Method and device for obtaining on-orbit relative radiometric calibration coefficient of satellite-borne camera

Abstract

The application provides an on-orbit relative radiation calibration coefficient acquisition method and device of a satellite-borne camera. The method comprises the following steps: acquiring an on-orbit relative radiation calibration coefficient relationship model, wherein the on-orbit relative radiation calibration coefficient relationship model is used for representing the relationship between on-orbit relative radiation calibration coefficients under different imaging parameters; determining a bright field uniform area and a dark field uniform area of the satellite-borne camera under a first imaging parameter; acquiring the on-orbit relative radiation calibration coefficient under the first imaging parameter based on the bright field uniform area and the dark field uniform area; and acquiring 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, thereby solving the technical problem of low efficiency of on-orbit relative radiation calibration coefficient acquisition in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of space-borne cameras, and particularly relates to a method and device for obtaining on-orbit relative radiometric calibration coefficients of a space-borne camera, an electronic device and a storage medium. BACKGROUND

[0002] High-resolution visible light remote sensing images play an important role in the fields of map surveying and mapping, city planning, land use, environmental monitoring, military reconnaissance, etc., and bring huge economic and military benefits. A large number of high-resolution remote sensing satellites have been launched by countries around the world. With the progress of science and technology, satellite performance is continuously improved, and the cost of developing high-resolution visible light cameras is reduced. Ground observation has also changed from the traditional single-satellite mode to a 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 high-resolution visible light cameras during on-orbit operation are of great significance in target identification and quantitative remote sensing data application. Whether it is a visible light load or an infrared load, due to factors such as inconsistent detector responses, changes in electronic gain and offset, optical system degradation, and focal plane particle contamination, there are longitudinal stripes, bands or uneven brightness and darkness in the acquired remote sensing images. For target identification applications, these stripes and bands reduce image quality, making it difficult to accurately identify targets from geometric and texture features. For quantitative remote sensing data applications, stripes and bands can increase absolute radiometric calibration errors and affect the accuracy of ground surface parameter (reflectivity, temperature, etc.) inversion. Therefore, on-orbit relative radiometric calibration and correction of high-resolution visible light cameras are needed to eliminate stripes, bands and uneven brightness and darkness in remote sensing images, and to improve image quality and quantitative remote sensing data levels.

[0004] In the traditional single-satellite mode, on-orbit relative radiometric calibration is usually achieved by histogram matching or uniform field method. The histogram matching method needs to statistically analyze a large amount of data to obtain an effective on-orbit relative radiometric calibration coefficient lookup table, and the calibration period is relatively long. The uniform field method can only quickly obtain on-orbit relative radiometric calibration coefficients under a certain imaging parameter, and needs to manually select uniform areas. Obviously, these two methods cannot meet the need for rapid on-orbit relative radiometric calibration of multiple satellites in a short period under the constellation mode.

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

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

[0007] To this end, a first object of the present application is to provide a method for obtaining an on-orbit relative radiometric calibration coefficient of a spaceborne camera, so as to improve the on-orbit relative radiometric calibration efficiency of a spaceborne high-resolution visible light camera and solve the problem of low on-orbit relative radiometric calibration efficiency of a high-resolution visible light camera in a current large-scale satellite system, which cannot meet the needs of fast calibration application under multiple satellites and multiple imaging parameters.

[0008] A second object of the present application is to provide an apparatus for obtaining an on-orbit relative radiometric calibration coefficient of a spaceborne camera.

[0009] A third object of the present application is to provide an electronic device.

[0010] A fourth object 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 objects, a first aspect of the present application provides a method for obtaining an on-orbit relative radiometric calibration coefficient of a spaceborne camera, comprising:

[0013] obtaining an on-orbit relative radiometric calibration coefficient relationship model, the on-orbit relative radiometric calibration coefficient relationship model being used to represent the relationship between on-orbit relative radiometric 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] obtaining an on-orbit relative radiometric calibration coefficient under the first imaging parameter based on the bright field uniform area and the dark field uniform area;

[0016] obtaining on-orbit relative radiometric calibration coefficients under other imaging parameters based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficient under the first imaging parameter.

[0017] To achieve the above objects, a second aspect of the present application provides an apparatus for obtaining an on-orbit relative radiometric calibration coefficient of a spaceborne camera, comprising:

[0018] a model obtaining module, configured to obtain an on-orbit relative radiometric calibration coefficient relationship model, the on-orbit relative radiometric calibration coefficient relationship model being used to represent the relationship between on-orbit relative radiometric calibration coefficients under different imaging parameters;

[0019] a region determining module, configured 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, configured to acquire the on-orbit relative radiometric calibration coefficient under the first imaging parameter based on the bright-field uniform area and the dark-field uniform area;

[0021] a coefficient derivation module, configured to acquire the on-orbit relative radiometric calibration coefficient under other imaging parameters based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficient under the first imaging parameter.

[0022] To achieve the above object, the third aspect of the present application provides an electronic device, comprising: a processor, and a memory connected with the processor in communication; the memory stores computer execution instructions; and the processor executes the computer execution instructions stored in the memory to implement the method of the first aspect.

[0023] To achieve the above object, the fourth aspect of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the method of the first aspect.

[0024] To achieve the above object, the fifth aspect of the present application provides a computer program product, comprising a computer program, which is executed by a processor to implement the method of the first aspect.

[0025] The method, device, electronic device and storage medium provided by the present application for acquiring the on-orbit relative radiometric calibration coefficient of a satellite-borne camera acquire an on-orbit relative radiometric calibration coefficient relationship model representing the relationship between the on-orbit relative radiometric calibration coefficients under different imaging parameters, determine the bright-field uniform area and the dark-field uniform area of the satellite-borne camera under a certain imaging parameter, and acquire the on-orbit relative radiometric calibration coefficient under the imaging parameter based on the bright-field uniform area and the dark-field uniform area; and acquire the on-orbit relative radiometric calibration coefficient under other imaging parameters based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficient under the imaging parameter, which realizes the automatic calculation of the on-orbit relative radiometric calibration coefficient of the satellite-borne camera, and can realize the derivation of the on-orbit relative radiometric calibration coefficient under different imaging parameters, improves the acquisition efficiency of the on-orbit relative radiometric calibration coefficient of the satellite-borne visible light camera, and thus can realize the rapid on-orbit relative radiometric calibration of the high-resolution visible light camera under multiple satellites and multiple imaging parameters, and solves the problem of low on-orbit relative radiometric calibration efficiency of the high-resolution visible light camera in the current large-scale satellite system, which is difficult to meet the needs of rapid calibration application under multiple satellites and multiple imaging parameters. In addition, the uniform field method is used to realize the rapid acquisition of the relative radiometric calibration coefficient under a certain imaging parameter, and the uniform area automatic selection method is used to improve the calibration efficiency.

[0026] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those having ordinary skill in the art upon examination of the following or can be learned from practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0027] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the appended drawings.

[0028] Figure 1 A flowchart of a method for obtaining an on-orbit relative radiometric calibration coefficient of a spaceborne camera according to an embodiment of the present application;

[0029] Figure 2 A schematic diagram of the working principle of a TDI detector according to an embodiment of the present application;

[0030] Figure 3 A flowchart of a method for determining a bright field uniform region and a dark field uniform region according to an embodiment of the present application;

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

[0032] Figure 5 A schematic diagram of derivation of on-orbit relative radiometric calibration coefficients for different imaging parameters according to an embodiment of the present application;

[0033] Figure 6a A graph of the relationship between the response gray value of an edge detector element and exposure time according to an embodiment of the present application;

[0034] Figure 6b A graph of the relationship between the response gray value of a center detector element and exposure time according to an embodiment of the present application;

[0035] Figure 7 A graph of the relationship between the response gray value of a detector element and gain at 3-gain and 4-gain according to an embodiment of the present application;

[0036] Figure 8a A result of automatic selection of a bright field uniform region according to an embodiment of the present application;

[0037] Figure 8b A result of automatic selection of a dark field uniform region according to an embodiment of the present application;

[0038] Figure 9a An integrating sphere image with an exposure time of 20 ms according to an embodiment of the present application;

[0039] Figure 9b An effect image after relative radiometric correction of an integrating sphere image with an exposure time of 20 ms using a 20 ms relative radiometric calibration coefficient derived at 10 ms according to an embodiment of the present application;

[0040] Figure 10a A 4-gain desert image provided by an embodiment of the present application;

[0041] Figure 10b An effect image after relative radiation correction of a 4-gain desert image by a 4-gain laboratory relative radiation calibration coefficient provided by an embodiment of the present application;

[0042] Figure 10c An effect image after relative radiation correction of a desert image by a 4-gain relative radiation calibration coefficient deduced from a 3-gain provided by an embodiment of the present application.

[0043] Figure 11 A block diagram of an on-orbit relative radiation calibration coefficient acquisition device of a satellite-borne camera provided by an embodiment of the present application;

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

[0045] The embodiments of the present application are described in detail below with reference to the accompanying drawings. The embodiments of the present application, which are shown by way of example in the accompanying drawings, are intended to explain the present application and cannot be understood as a limitation of the present application.

[0046] The on-orbit relative radiation calibration coefficient acquisition method, device and equipment of a satellite-borne camera of an embodiment of the present application are described below with reference to the accompanying drawings.

[0047] Figure 1 A flowchart of an on-orbit relative radiation calibration coefficient acquisition method of a satellite-borne camera provided by an embodiment of the present application.

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

[0049] As shown in Figure 1 the on-orbit relative radiation calibration coefficient acquisition method of a satellite-borne camera includes the following steps 101-104:

[0050] Step 101, acquiring an on-orbit relative radiation calibration coefficient relationship model under a plurality of imaging parameters. The on-orbit relative radiation calibration coefficient relationship model is used to represent the relationship between the on-orbit relative radiation calibration coefficients under a plurality of imaging parameters.

[0051] As an implementation manner, a method for obtaining an on-orbit relative radiometric calibration coefficient relationship model under multiple imaging parameters comprises the following steps:

[0052] Based on the imaging parameter adjustment principle and the linear disassemblable principle of the spaceborne camera, an on-orbit relative radiometric calibration coefficient relationship model under multiple imaging parameters is constructed.

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

[0054] In some embodiments, the implementation manner for constructing an on-orbit relative radiometric calibration coefficient relationship model under multiple imaging parameters based on the imaging parameter adjustment principle and the linear disassemblable principle of the spaceborne camera comprises the following contents:

[0055] First of all, it needs to be pointed out that a general spaceborne high-resolution visible light camera performs imaging through linear array push-broom imaging, adopts a Time Delay Integration (TDI) technology to improve sensitivity and signal-to-noise ratio, and acquires high-quality images. The working principle of a TDI detector is shown in FIG. 1. Figure 2 The TDI detector is actually a surface array detector with a column number much larger than a row number. The column number of the detector is consistent with the column number of an image, and the row number of the detector represents the number of integrable levels. For example, a ground scene is marked with a star, a triangle and a circle. The camera moves forward with the satellite to perform imaging. At t1, the circle of the ground scene is exposed to the first row of the TDI detector. At t2, the circle of the ground scene is exposed to the second row of the TDI detector, and the charges generated by the exposure of the circle to the first and second rows are accumulated. The triangle of the ground scene is exposed to the first row of the TDI detector. At t3, the circle of the ground scene is exposed to the third row of the TDI detector, and the charges accumulated by the second row are accumulated with the exposure charges of the third row. The triangle of the ground scene is exposed to the second row of the TDI detector, and the charges generated by the exposure of the triangle to the first and second rows are accumulated. The star of the ground scene is exposed to the first row of the TDI detector. In this way, the actual imaging effect is formed, that is, each row of pixel data of an image is actually the result of the charge accumulation of multiple rows of the TDI detector.

[0056] The imaging parameters of the spaceborne high-resolution visible light camera mainly include an exposure time, a gain and an integration level. After the exposure time is set as T, the integration level is set as L and the gain is set as G, each row of the TDI detector is exposed to T, the charge accumulation of the first L rows of the TDI detector is performed, and then the whole is amplified by the gain G. As can be seen, when the integration level is fixed as L, different exposure times or gains can be regarded as the overall amplification of the charge of the first L rows of the TDI detector. When the exposure time and the gain are fixed, different integration levels represent the accumulation of the charges of different row numbers of the TDI detector.

[0057] If the relative radiometric calibration coefficient of imaging parameter 1 (only indicating one state) is obtained, the relationship between the image pixel i gray value before and after the relative radiometric correction is as follows:

[0058]

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

[0060] Similarly, when the imaging parameter is x, the same can be obtained:

[0061]

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

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

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

[0065] wherein, DN x,i represents the gray value of image pixel i when the exposure time or gain is x (the charge accumulation value of the first L rows of detection elements on the TDI detector), DN 1,i represents the gray value of image pixel i when the exposure time or gain is 1 (the charge accumulation value of the first L rows of detection elements on the TDI detector), a 1,i and a 2,i are the gray value response relationship model coefficients of image pixel i with the exposure time or gain, which are only related to the imaging parameter and do not change with the change of the detection element response.

[0066] According to the principle that the exposure time or gain is the overall amplification of the charge of the detection element, formula (3) is brought into formula (2) to have:

[0067]

[0068] Accordingly, the following expression can be derived:

[0069]

[0070] The relationship between the relative radiometric calibration coefficient when the gain or exposure time is x and the relative radiometric 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 radiometric calibration coefficient does not change with the change of the gain or exposure time, the intercept changes with the change of 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, the image pixel response between different integration orders does not have an overall linear transformation, but a cumulative integration relationship, that is:

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

[0075] where DN x,i represents the gray value of pixel i in the image when the integration order is x (the cumulative value of the charge of the first x rows of the pixel on the TDI detector), DN 1,i represents the gray value of pixel i in the image when the integration order is 1 (the cumulative value of the charge of the first row of the pixel on the TDI detector), DN l ' ,i represents the charge value of the lth row of the pixel on the TDI detector when the integration order is 1, and l = 2…x.

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

[0077] In some embodiments, the implementation of the coefficient of the on-orbit relative radiometric calibration coefficient relationship model is determined based on the laboratory radiometric calibration data of the satellite-borne camera, including:

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

[0079] i) Coefficient calculation of relative radiation calibration relationship model under different gains.

[0080] Generally, when the camera development unit sets the gain level, it is divided into 8 levels. The gray level relationship of pixel i under G2 and G1 gain is:

[0081]

[0082] wherein, represents the average gray level of pixel i under gain G2, represents the average gray level of pixel i under gain G1, A i is the amplification factor of pixel i gain increase by 1 level, which is generally set by the camera development unit; then

[0083]

[0084] In actual use, a set of integral sphere image data with the same integral number, the same exposure time and different gains is selected. For each gain corresponding integral sphere image, column average is performed to obtain a data table. The row direction represents the pixel number, the column direction represents the gain level (generally 1, 2, 3…8), and each value in the table represents the response value of pixel i under gain G j , then

[0085] ii) Coefficient calculation of relative radiation calibration relationship model under different exposure times.

[0086] A set of integral sphere image data with the same integral number, the same gain and different exposure times is selected. For each exposure time corresponding integral sphere image, column average is performed, and the relationship between the response gray level of each pixel and the exposure time is obtained by least square fitting as follows:

[0087]

[0088] wherein, represents the average gray level of pixel i under exposure time T j , Tj denotes the exposure time, b 1,i , b 2,i is a model coefficient of the relationship between the response gray value of the pixel i and the exposure time.

[0089] Therefore, it can be deduced that the relationship between the response gray value of the pixel i under the exposure times T2 and T1 is:

[0090]

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

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

[0093] Step 102, determining the bright field uniform area and the dark field uniform area of the satellite-borne camera under the first imaging parameter in the plurality of imaging parameters.

[0094] As an implementation manner, the implementation method for determining the bright field uniform area and the dark field uniform area of the satellite-borne camera under the first imaging parameter in the plurality of imaging parameters includes the following steps 201-204, as shown in the figure. Figure 3

[0095] Step 201, dividing the dynamic range of the satellite-borne camera into a plurality of linear regions.

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

[0097] Step 202, selecting the bright and dark uniform fields for each linear region in the plurality of linear regions, and obtaining the bright and dark uniform field image products under the first imaging parameter.

[0098] ​As an implementation manner, from the global calibration field network database, a bright and dark uniform field is selected in each linear area, and data information (including central longitude and latitude, altitude, size, etc.) of the bright and dark uniform field is obtained; based on this, a calibration task planning is performed on a spaceborne high-resolution visible light camera, and a large-area bright and dark uniform field image product under the same imaging parameters (the same integration order, exposure time and gain) is obtained, the large-area bright and dark uniform field image product including image data, metadata and RPC (Rational Polynomial Coefficient, rational polynomial coefficient) information.

[0099] In step 203, based on the data information of the bright and dark uniform fields, the row range of the uniformity evaluation area in the bright and dark uniform field images is determined.

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

[0101]

[0102] Wherein, row represents the row range of the uniformity evaluation area, r c represents 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] In step 204, a target image area corresponding to the row range of the uniformity evaluation area in the bright and dark uniform field image product is determined, the target image area is divided into a plurality of full-width sliding evaluation windows, and based on the uniformity of each full-width sliding evaluation window, a bright and dark field uniform area of the spaceborne camera under the first imaging parameter is determined.

[0104] As an implementation manner, the full-width sliding evaluation window is divided, and the window width contains all the pixels, as shown in the following table: Figure 4 The window height can be generally set to 20, the window is slid from top to bottom, the uniformity of each window is calculated, and the window with the minimum uniformity is automatically selected, that is, the bright and dark field uniform area of the spaceborne camera is determined, which is used for relative radiometric calibration coefficient calculation.

[0105]

[0106] Wherein, U i represents the uniformity of window i, σ i represents the gray scale standard deviation of window i, represents the gray scale average value of window i.

[0107] In step 103, the on-orbit relative radiometric calibration coefficient under the first imaging parameter is obtained based on the bright field uniform area and the dark field uniform area.

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

[0109] For example, based on the automatic selection of the optimal uniform area of the bright and dark uniform fields, the average gray value of the bright and dark uniform areas and the gray column mean of each detector element are calculated to obtain the following equation group:

[0110]

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

[0112] The equation group is solved to obtain the relative radiometric calibration coefficient.

[0113] It should be noted that after obtaining the relative radiometric calibration coefficient, it is also necessary to verify whether the relative radiometric calibration coefficient is effective.

[0114] In some embodiments, the method for verifying whether the relative radiometric calibration coefficient is effective comprises:

[0115] According to the on-orbit relative radiometric calibration coefficient, the other uniform scene images and complex scene images with matching imaging parameters are subjected to relative radiometric correction, and the longitudinal stripes and uneven brightness and darkness on the corrected images are effectively eliminated, which indicates that the obtained on-orbit relative radiometric calibration coefficient is effective.

[0116] Therefore, steps 102 and 103 utilize the uniform field method to realize the rapid acquisition of the relative radiometric calibration coefficient under a certain imaging parameter.

[0117] In step 104, the on-orbit relative radiometric calibration coefficient under other imaging parameters is obtained based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficient under the first imaging parameter.

[0118] After obtaining the on-orbit relative radiometric calibration coefficients under the first imaging parameter automatically, according to the constructed on-orbit relative radiometric calibration coefficient relationship model (including the relative radiometric calibration coefficient relationship model between different gains and the relative radiometric calibration coefficient relationship model between different exposure times), the on-orbit relative radiometric calibration coefficients under different gains can be deduced with a fixed exposure time, or the on-orbit relative radiometric calibration coefficients under different exposure times can be deduced with a fixed gain, and the specific deduction method is as shown in Figure 5

[0119] Through deduction, after obtaining the on-orbit relative radiometric calibration coefficients under other imaging parameters, the obtained on-orbit relative radiometric calibration coefficients can be verified for effectiveness, and the verification method is as follows:

[0120] The on-orbit relative radiometric calibration coefficients under a certain imaging parameter obtained through deduction are used to perform relative radiometric correction on other uniform scene images and complex scene images matched with the imaging parameter, and the longitudinal stripes and uneven brightness and darkness on the corrected images are effectively eliminated, which indicates that the deduced on-orbit relative radiometric calibration coefficients are effective, and the following average row standard deviation method can be used to evaluate the relative radiometric calibration accuracy of the corrected uniform scene images.

[0121]

[0122] wherein, RCP represents the relative radiometric calibration accuracy, N represents the total number of pixels, represents the average gray value of the i-th column of pixels in the uniform area of the corrected image, is the average gray value of the uniform area of the corrected image.

[0123] ​The method for obtaining the on-orbit relative radiometric calibration coefficients of a spaceborne camera according to embodiments of this application obtains an on-orbit relative radiometric calibration coefficient relationship model characterizing the relationship between on-orbit relative radiometric calibration coefficients under different imaging parameters, determines the uniform bright field region and uniform dark field region of the spaceborne camera under a certain imaging parameter, and obtains the on-orbit relative radiometric calibration coefficients under that imaging parameter based on the uniform bright field region and uniform dark field region; based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficients under that imaging parameter, the on-orbit relative radiometric calibration coefficients under other imaging parameters are obtained, realizing the automated calculation of the on-orbit relative radiometric calibration coefficients of the spaceborne camera, and enabling the derivation of the on-orbit relative radiometric calibration parameters under different imaging parameters, improving the efficiency of obtaining the on-orbit relative radiometric calibration coefficients of the spaceborne visible light camera, thereby enabling rapid on-orbit relative radiometric calibration of high-resolution visible light cameras under multiple satellites and multiple imaging parameters, solving the problem in related technologies that the on-orbit relative radiometric calibration efficiency of high-resolution visible light cameras in current large-scale satellite constellation systems is low and difficult to meet the needs of rapid calibration applications under multiple satellites and multiple imaging parameters. Furthermore, the uniform field method offers the advantage of rapidly obtaining relative radiometric calibration coefficients for a given imaging parameter, and its calibration efficiency is further improved through an automatic uniform region selection method. This method was applied to a spaceborne high-resolution visible light camera, yielding effective on-orbit relative radiometric calibration coefficients and achieving good correction results.

[0124] To clearly illustrate the above embodiments, specific examples will now be used for explanation.

[0125] The following example, using a satellite-borne high-resolution visible light camera laboratory and on-orbit Earth observation data, illustrates how this invention achieves the automatic calculation and derivation of its on-orbit relative radiometric calibration coefficients.

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

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

[0128]

[0129] The relationship model between the response gray value of the detector and the gain is established using the camera laboratory integrating sphere calibration data, as shown in Figure 7 The response gray value of the detector and the gain under 3-gain and 4-gain is shown in the figure, the horizontal coordinate represents the pixel sequence number, and the vertical coordinate represents the gray relationship, i.e., a1. It can be seen that the values of a1 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 consistent with the 1.1 n relationship set by the camera development unit.

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

[0131] Figure 9a The integrating sphere image with an exposure time of 20 ms has many longitudinal stripes and uneven brightness and darkness due to the inconsistency of the response of the detector. The relative radiometric calibration coefficient of the 20 ms exposure time is calculated from the relative radiometric calibration coefficient of the 10 ms exposure time, and the 20 ms exposure time integrating sphere image is corrected, and the result is shown in Figure 9b . It can be seen that the stripes and uneven brightness and darkness in the image are effectively eliminated, and the integrating sphere image becomes more uniform, indicating the correctness of the established relative radiometric calibration coefficient deduction relationship model between different gains.

[0132] The relative radiometric calibration coefficient of 3-gain is calculated using the desert and ocean uniform field images obtained on orbit, and the relative radiometric calibration coefficient of 4-gain is calculated from the relative radiometric calibration coefficient of 3-gain according to the established relative radiometric calibration coefficient deduction relationship between different gains. The desert image obtained by 4-gain ( Figure 10a ) is corrected, and the correction effect is shown in Figure 10c , while Figure 10b is the correction effect of the laboratory relative radiometric calibration coefficient of 4-gain on Figure 10a . It can be seen that the desert image before correction has stripes and uneven brightness and darkness, which affects the recognition of desert texture and details. The relative radiometric calibration coefficient obtained on orbit is used to correct the image, which can effectively eliminate the stripes and uneven brightness and darkness, and the laboratory relative radiometric calibration coefficient is no longer applicable, and the correction effect is not as good as the relative radiometric calibration coefficient obtained on orbit.

[0133] To achieve the above-mentioned embodiments, the application further provides an on-orbit relative radiometric calibration coefficient acquisition device of a spaceborne camera. Figure 11 A structural schematic diagram of an on-orbit relative radiometric calibration coefficient acquisition device of a spaceborne camera provided by the embodiments of the application is shown in FIG. 1. As shown in the figure, the on-orbit relative radiometric calibration coefficient acquisition device of the spaceborne camera can include a model acquisition module 301, a region determination module 302, a coefficient calculation module 303, and a coefficient derivation module 304. Figure 11

[0134] The model acquisition module 301 is configured to acquire an on-orbit relative radiometric calibration coefficient relationship model, which is used to represent the relationship between on-orbit relative radiometric calibration coefficients under different imaging parameters.

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

[0136] The coefficient calculation module 303 is configured to acquire the on-orbit relative radiometric calibration coefficient under the first imaging parameter based on the bright-field uniform region and the dark-field uniform region.

[0137] The coefficient derivation module 304 is configured to acquire the on-orbit relative radiometric calibration coefficient under other imaging parameters based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficient under the first imaging parameter.

[0138] Further, in a possible implementation manner of the embodiments of the application, the model acquisition module 301 is specifically configured to:

[0139] construct the on-orbit relative radiometric calibration coefficient relationship model based on an imaging parameter adjustment principle of the spaceborne camera and a linear disassemblable principle;

[0140] determine the coefficients of the on-orbit relative radiometric calibration coefficient relationship model based on laboratory radiometric calibration data of the spaceborne camera.

[0141] Further, in a possible implementation manner of the embodiments of the application, the imaging parameters include an exposure time, a gain, and an integration step, and when constructing the on-orbit relative radiometric calibration coefficient relationship model, the model acquisition module 301 is specifically configured to:

[0142] acquire the relative radiometric calibration coefficient when the imaging parameter is 1, and obtain the relationship between the image element i gray values before and after the relative radiometric correction as follows:

[0143]

[0144] wherein, ​DN 1,i and B 1,i DN 1,i DN

[0145] DN

[0146]

[0147] DN DN x,i and B x,i DN x,i DN

[0148] 1) When the integral order is L, there is a linear change model between the response gray value of the image pixel and the exposure time or gain, i.e.

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

[0150] DN x,i DN 1,i DN 1,i and a 2,i are the response model coefficients of the gray value of the pixel i with the exposure time or gain, which are only related to the imaging parameter and do not change with the response of the pixel;

[0151] According to the principle that the exposure time or gain is the overall amplification of the pixel charge, formula (3) is brought into formula (2), and there is

[0152]

[0153] Accordingly, the following is derived:

[0154]

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

[0156]

[0157] The slope of the relative radiometric calibration coefficient in the on-orbit relative radiometric calibration coefficient relationship model does not change with the change of gain or exposure time, the intercept changes with the change of gain and exposure time, and depends on the coefficient a in the image pixel response linear relationship model 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 between the image pixel responses of different integration orders, but a cumulative integration relationship, that is:

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

[0160] wherein DN x,i represents the gray value of pixel i in the image with integration order x, DN 1,i represents the gray value of pixel i in the image with integration order 1, and DN l ′ ,i represents the charge value of the lth row of pixels on the TDI detector with integration order 1, l = 2…x.

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

[0162] i) Coefficient calculation of the relative radiometric calibration relationship model under different gains:

[0163] The relationship between the pixel i response gray value of the camera under the gain of the G2 gear and the gain of the G1 gear is as follows:

[0164]

[0165] wherein, DN represents the average gray value of pixel i with gain G2, represents the average gray value of pixel i with gain G1, and A i is the amplification multiple of pixel i with gain increased by 1 gear.

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

[0167] ii) Coefficient calculation of the relative radiation calibration relationship model under different exposure times:

[0168] Select a group of integrating sphere image data with the same integrating level, the same gain and different exposure times, perform column averaging on the integrating sphere image corresponding to each exposure time, and obtain the relationship of the response gray value of each pixel with the exposure time through least square fitting as follows:

[0169]

[0170] wherein, represents the average gray value of the pixel i when the exposure time is T j , T j represents the exposure time, and b 1,i , b 2,i are the model coefficients of the response gray value of the pixel i with the exposure time;

[0171] The relationship of the response gray value of the pixel i under the exposure times T2 and T1 can be obtained as follows:

[0172]

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

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

[0175] divide the dynamic range of the space-borne camera into a plurality of linear regions;

[0176] select a bright and dark uniform field for each linear region in the plurality of linear regions, and obtain a bright and dark uniform field image product under the first imaging parameter;

[0177] ​​Determine the row range of the uniformity evaluation area in the bright and dark uniform field images based on the data information of the bright and dark uniform fields;

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

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

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

[0181] Solve the equation group to obtain the on-orbit relative radiometric calibration coefficient under the first imaging parameter;

[0182] Verify the on-orbit relative radiometric calibration coefficient under the first imaging parameter for effectiveness, and obtain the on-orbit relative radiometric calibration coefficient under the first imaging parameter that passes the verification.

[0183] It should be noted that the above explanation and description of the embodiment of the method for obtaining the on-orbit relative radiometric calibration coefficient of the satellite-borne camera also applies to the device for obtaining the on-orbit relative radiometric calibration coefficient of the satellite-borne camera of the embodiment, which will not be described here.

[0184] In order to realize the above-mentioned embodiments, the present application further provides an electronic device. Please refer to Figure 12 , Figure 12 is a structural schematic diagram of the electronic device provided by the embodiment of the present application. As Figure 12 shown, the electronic device 1200 includes a processor 1201 and a memory 1202 connected with the processor 1201; the memory 1202 stores computer execution instructions; the processor 1201 executes the computer execution instructions stored in the memory to realize the method provided by the foregoing embodiments.

[0185] In order to realize the above-mentioned embodiments, the present application further provides a computer readable storage medium, and the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to realize the method provided by the foregoing embodiments.

[0186] In order to realize the above-mentioned embodiments, the present application further provides a computer program product, which includes a computer program, and the computer program is executed by a processor to realize the method provided by the foregoing embodiments.

[0187] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the present application comply with relevant laws and regulations and do not violate public order and good customs.

[0188] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and not shared or sold outside these legitimate uses. In addition, such collection / sharing should be carried out after the user's informed consent is received, including but not limited to informing the user to read the user agreement / user notice before the user uses the function, and signing the agreement / authorization including authorization of relevant user information. In addition, any necessary steps should be taken to protect and secure access to such personal information data and ensure that other people with access to personal information data comply with their privacy policies and processes.

[0189] The present application contemplates providing implementations in which the user can selectively block the use of, or access to, personal information data. That is, the present disclosure contemplates providing users with control to permit, deny, or limit how their information is shared with other entities, including providers of social media services.

[0190] In the foregoing various embodiments described, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples, without contradiction.

[0191] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise explicitly specified.

[0192] Any processes or methods described in the flowcharts or otherwise described herein can be understood as representing modules, segments, or portions of code that include one or more executable instructions for implementing specific logical functions or steps, and the various embodiments of the application can include additional or fewer steps performing the same or equivalent functions as those shown or discussed, in different orders, including substantially simultaneous execution of the functions described with respect to particular steps, and the like.

[0193] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a list of executable instructions for implementing the logic function, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor- containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can specifically include the following, which are non-exhaustive listings: electrical connections (electrical apparatus), portable computer disks (magnetic apparatus), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fiber devices, and portable compact disk read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable medium upon which the program can be printed, as the program can be electronically captured, for example, via the optical scanning of the paper or other medium, followed by the electronic conversion of the optically scanned program into a form that can be edited, compiled, or interpreted or otherwise processed into an electronically usable form, and then stored in the computer memory.

[0194] It should be understood that portions of the application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, the various steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As such, if implemented in hardware and in another embodiment, any of the following technologies, known in the art, or their combinations, can be used to implement the hardware: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0195] Those skilled in the art of the present technology can understand that all or part of the steps carried out by the above-mentioned embodiment method can be completed by programs instructing related hardware, and the programs can be stored in a computer readable storage medium. When the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

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

[0197] The storage medium mentioned above can 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 should be understood that the above-mentioned embodiments are exemplary and cannot be understood as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present application.

Claims

1. A method for obtaining on-orbit relative radiometric calibration coefficients of a space-borne camera, characterized in that, The method comprises the following steps: obtaining an on-orbit relative radiometric calibration coefficient relationship model, the on-orbit relative radiometric calibration coefficient relationship model being used to represent a relationship 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 satellite-borne camera under a first imaging parameter; obtaining on-orbit relative radiometric calibration coefficients under the first imaging parameter based on the bright field uniform area and the dark field uniform area; obtaining on-orbit relative radiometric calibration coefficients under other imaging parameters based on the on-orbit relative radiometric calibration coefficient relationship model and the on-orbit relative radiometric calibration coefficients under the first imaging parameter; the obtaining of the on-orbit relative radiometric calibration coefficient relationship model comprises: constructing the on-orbit relative radiometric calibration coefficient relationship model based on an imaging parameter adjustment principle of the satellite-borne camera and a linear disassemblable principle; determining coefficients of the on-orbit relative radiometric calibration coefficient relationship model based on laboratory radiometric calibration data of the satellite-borne camera; the imaging parameters comprise exposure time, gain and integration order, and the constructing of the on-orbit relative radiometric calibration coefficient relationship model based on the imaging parameter adjustment principle of the satellite-borne camera and the linear disassemblable principle comprises: 1) When the integration time is the same for both L, the relative radiometric coefficients for gain or exposure time of x 1 and gain or exposure time of 1 are as follows: （6） wherein K 1,i and B 1,i denote the slope and intercept of the relative radiometric calibration of the image pixels i for an imaging parameter of 1; K x,i and B x,i denote the slope and intercept of the relative radiometric calibration of the image pixels x for an imaging parameter of i 1. The slope of the relative radiometric calibration coefficient in the on-orbit relative radiometric calibration coefficient relationship model does not change with the change of gain or exposure time, the intercept changes with the change of gain and exposure time, and depends on the coefficient in the image pixel response linear relationship model between different exposure times or gains a 1,i and a 2,i under different gains, a 1,i = / , represents the average gray value of the pixel i under the gain G1, under different exposure times, a 1,i = 1, , b 1,i is the pixel i response gray value change relationship model coefficient with exposure time; 2) when the gain and the exposure time are the same, there is no overall linear transformation between image pixel responses under different integration orders, but a cumulative integration relationship, that is: （7） wherein DN x,i represents the gray value of a pixel in the image when the integral order is x i DN 1,i represents the gray value of a pixel in the image when the integral order is i represents the charge value of the pixel in the l l l =2… x .​​​​​ 2. The method of claim 1, wherein, the constructing of the on-orbit relative radiometric calibration coefficient relationship model based on the imaging parameter adjustment principle of the satellite-borne camera and the linear disassemblable principle comprises: The relative radiation calibration coefficient of imaging parameter 1 is obtained, and the image pixels before and after relative radiation correction are obtained i The relationship between the gray values is as follows: （1） wherein, DN represents the gray value of the image pixel when the relative radiation correction after imaging parameter is 1; and i DN represents the gray value of the image pixel when the relative radiation correction after imaging parameter is 1; and 1,i DN represents the gray value of the image pixel when the relative radiation correction after imaging parameter is 1; and i DN represents the gray value of the image pixel when the relative radiation correction after imaging parameter is 1; and The imaging parameter is acquired as x the relative radiation calibration coefficient at the time, to obtain the relationship between the image pixel gray values before and after the relative radiation correction i the relative radiation calibration coefficient at the time, to obtain the relationship between the image pixel gray values before and after the relative radiation correction （2） wherein, represents the gray value of the image pixel when the relative radiation-corrected imaging parameter is x i DN x,i represents the gray value of the image pixel when the relative radiation-uncorrected imaging parameter is x i DN​​ 1) when the integration order is L, there is an overall linear change relationship model between image pixel response gray values under different exposure times or gains, that is: （3） wherein, DN x,i denotes the gray value of the image element x at the time of exposure or gain of 1, i DN 1,i denotes the gray value of the image element i at the time of exposure or gain of 1, a 1,i and a 2,i is a model coefficient of the gray value of the image element i in response to the exposure time or gain, which is only related to the imaging parameter and does not change with the change of the probe element response.​ According to the principle that the exposure time or the gain is overall amplification of the charge of the pixel, formula (3) is brought into formula (2), and there is: （4） Accordingly, the following is disassembled and derived: （5） The relative radiometric coefficients for gain or exposure times of x The relationship between the relative radiometric coefficients for gain or exposure times of 1 and gain or exposure times of 1 is as follows: （6）。 3. The method of claim 2, wherein, the laboratory radiometric calibration data comprise integrating sphere image data under different exposure times and different gains, and the determining of the coefficients of the on-orbit relative radiometric calibration coefficient relationship model based on the laboratory radiometric calibration data of the satellite-borne camera comprises: i) coefficient calculation of the relative radiometric calibration relationship model under different gains: ii) coefficient calculation of the relative radiometric calibration relationship model under different exposure times: The camera probes the element under G2 and G1 gain i The response gray value relationship is: （8） wherein, represents the average gray value of the pixel i with gain G2, A i is the pixel i with gain increased by one step, then a 1,i = ; Select a group of integrating sphere image data with same integral series, same exposure time and different gain. For each gain corresponding integrating sphere image, carry out column average to obtain a data table. Row direction represents pixel serial number, column direction represents gain level, and each value in the table represents response value under gain i G j ​​​ a set of integrating sphere image data with the same integration order, the same gain and different exposure times are selected, column averages are performed on the integrating sphere image corresponding to each exposure time, and the relationship between the gray value of each pixel response and the exposure time is obtained through least square fitting as follows: the determining of the bright field uniform area and the dark field uniform area of the satellite-borne camera under the first imaging parameter comprises: （9） in, Indicates the exposure time is T j Time Pixel i Average gray value, T j Indicates the exposure time. b 2,i For pixels i Coefficients of the model relating response grayscale value to exposure time; Available exposure time T 2 and T 1 down element i Response gray value relationship is: （10） wherein, represents the average gray value of the pixels T when the exposure time is i 2, represents the average gray value of the pixels T when the exposure time is i 1.

4. The method of claim 1, wherein, dividing a dynamic range of the satellite-borne 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 the first imaging parameter; based on data information of the bright uniform field and the dark uniform field, determining a row range of a uniformity evaluation area in the bright uniform field image and the dark uniform field image; ​ Corresponding to the row range of the uniformity evaluation area in the bright and dark uniform field image product, a target image area is determined, the target image area is divided into a plurality of full-width sliding evaluation windows, and based on the uniformity of each full-width sliding evaluation window, a bright field uniform area and a dark field uniform area of the spaceborne camera under the first imaging parameter are determined.

5. The method of claim 1, wherein, The in-orbit relative radiometric calibration coefficient under the first imaging parameter is obtained based on the bright field uniform area and the dark field uniform area, and the in-orbit relative radiometric calibration coefficient under the first imaging parameter is obtained based on the bright field uniform area and the dark field uniform area. The average gray value of the bright field uniform area and the dark field uniform area and the gray column mean value of each detector element are obtained, and an equation set is obtained. The in-orbit relative radiometric calibration coefficient under the first imaging parameter is obtained by solving the equation set. The in-orbit relative radiometric calibration coefficient under the first imaging parameter is verified for effectiveness, and the in-orbit relative radiometric calibration coefficient under the first imaging parameter that passes the verification is obtained.

6. An on-orbit relative radiometric calibration coefficient acquisition device for a space-borne camera, characterized in that, It comprises: A model acquisition module is configured to acquire an in-orbit relative radiometric calibration coefficient relationship model, which is used to represent the relationship between in-orbit relative radiometric calibration coefficients under different imaging parameters. A region determination module is configured to determine a bright field uniform area and a dark field uniform area of the spaceborne camera under the first imaging parameter. A coefficient calculation module is configured to obtain the in-orbit relative radiometric 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 configured to obtain the in-orbit relative radiometric calibration coefficient under other imaging parameters based on the in-orbit relative radiometric calibration coefficient relationship model and the in-orbit relative radiometric calibration coefficient under the first imaging parameter. The in-orbit relative radiometric calibration coefficient relationship model is obtained based on the imaging parameter adjustment principle of the spaceborne camera and the linear decomposability principle. The in-orbit relative radiometric calibration coefficient relationship model is constructed based on the imaging parameter adjustment principle of the spaceborne camera and the linear decomposability principle. The imaging parameters include exposure time, gain and integration order, and the in-orbit relative radiometric calibration coefficient relationship model is constructed based on the imaging parameter adjustment principle of the spaceborne camera and the linear decomposability principle. 2) When the gain and the exposure time are the same, there is no overall linear transformation between the image element responses of different integration orders, but a cumulative integration relationship, that is: 1) When the integration time is the same for both L, the relative radiometric coefficients for gain or exposure time of x 1 and gain or exposure time of 1 are as follows: （6） wherein K 1,i and B 1,i denote the slope and intercept in the relative radiometric calibration of image pixels i for an imaging parameter of 1; K x,i and B x,i denote the slope and intercept in the relative radiometric calibration of image pixels x for an imaging parameter of i 1. The slope of the relative radiometric calibration coefficient in the on-orbit relative radiometric calibration coefficient relationship model does not change with the change of gain or exposure time, the intercept changes with the change of gain and exposure time, and depends on the coefficient in the image pixel response linear relationship model between different exposure times or gains a 1,i and a 2,i under different gains, a 1,i = / , represents the average gray value of the pixel i under the gain G1, under different exposure times, a 1,i =1, , b 1,i is the pixel i response gray value change relationship model coefficient with exposure time; DN （7） wherein DN x,i represents the gray value of the pixel in the image when the integral order is x i It comprises: 1,i represents the gray value of the pixel in the image when the integral order is 1, i represents the charge value of the pixel in the TDI detector when the integral order is l l l =2… x .​​​​​ 7. An electronic device, comprising: A processor and a memory in communication with the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method of any one of claims 1-5. The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1-5.

9. A computer program product, characterised in that, ​

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