orbit relative radiation calibration coefficient of the satellite-borne visible light camera, thereby realizing the rapid on-orbit relative radiation calibration of a high-resolution visible light camera under multiple satellites and multiple imaging parameters, and solves the problem in the related art that the on-orbit relative radiation calibration efficiency of high-resolution visible light cameras in current large-scale star cluster systems is low, and it is difficult to meet the needs of rapid calibration applications under multiple satellites and multiple imaging parameters. In addition, the uniform field method is used to achieve the advantage of quickly obtaining the relative radiation calibration coefficient under a certain imaging parameter, and its calibration efficiency is improved through the automatic selection method of uniform areas.

[0026] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0028] Figure 1 A schematic flow chart of a method for obtaining an on-orbit relative radiation calibration coefficient of a spaceborne camera provided in an embodiment of the present application;

[0029] Figure 2 A schematic diagram of the working principle of the TDI detector provided in the embodiment of the present application;

[0030] Figure 3 A flow chart of a method for determining bright and dark field uniform areas provided in an embodiment of the present application;

[0031] Figure 4 A schematic diagram of the division and movement of the full-width sliding window provided in an embodiment of the present application.

[0032] Figure 5 A schematic diagram of deducing on-orbit relative radiation calibration coefficients for different imaging parameters provided in an embodiment of the present application;

[0033] Figure 6a A graph showing the relationship between the grayscale value of the edge detector response and the exposure time provided in an embodiment of the present application;

[0034] Figure 6b A graph showing the relationship between the grayscale value of the central detector response and the exposure time provided in an embodiment of the present application;

[0035] Figure 7 A graph showing the relationship between the grayscale value of the detector response and the gain at the 3rd and 4th gain levels provided in the embodiment of the present application;

[0036] Figure 8a The automatic selection result of the bright field uniform area provided in the embodiment of the present application;

[0037] Figure 8b The automatic selection result of the dark field uniform area provided in the embodiment of the present application;

[0038] Figure 9a This is the integrating sphere image with a 20ms exposure time provided in the embodiment of the present application;

[0039] Figure 9b This is a diagram showing the effect of relative radiation correction of an integrating sphere image using the 20ms relative radiation calibration coefficient derived from the 10ms provided in the embodiment of the present application;

[0040] Fig.10a The 4-level gain desert image provided in the embodiment of the present application;

[0041] Fig.10b This is a diagram showing the effect of relative radiation correction of a desert image using the 4-level gain laboratory relative radiation calibration coefficients provided in the embodiment of the present application;

[0042] Fig.10c This is a diagram showing the effect of relative radiation correction of a desert image using the 4-level gain relative radiation calibration coefficient derived from the 3-level gain provided in an embodiment of the present application.

[0043] Fig.11 A block diagram of a device for acquiring an on-orbit relative radiation calibration coefficient of a space-borne camera provided in an embodiment of the present application;

[0044] Fig.12 A block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0046] The following describes, with reference to the accompanying drawings, a method, device, and apparatus for obtaining the on-orbit relative radiation calibration coefficient of a spaceborne camera in an embodiment of the present application.

[0047] Figure 1 A schematic flow chart of a method for obtaining an on-orbit relative radiation calibration coefficient of a spaceborne camera provided in an embodiment of the present application.

[0048] It should be noted that the executor of the method for obtaining the on-orbit relative radiation calibration coefficient of the satellite-borne camera in the embodiment of the present application is the device for obtaining the on-orbit relative radiation calibration coefficient of the satellite-borne camera in the embodiment of the present application. The device for obtaining the on-orbit relative radiation calibration coefficient of the satellite-borne camera can be configured in an electronic device so that the electronic device can perform the function of obtaining the on-orbit relative radiation calibration coefficient of the satellite-borne camera.

[0049] like Figure 1 As shown, the method for obtaining the on-orbit relative radiation calibration coefficient of the spaceborne camera includes the following steps 101-104:

[0050] Step 101 : obtaining an on-orbit relative radiation calibration coefficient relationship model under multiple imaging parameters, where the on-orbit relative radiation calibration coefficient relationship model is used to characterize the relationship between on-orbit relative radiation calibration coefficients under multiple imaging parameters.

[0051] As an implementation method, a method for obtaining an on-orbit relative radiation calibration coefficient relationship model under multiple imaging parameters includes:

[0052] Based on the imaging parameter adjustment principle and linear decomposability principle of the spaceborne camera, a model for the relationship between the on-orbit relative radiation calibration coefficients under multiple imaging parameters is constructed.

[0053] Based on the laboratory radiation calibration data of the spaceborne camera, the coefficients of the on-orbit relative radiation calibration coefficient relationship model are determined.

[0054] In some embodiments, based on the imaging parameter adjustment principle of the spaceborne camera and the linear decomposability principle, an implementation method of constructing an on-orbit relative radiation calibration coefficient relationship model under multiple imaging parameters includes the following contents:

[0055] First of all, it should be noted that the general satellite-borne high-resolution visible light camera uses linear array push-scan imaging and time delay integration (TDI) technology to improve sensitivity and signal-to-noise ratio to obtain high-quality images. The working principle of TDI detector is as follows Figure 2 As shown. The TDI detector is actually a planar array detector with far more columns than rows. The number of detector columns is consistent with the number of image columns, and the number of detector rows represents the number of integrable levels. For example, ground scenes are marked with stars, triangles, and circles. The camera moves forward with the satellite to form an image. At t1, the ground scene circle is exposed by the first row of detectors of the TDI detector. At t2, the ground scene circle is exposed by the second row of detectors of the TDI detector, and the charges generated by the exposure of the first and second rows are accumulated; the ground scene triangle is exposed by the first row of detectors of the TDI detector. At t3, the ground scene circle is exposed by the third row of detectors of the TDI detector, and the charges accumulated in the second row are accumulated with the charges exposed in the third row; the ground scene triangle is exposed by the second row of the TDI detector, and the charges generated by the exposure of the first and second rows are accumulated; the ground scene star is exposed by the first row of detectors of the TDI detector. By analogy, the actual imaging effect is formed, that is, each row of pixel data of the image is actually the result of the accumulation of charges of multiple rows of detectors on the TDI detector.

[0056] The imaging parameters of the satellite-borne high-resolution visible light camera mainly include exposure time, gain and integration level. After setting the exposure time to T, the integration level to L, and the gain to G, each row of detectors in the TDI detector is exposed according to T, the detector charge is accumulated according to the previous L rows, and then the whole is amplified according to the gain G. It can be seen that when the integration level is fixed to L, different exposure times or gains can be regarded as the overall amplification of the detector charge of the previous L rows on the TDI detector. When the exposure time and gain are fixed, different integration levels represent the accumulation of detector charges of different rows on the TDI detector.

[0057] If the relative radiation calibration coefficient is obtained when the imaging parameter is 1 (representing only one state), the relationship between the grayscale values ​​of image pixel i before and after relative radiation correction is as follows:

[0058]

[0059] in, Represents the gray value of image pixel i when the imaging parameter is 1 after relative radiation correction; K 1,i and B 1,i Represents the relative radiation calibration coefficient (slope, intercept) of image pixel i when the imaging parameter is 1, DN 1,i Represents the gray value of image pixel i when the imaging parameter is 1 before relative radiation correction.

[0060] Similarly, when the imaging parameter is x, we can also get:

[0061]

[0062] in, Represents the gray value of image pixel i when the imaging parameter is x after relative radiation correction; K x,i and B x,i Represents the relative radiation calibration coefficient (slope, intercept) of image pixel i when the imaging parameter is x, DN x,i It represents the gray value of image pixel i when the imaging parameter is x before relative radiation correction.

[0063] i) When the integral series is the same as L, there is an overall linear change relationship model for the grayscale value of the image pixel response between different exposure times or gains, that is:

[0064] DN x,i =a 1,i ×DN 1,i +a 2,i (3)

[0065] Among them, DN x,i It represents the gray value of pixel i in the image when the exposure time or gain is x (the accumulated value of the charge of the first L rows of detectors on the TDI detector), DN 1,i It represents the gray value of pixel i in the image when the exposure time or gain is 1 (the accumulated value of the charge of the first L rows of detectors on the TDI detector), a 1,i and a 2,i is the model coefficient of the response relationship between the gray value of pixel i and the exposure time or gain. The model coefficient is only related to the imaging parameters and does not change with the change of the detector response.

[0066] According to the principle that exposure time or gain is the overall amplification of the detector charge, substituting equation (3) into equation (2) yields:

[0067]

[0068] Based on this, we can decompose and deduce:

[0069]

[0070] The relationship between the relative radiation calibration coefficient when the gain or exposure time is x and the relative radiation calibration coefficient when the gain or exposure time is 1 is as follows:

[0071]

[0072] It can be seen that the slope of the relative radiation calibration coefficient does not change with the gain or exposure time, and the intercept changes with the gain and exposure time, and mainly depends on the coefficient a in the linear relationship model of the image pixel response between different exposure times or gains. 1,i and a 2,i .

[0073] ii) When the gain and exposure time are the same, there is no overall linear transformation of the image pixel response between different integration levels, but a cumulative integral relationship, that is:

[0074] DN x,i =DN 1,i +DN2′ ,i +DN3′ ,i +...+DN x ' ,i (7)

[0075] Among them, DN x,i It represents the gray value of pixel i in the image when the integration level is x (the accumulated value of the charge of the first x rows of detectors on the TDI detector), DN 1,i Indicates the gray value of pixel i in the image when the integration level is 1 (the accumulated value of the detector charge in the first row on the TDI detector), DN l ' ,i It represents the charge value of the lth row of detectors on the TDI detector when the integration order is l, l = 2…x.

[0076] Obviously, when the detector response on the TDI detector changes, it is difficult to decompose and derive the relationship expression between the relative radiation calibration coefficient when the integral order is x and the relative radiation calibration coefficient when the integral order is 1.

[0077] In some embodiments, the implementation method of determining the coefficients of the on-orbit relative radiation calibration coefficient relationship model based on the laboratory radiation calibration data of the spaceborne camera includes:

[0078] It should be noted that the laboratory radiation calibration data is the integrating sphere image data with different exposure times and gains obtained during the laboratory radiation calibration of the camera. Due to the vibration of the satellite launch process and the influence of the space environment, the detector response of the TDI detector will inevitably change over time, resulting in the failure of the laboratory relative radiation calibration coefficient, but the relationship between the grayscale changes caused by the exposure time and gain is unchanged. Therefore, using the integrating sphere image data with different exposure times and gains obtained during the laboratory radiation calibration of the camera, the coefficients of the relative radiation calibration coefficient relationship model under different imaging parameters can be accurately calculated.

[0079] i) Calculation of coefficients of the relative radiation calibration relationship model under different gains.

[0080] Generally speaking, when the camera development unit sets the gain level, it is divided into 8 levels. The relationship between the grayscale value of the response of the element i in the G2 level and the G1 level gain is:

[0081]

[0082] in, represents the average gray value of pixel i when the gain is G2, A represents the average gray value of pixel i when the gain is G1. i The gain of pixel i is increased by 1 level, which is usually set by the camera development unit; then

[0083]

[0084] In actual use, a group of integrating sphere image data with the same integration level, the same exposure time and different gains are selected, and the integrating sphere images corresponding to each gain are averaged to obtain a data table. The row direction represents the pixel number, and the column direction represents the gain level (generally 1, 2, 3...8). Each value in the table Represents detector i at gain G j The response value is

[0085] ii) Calculation of coefficients of the relative radiation calibration relationship model under different exposure times.

[0086] A group of integrating sphere image data with the same integration order, the same gain and different exposure time are selected. The integrating sphere images corresponding to each exposure time are averaged by column. The relationship between the grayscale value of each pixel response and the exposure time is obtained by least squares fitting as follows:

[0087]

[0088] in, Indicates that the exposure time is T j The average gray value of pixel i at time Tj represents the exposure time, b 1,i 、b 2,i is the model coefficient of the relationship between the grayscale value of pixel i and the exposure time.

[0089] It can be deduced that the relationship between the grayscale value of the response of the detector element i under the exposure time T2 and T1 is:

[0090]

[0091] in, represents the average gray value of pixel i when the exposure time is T2, represents the average gray value of pixel i when the exposure time is T1. Then, a 1,i =1,a 2,i =b 1,i ×(T x -T1).

[0092] It can be seen that the on-orbit relative radiation calibration coefficient relationship model finally obtained includes the relative radiation calibration coefficient relationship model between different gains and the relative radiation calibration coefficient relationship model between different exposure times.

[0093] Step 102 : determining a bright field uniform area and a dark field uniform area of ​​a spaceborne camera under a first imaging parameter among a plurality of imaging parameters.

[0094] As an implementation method, a method for determining the uniform bright and dark field areas of a spaceborne camera under a first imaging parameter among multiple imaging parameters is as follows: Figure 3 As shown, the following steps 201-204 are included:

[0095] Step 201: divide the dynamic range of the spaceborne camera into multiple linear regions.

[0096] It should be noted that the response of a general satellite-borne visible light camera is not completely linear in the entire dynamic range. There are nonlinear regions at the low and high ends. The entire dynamic range can be divided into multiple linear regions based on the camera response determined by laboratory calibration. Optionally, the entire dynamic range can be divided into three linear regions.

[0097] Step 202 : For each linear region in the plurality of linear regions, a bright uniform field and a dark uniform field are selected, and a bright uniform field image product and a dark uniform field image product under a first imaging parameter are obtained.

[0098] As an implementation method, bright and dark uniform fields are selected in each linear region from the global calibration field network database, and data information of the bright and dark uniform fields (including central longitude and latitude, altitude, size, etc.) is obtained; based on this, a calibration task is planned for a satellite-borne high-resolution visible light camera to obtain large-area bright and dark uniform field image products under the same imaging parameters (same integral series, exposure time and gain), and the large-area bright and dark uniform field image products include image data, metadata and RPC (Rational Polynomial Coefficient) information.

[0099] Step 203: Based on the data information of the bright and dark uniform fields, determine the row range of the uniformity evaluation area in the bright and dark uniform field images.

[0100] As an implementation method, the position (row and column number) of the uniform field in the image is located according to the central longitude and latitude of the bright and dark uniform fields and the altitude, combined with the RPC information; the row range of the uniformity evaluation area is calculated and determined according to the height of the bright and dark uniform fields and the spatial resolution of the camera:

[0101]

[0102] Among them, row represents the row range of the uniformity evaluation area, r c Indicates the row number of the uniform field in the image, Field H represents the height of the uniform field, and R represents the camera spatial resolution.

[0103] Step 204, determine the target image area corresponding to the row range of the uniformity evaluation area in the bright and dark uniform field image products, divide the target image area into multiple full-width sliding evaluation windows, and determine the bright and dark field uniform areas of the spaceborne camera under the first imaging parameter based on the uniformity of each full-width sliding evaluation window.

[0104] As an implementation method, the full-width sliding evaluation window is divided, and the window width includes all detectors, such as Figure 4 The height of the window shown can generally be set to 20. The window is slid from top to bottom, and the uniformity of each window is calculated. The window with the minimum uniformity will be automatically selected, that is, it will be determined as the bright and dark field uniform area of ​​the spaceborne camera for the calculation of the relative radiation calibration coefficient.

[0105]

[0106] Among them, U i represents the uniformity of window i, σ i represents the grayscale standard deviation of window i, Represents the grayscale average of window i.

[0107] Step 103: Based on the bright field uniform area and the dark field uniform area, an on-orbit relative radiation calibration coefficient under the first imaging parameter is obtained.

[0108] As an implementation method, the average grayscale value of the bright field uniform area and the dark field uniform area and the grayscale column mean of each detector are obtained to obtain a group of equations; the group of equations is solved to obtain the on-orbit relative radiation calibration coefficient under the first imaging parameter.

[0109] Exemplarily, based on the automatic selection of the optimal uniform area of ​​the bright and dark uniform fields, the average grayscale value of the bright and dark field uniform areas and the grayscale column mean of each detector are calculated to obtain the following set of equations:

[0110]

[0111] in, Indicates the average gray value of the bright field uniform area, DN H,i represents the gray column mean of pixel i in the bright field uniform area, is the average gray value of the uniform dark field area, DN L,i is the gray column mean of detector i in the dark field uniform area, K i is the slope of the relative radiation calibration coefficient of detector i, B i is the intercept of the relative radiometric calibration coefficient of detector i.

[0112] Solve the above equations to obtain the relative radiation calibration coefficient.

[0113] It should be noted that after obtaining the relative radiation calibration coefficient, it is still necessary to verify whether the relative radiation calibration coefficient is valid.

[0114] In some embodiments, a method for verifying whether a relative radiation calibration coefficient is valid includes:

[0115] According to the on-orbit relative radiation calibration coefficient, relative radiation correction is performed on other uniform scene images and complex scene images that match their imaging parameters. After correction, the longitudinal stripes and uneven brightness on the images are effectively eliminated, which means that the obtained on-orbit relative radiation calibration coefficient is valid.

[0116] Therefore, step 102 and step 103 use the uniform field method to achieve rapid acquisition of relative radiation calibration coefficients under certain imaging parameters.

[0117] Step 104 : Based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the first imaging parameter, the on-orbit relative radiation calibration coefficient under other imaging parameters is obtained.

[0118] After automatically acquiring the on-orbit relative radiation calibration coefficient under the first imaging parameter, according to the constructed on-orbit relative radiation calibration coefficient relationship model (including the relative radiation calibration coefficient relationship model between different gains and the relative radiation calibration coefficient relationship model between different exposure times), the exposure time can be fixed to deduce the on-orbit relative radiation calibration coefficient under different gains, or the gain can be fixed to deduce the on-orbit relative radiation calibration coefficient with different exposure times. The specific deduction method is as follows: Figure 5 shown.

[0119] By deduction, after obtaining the on-orbit relative radiation calibration coefficients under other imaging parameters, the obtained on-orbit relative radiation calibration coefficients can be verified for validity. The verification method is as follows:

[0120] The on-orbit relative radiation calibration coefficient under a certain imaging parameter is used to perform relative radiation correction on other uniform scene images and complex scene images that match the imaging parameters. The longitudinal stripes and uneven brightness on the images are effectively eliminated after correction, indicating that the deduced on-orbit relative radiation calibration coefficient is effective. The following mean-row standard deviation method can be used to evaluate the relative radiation calibration accuracy of the uniform scene images after correction.

[0121]

[0122] Where RCP represents the relative radiometric calibration precision, N represents the total number of detectors, It represents the average gray value of the pixels in the i-th column of the uniform area of ​​the image after correction. It is the average gray value of the uniform area of ​​the corrected image.

[0123] The method for obtaining the on-orbit relative radiation calibration coefficient of the satellite camera in the embodiment of the present application obtains an on-orbit relative radiation calibration coefficient relationship model that characterizes the relationship between the on-orbit relative radiation calibration coefficients under different imaging parameters, determines the bright field uniform area and the dark field uniform area of ​​the satellite camera under a certain imaging parameter; and based on the bright field uniform area and the dark field uniform area, obtains the on-orbit relative radiation calibration coefficient under the imaging parameter; based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the imaging parameter, obtains the on-orbit relative radiation calibration coefficient under other imaging parameters, realizes the automatic calculation of the on-orbit relative radiation calibration coefficient of the satellite camera, and can realize the deduction of the on-orbit relative radiation calibration parameters under different imaging parameters, improves the acquisition efficiency of the on-orbit relative radiation calibration coefficient of the satellite-borne visible light camera, thereby realizing the rapid on-orbit relative radiation calibration of the high-resolution visible light camera under multiple satellites and multiple imaging parameters, and solves the problem in the related art that the on-orbit relative radiation calibration efficiency of the high-resolution visible light camera in the current large-scale star cluster system is low, and it is difficult to meet the application needs of rapid calibration under multiple satellites and multiple imaging parameters. In addition, the uniform field method is used to quickly obtain the relative radiation calibration coefficient under a certain imaging parameter, and the calibration efficiency is improved by the automatic selection method of uniform areas. This method is used for satellite-borne high-resolution visible light cameras to obtain effective on-orbit relative radiation calibration coefficients and good correction effects.

[0124] In order to clearly illustrate the above embodiment, specific examples are now provided for illustration.

[0125] The following uses a satellite-borne high-resolution visible light camera laboratory and on-orbit earth observation data as an example to illustrate how the present invention achieves automatic calculation and deduction of its on-orbit relative radiation calibration coefficient.

[0126] Using the camera laboratory integrating sphere calibration data, a relationship model between the grayscale values ​​of the detector response under different exposure times (1, 5, 10, 15, 20, 25, 30ms) was established, as shown in Figure 6a and Figure 6b As shown. Figure 6a and Figure 6b It can be seen that the grayscale value of the camera detector response is proportional to the exposure time, with a good linear relationship and a Pearson correlation coefficient of 0.999. The relationship between the grayscale value of the edge and center detectors and the exposure time obtained by linear fitting is shown in Table 1. It can be seen that the response relationship between the edge and center detectors is slightly different, mainly due to the different transmittance of the center and edge of the optical lens, which will be eliminated by the flat field during the relative radiation calibration process.

[0127] Table 1: Relationship between the grayscale value of the detector response and the exposure time (model parameters)

[0128]

[0129] Using the camera laboratory integrating sphere calibration data, a relationship model between the grayscale values ​​of the detector response under different gains is established, such as Figure 7 The figure shows the relationship between the grayscale value of the detector response and the gain under 3-level gain and 4-level gain. The horizontal axis represents the pixel number and the vertical axis represents the grayscale relationship, i.e., a1. It can be seen that the a1 values ​​of different detectors are not much different, the difference is in the third decimal place, and the average value is about 1.1, which is in line with the 1.1 set by the camera development unit. n relation.

[0130] The results of automatic selection of bright and dark field uniform areas are as follows Figure 8a and Figure 8b As shown, the bright field is a desert image, and the dark field is an ocean image. In order to illustrate the relationship between the selection window and the uniformity curve, the sliding window moves from top to bottom in the image. The left side of each figure shows the relationship between the uniformity of the sliding window and the row number for each row from top to bottom, and the right side shows the position of the window with the minimum uniformity in the image that is automatically calculated and marked by the program. It can be seen that the row number of the window with the minimum uniformity corresponds to the position in the image, indicating that the automatic selection method of uniform areas is effective.

[0131] Figure 9a This is an integrating sphere image with an exposure time of 20ms. Due to the inconsistency of the detector response, there are many longitudinal stripes and uneven brightness in the image. The relative radiation calibration coefficient between different exposure times is deduced from the relative radiation calibration coefficient of 10ms exposure time, and the integrating sphere image with an exposure time of 20ms is corrected. The results are shown in the figure. Figure 9b It can be seen that the stripes and uneven brightness in the image are effectively eliminated, and the integrating sphere image becomes more uniform, indicating the correctness of the established model for deducing the relationship between relative radiation calibration coefficients between different gains.

[0132] The relative radiation calibration coefficients under three-gain levels were calculated by using the uniform field images of desert and ocean acquired on orbit. The relative radiation calibration coefficients under three-gain levels were deduced from the relative radiation calibration coefficients under three-gain levels according to the established relationship between relative radiation calibration coefficients between different gains. The relative radiation calibration coefficients under four-gain levels were calculated for another desert image acquired under four-gain levels. Fig.10a ) is used for correction. The correction effect is as follows Fig.10c As shown, Fig.10b The 4-gain laboratory relative radiation calibration coefficient is used to Fig.10a Correction effect. It can be seen that there are stripes and uneven brightness in the desert image before correction, which affects the identification of desert texture and details. The image is corrected using the relative radiation calibration coefficient deduced on-orbit, which can effectively eliminate the stripes and uneven brightness. The laboratory relative radiation calibration coefficient is no longer applicable, and the correction effect is not as good as the on-orbit relative radiation calibration coefficient.

[0133] In order to implement the above-mentioned embodiment, the present application also proposes a device for acquiring an on-orbit relative radiation calibration coefficient of a space-borne camera. Fig.11 A schematic diagram of the structure of a device for acquiring the on-orbit relative radiation calibration coefficient of a space-borne camera provided in an embodiment of the present application. Fig.11 As shown, the device for acquiring the on-orbit relative radiation calibration coefficient of the spaceborne camera may include: a model acquisition module 301, a region determination module 302, a coefficient calculation module 303 and a coefficient deduction module 304.

[0134] The model acquisition module 301 is used to acquire an on-orbit relative radiation calibration coefficient relationship model, and the on-orbit relative radiation calibration coefficient relationship model is used to characterize the relationship between the on-orbit relative radiation calibration coefficients under different imaging parameters;

[0135] The region determination module 302 is used to determine a bright field uniform region and a dark field uniform region of the spaceborne camera under a first imaging parameter;

[0136] A coefficient calculation module 303 is used to obtain an on-orbit relative radiation calibration coefficient under a first imaging parameter based on a bright field uniform area and a dark field uniform area;

[0137] The coefficient deduction module 304 is used to obtain the on-orbit relative radiation calibration coefficient under other imaging parameters based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the first imaging parameter.

[0138] Furthermore, in a possible implementation of the embodiment of the present application, the model acquisition module 301 is specifically used to:

[0139] Based on the imaging parameter adjustment principle and linear decomposability principle of the spaceborne camera, a model for the relationship between the on-orbit relative radiation calibration coefficients is constructed.

[0140] Based on the laboratory radiation calibration data of the spaceborne camera, the coefficients of the on-orbit relative radiation calibration coefficient relationship model are determined.

[0141] Further, in a possible implementation of the embodiment of the present application, the imaging parameters include exposure time, gain and integration series. When the model acquisition module 301 constructs the on-orbit relative radiation calibration coefficient relationship model, it is specifically used to:

[0142] The relative radiation calibration coefficient is obtained when the imaging parameter is 1, and the relationship between the grayscale values ​​of image pixel i before and after relative radiation correction is as follows:

[0143]

[0144] in, Represents the gray value of image pixel i when the imaging parameter is 1 after relative radiation correction; K 1,i and B 1,i Represents the slope and intercept of the relative radiation calibration coefficient of image pixel i when the imaging parameter is 1; DN 1,i Represents the gray value of image pixel i when the imaging parameter is 1 before relative radiation correction;

[0145] The relative radiation calibration coefficient is obtained when the imaging parameter is x, and the relationship between the grayscale values ​​of the image pixel i before and after the relative radiation correction is obtained as follows:

[0146]

[0147] in, Represents the gray value of image pixel i when the imaging parameter is x after relative radiation correction; K x,i and B x,i Represents the slope and intercept of the relative radiation calibration coefficient of image pixel i when the imaging parameter is x, DN x,i It represents the gray value of image pixel i when the imaging parameter is x before relative radiation correction;

[0148] 1) When the integral series is the same as L, there is an overall linear change relationship model for the grayscale value of the image pixel response between different exposure times or gains, that is:

[0149] DN x,i =a 1,i ×DN 1,i +a 2,i (3)

[0150] Among them, DN x,i Indicates the gray value of pixel i in the image when the exposure time or gain is x, DN 1,i Indicates the gray value of pixel i in the image when the exposure time or gain is 1, a 1,i and a 2,i is the model coefficient of the gray value of pixel i in response to exposure time or gain. This model coefficient is only related to the imaging parameters and does not change with the change of the detector response;

[0151] According to the principle that exposure time or gain is the overall amplification of the detector charge, substituting equation (3) into equation (2) yields:

[0152]

[0153] Based on this, the following is deduced:

[0154]

[0155] The relationship between the relative radiation calibration coefficient when the gain or exposure time is x and the relative radiation calibration coefficient when the gain or exposure time is 1 is as follows:

[0156]

[0157] The slope of the relative radiation calibration coefficient in the on-orbit relative radiation calibration coefficient relationship model does not change with the gain or exposure time, and the intercept changes with the gain and exposure time, and depends on the coefficient a in the linear relationship model of the image pixel response between different exposure times or gains. 1,i and a 2,i ;

[0158] 2) When the gain and exposure time are the same, there is no overall linear transformation of the image pixel response between different integration levels, but a cumulative integral relationship, that is:

[0159] DN x,i =DN 1,i +DN2′ ,i +DN3′ ,i +...+DN x ' ,i (7)

[0160] Among them, DN x,i Indicates the gray value of pixel i in the image when the integral level is x, DN 1,i Indicates the gray value of pixel i in the image when the integral level is 1, DN l ' ,i It represents the charge value of the lth row of detectors on the TDI detector when the integration order is l, l = 2…x.

[0161] Further, in a possible implementation of the embodiment of the present application, the laboratory radiation calibration data includes integrating sphere image data with different exposure times and different gains. When the model acquisition module 301 determines the coefficients of the on-orbit relative radiation calibration coefficient relationship model based on the laboratory radiation calibration data of the spaceborne camera, it is used to:

[0162] i) Calculation of coefficients of relative radiation calibration relationship model under different gains:

[0163] The relationship between the grayscale values ​​of the detector i response when the camera is at gain level G2 and G1 is:

[0164]

[0165] in, represents the average gray value of pixel i when the gain is G2, A represents the average gray value of pixel i when the gain is G1. i The gain of pixel i is increased by 1 level, then

[0166] Select a group of integrating sphere image data with the same integration level, the same exposure time and different gains, and perform column averaging on the integrating sphere images corresponding to each gain to obtain a data table. The row direction represents the pixel number, and the column direction represents the gain level. Each value in the table Represents detector i at gain G j The response value under

[0167] ii) Calculation of coefficients of relative radiation calibration relationship model under different exposure times:

[0168] A group of integrating sphere image data with the same integration order, the same gain and different exposure time are selected. The integrating sphere images corresponding to each exposure time are averaged by column. The relationship between the grayscale value of each pixel response and the exposure time is obtained by least squares fitting as follows:

[0169]

[0170] in, Indicates that the exposure time is T j The average gray value of pixel i at time T j represents the exposure time, b 1,i 、b 2,i is the model coefficient of the relationship between the grayscale value of pixel i and the exposure time;

[0171] The relationship between the grayscale value of the response of the detector element i at exposure time T2 and T1 is:

[0172]

[0173] in, represents the average gray value of pixel i when the exposure time is T2, represents the average gray value of pixel i when the exposure time is T1. Then, a 1,i =1,a 2,i =b 1,i ×(T x -T1).

[0174] Furthermore, in a possible implementation of the embodiment of the present application, the region determination module 302 is specifically configured to:

[0175] Divide the dynamic range of the spaceborne camera into multiple linear regions;

[0176] For each linear region in the plurality of linear regions, a bright uniform field and a dark uniform field are selected, and a bright uniform field image product and a dark uniform field image product under a first imaging parameter are obtained;

[0177] Based on the data information of the bright and dark uniform fields, determining the row range of the uniformity evaluation area in the bright and dark uniform field images;

[0178] Determine the target image area corresponding to the row range of the uniformity evaluation area in the bright and dark uniform field image products, divide the target image area into multiple full-width sliding evaluation windows, and determine the bright and dark field uniform areas of the spaceborne camera under the first imaging parameter based on the uniformity of each full-width sliding evaluation window.

[0179] Further, in a possible implementation of the embodiment of the present application, the coefficient calculation module 303 is specifically used to:

[0180] Obtain the average grayscale value of the bright field uniform area and the dark field uniform area and the grayscale column mean of each detector to obtain the equation group;

[0181] Solving the equation group, obtaining the on-orbit relative radiation calibration coefficient under the first imaging parameter;

[0182] The effectiveness of the on-orbit relative radiation calibration coefficient under the first imaging parameter is verified to obtain the on-orbit relative radiation calibration coefficient under the first imaging parameter that has passed the verification.

[0183] It should be noted that the above explanation of the embodiment of the method for obtaining the on-orbit relative radiation calibration coefficient of the space-borne camera is also applicable to the device for obtaining the on-orbit relative radiation calibration coefficient of the space-borne camera of this embodiment, and will not be repeated here.

[0184] In order to implement the above embodiment, the present application also proposes an electronic device. Fig.12 , Fig.12 Schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Fig.12 As shown, the electronic device 1200 includes: a processor 1201, and a memory 1202 communicatively connected to the processor 1201; the memory 1202 stores computer-executable instructions; the processor 1201 executes the computer-executable instructions stored in the memory to implement the method provided in the aforementioned embodiment.

[0185] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0186] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0187] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0188] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0189] The present application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0190] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0191] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0192] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0193] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0194] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0195] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0196] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0197] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for obtaining an on-orbit relative radiation calibration coefficient of a spaceborne camera, characterized in that: The following steps are involved: Acquire an on-orbit relative radiation calibration coefficient relationship model, where the on-orbit relative radiation calibration coefficient relationship model is used to characterize the relationship between on-orbit relative radiation calibration coefficients under different imaging parameters; Determine a bright field uniform area and a dark field uniform area of ​​the spaceborne camera under a first imaging parameter; Based on the bright field uniform area and the dark field uniform area, acquiring an on-orbit relative radiation calibration coefficient under the first imaging parameter; Based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the first imaging parameter, the on-orbit relative radiation calibration coefficient under other imaging parameters is obtained.

2. The method according to claim 1, characterized in that The method of obtaining the on-orbit relative radiation calibration coefficient relationship model comprises: Based on the imaging parameter adjustment principle and linear decomposability principle of the on-board camera, the on-orbit relative radiation calibration coefficient relationship model is constructed; Based on the laboratory radiation calibration data of the spaceborne camera, the coefficients of the on-orbit relative radiation calibration coefficient relationship model are determined.

3. The method according to claim 2, characterized in that The imaging parameters include exposure time, gain and integration series. The imaging parameter adjustment principle based on the spaceborne camera and the linear decomposability principle are used to construct the on-orbit relative radiation calibration coefficient relationship model; including: The relative radiation calibration coefficient is obtained when the imaging parameter is 1, and the relationship between the grayscale values ​​of image pixel i before and after relative radiation correction is as follows: in, Represents the gray value of image pixel i when the imaging parameter is 1 after relative radiation correction; K 1,i and B 1,i Represents the slope and intercept of the relative radiation calibration coefficient of image pixel i when the imaging parameter is 1; DN 1,i Represents the gray value of image pixel i when the imaging parameter is 1 before relative radiation correction; The relative radiation calibration coefficient is obtained when the imaging parameter is x, and the relationship between the grayscale values ​​of the image pixel i before and after the relative radiation correction is obtained as follows: in, Represents the gray value of image pixel i when the imaging parameter is x after relative radiation correction; K x,i and B x,i Represents the slope and intercept of the relative radiation calibration coefficient of image pixel i when the imaging parameter is x, DN x,i It represents the gray value of image pixel i when the imaging parameter is x before relative radiation correction; 1) When the integral series is the same as L, there is an overall linear change relationship model for the grayscale value of the image pixel response between different exposure times or gains, that is: DN x,i =a 1,i ×DN 1,i +a 2,i (3) Among them, DN x,i Indicates the gray value of pixel i in the image when the exposure time or gain is x, DN 1,i Indicates the gray value of pixel i in the image when the exposure time or gain is 1, a 1,i and a 2,i is the model coefficient of the gray value of pixel i in response to exposure time or gain. This model coefficient is only related to the imaging parameters and does not change with the change of the detector response; According to the principle that exposure time or gain is the overall amplification of the detector charge, substituting equation (3) into equation (2) yields: Based on this, the following is deduced: The relationship between the relative radiation calibration coefficient when the gain or exposure time is x and the relative radiation calibration coefficient when the gain or exposure time is 1 is as follows: The slope of the relative radiation calibration coefficient in the on-orbit relative radiation calibration coefficient relationship model does not change with the gain or exposure time, the intercept changes with the gain and exposure time, and depends on the coefficient a in the linear relationship model of the image pixel response between different exposure times or gains. 1,i and a 2,i ; 2) When the gain and exposure time are the same, there is no overall linear transformation of the image pixel response between different integration levels, but a cumulative integral relationship, that is: DN x,i =DN 1,i +DN2′ ,i +DN3′ ,i +...+DN x ′ ,i (7) Among them, DN x,i Indicates the gray value of pixel i in the image when the integral level is x, DN 1,i Indicates the gray value of pixel i in the image when the integral level is 1, DN l ' ,i It represents the charge value of the lth row of detectors on the TDI detector when the integration order is l, l = 2…x.

4. The method according to claim 3, characterized in that The laboratory radiation calibration data includes integrating sphere image data with different exposure times and different gains, and the coefficients of the on-orbit relative radiation calibration coefficient relationship model are determined based on the laboratory radiation calibration data of the spaceborne camera; include: i) Calculation of coefficients of relative radiation calibration relationship model under different gains: The relationship between the grayscale values ​​of the detector i response when the camera is at gain level G2 and G1 is: in, represents the average gray value of pixel i when the gain is G2, A represents the average gray value of pixel i when the gain is G1. i The gain of pixel i is increased by 1 level, then Select a group of integrating sphere image data with the same integration level, the same exposure time and different gains, and perform column averaging on the integrating sphere images corresponding to each gain to obtain a data table. The row direction represents the pixel number, and the column direction represents the gain level. Each value in the table Represents detector i at gain G j The response value under ii) Calculation of coefficients of relative radiation calibration relationship model under different exposure times: A group of integrating sphere image data with the same integration order, the same gain and different exposure time are selected. The integrating sphere images corresponding to each exposure time are averaged by column. The relationship between the grayscale value of each pixel response and the exposure time is obtained by least squares fitting as follows: in, Indicates that the exposure time is T j The average gray value of pixel i at time T j represents the exposure time, b 1,i , b 2,i is the model coefficient of the relationship between the grayscale value of pixel i and the exposure time; The relationship between the grayscale value of the response of the detector element i at exposure time T2 and T1 is: in, represents the average gray value of pixel i when the exposure time is T2, represents the average gray value of pixel i when the exposure time is T1. Then, a 1,i =1, a 2,i =b 1,i ×(T x -T1).

5. The method according to claim 1, characterized in that The determining of the bright field uniform area and the dark field uniform area of ​​the spaceborne camera under the first imaging parameter comprises: Dividing the dynamic range of the spaceborne camera into a plurality of linear regions; For each linear region in the plurality of linear regions, selecting a bright uniform field and a dark uniform field, and obtaining a bright uniform field image product and a dark uniform field image product under a first imaging parameter; Based on the data information of the bright and dark uniform fields, determining the row range of the uniformity evaluation area in the bright and dark uniform field images; Determine a target image area corresponding to a row range of the uniformity evaluation area in the bright and dark uniform field image products, divide the target image area into a plurality of full-width sliding evaluation windows, and determine a bright field uniform area and a dark field uniform area of ​​the spaceborne camera under a first imaging parameter based on the uniformity of each of the full-width sliding evaluation windows.

6. The method according to claim 1, characterized in that The step of acquiring an on-orbit relative radiation calibration coefficient under the first imaging parameter based on the bright field uniform area and the dark field uniform area comprises: Obtaining the average grayscale value of the bright field uniform area and the dark field uniform area and the grayscale column mean of each detector to obtain a set of equations; Solving the equation group to obtain an on-orbit relative radiation calibration coefficient under a first imaging parameter; The effectiveness of the on-orbit relative radiation calibration coefficient under the first imaging parameter is verified to obtain the on-orbit relative radiation calibration coefficient under the first imaging parameter that passes the verification.

7. A device for obtaining the on-orbit relative radiation calibration coefficient of a space-borne camera, characterized in that: include: A model acquisition module, used to acquire an on-orbit relative radiation calibration coefficient relationship model, wherein the on-orbit relative radiation calibration coefficient relationship model is used to characterize the relationship between the on-orbit relative radiation calibration coefficients under different imaging parameters; An area determination module, used to determine a bright field uniform area and a dark field uniform area of ​​the spaceborne camera under a first imaging parameter; A coefficient calculation module, used for obtaining an on-orbit relative radiation calibration coefficient under the first imaging parameter based on the bright field uniform area and the dark field uniform area; A coefficient deduction module is used to obtain the on-orbit relative radiation calibration coefficient under other imaging parameters based on the on-orbit relative radiation calibration coefficient relationship model and the on-orbit relative radiation calibration coefficient under the first imaging parameter.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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