A Space-based Quantitative Photometric Measurement Method and Device for Space Point Targets

Abstract

The present invention discloses a method and device for space point target photometric space-based quantitative measurement, which solves the problem of how to improve the efficiency and accuracy of space point target photometric space-based quantitative measurement; belongs to the field of optoelectronic detection; includes: performing non-uniform correction and bilateral filtering denoising on the original image to obtain a preprocessed image; estimating the dark field value of the preprocessed image by the mode method as the background gray value; if a point target is detected in the preprocessed image, calculating the photometric aperture to obtain the photometric aperture when the optical signal-to-noise ratio is the largest, otherwise directly feedbacking invalid information; inputting the photometric aperture parameter into the calibration response relationship function to calculate the inversion photometric value of the point target; calculating the magnitude error or magnitude standard deviation according to the point target photometric value error model or the point target photometric value error transfer model to verify the accuracy of space point target photometric space-based quantitative measurement. The present invention improves the efficiency and accuracy of space point target photometric measurement.

Description

Technical Field

[0001] The present invention belongs to the technical field of optoelectronic detection, and relates to a method and device for quantitative space-based photometric measurement of space point targets. Background Art

[0002] To explore and utilize space more effectively, countries around the world have put forward higher requirements for obtaining the characterization information and behavioral characteristics of space targets. As an important means of space situation awareness, space-based observation effectively avoids the influence of factors such as weather, day and night, and background skylight, and can obtain target photometric information all-weather, over a wide area, and at a long distance. The optical characteristics of space targets are closely related to the changes in the space position, attitude, and detection angle of the targets. At the same time, the material changes of the targets during space operation will also cause changes in photometry. Therefore, accurate and reliable photometric measurement devices and data measurement are particularly crucial. Compared with ground-based observation, space-based observation needs to focus on and meet requirements such as space illumination, particle radiation, and carrying conditions, and specific designs need to be carried out in terms of volume, weight, temperature control, radiation protection, stray light elimination, vibration, and detection sensitivity. At the same time, the performance of space-based observation is also affected by factors such as orbit, earth occlusion and earth light conditions, penumbra conditions, sunlight conditions, moonlight conditions, and non-direct conditions. It is necessary to avoid direct sunlight and earth-gas light interference by reasonably planning the observation time and angle, attitude adjustment, etc.

[0003] Space-based optical detection systems generally require functions such as geometric visibility, optical scattering characteristics, photoelectric effect, orbit parameter and camera pointing calculation, and imaging simulation, stray light suppression, etc., and usually consist of a space platform, an optical telescope, a photoelectric sensor, an image processor, a data storage and transmission device, etc. Among them, the space platform is used to protect against severe vibration, micro-meteorite impact, and solar radiation during the launch process. At present, high-performance space-based optical cameras are relatively heavy. With the development of technology, some small and lightweight space optical cameras have emerged, but most of them are limited to optical imaging and the measurement effect is not good. Therefore, when designing a reliable space-based quantitative photometric measurement device for space point targets, aspects such as optical lenses, opto-mechanical structures, electronic systems, and temperature control need to be considered to ensure the stable operation of the measurement device, efficiently process space image data, and transmit it. Summary of the Invention

[0004] In order to solve the technical problem of how to improve the efficiency and accuracy of space-based quantitative photometric measurement of space point targets, the present invention proposes a method and device for space-based quantitative photometric measurement of space point targets, which helps to design a lightweight and small space-based photometric measurement device, and can efficiently perform the task of space-based quantitative photometric measurement of space point targets, effectively improve the efficiency and accuracy of space-based quantitative photometric measurement of space point targets, improve the space point target image data processing ability, and provide reliable conditions for long-term observation, characteristic mastery, and cataloging of targets.

[0005] The object of the present invention is specifically realized by the following technical solutions:

[0006] The present invention discloses a space point target photometric space-based quantitative measurement method, including:

[0007] Step 1: Parse and compress the on-board image data, and then the downlink data transmission system transmits the obtained original image to the ground processing system;

[0008] Step 2: The ground processing system performs non-uniform correction on the obtained original image and then performs denoising processing through bilateral filtering to obtain a preprocessed image;

[0009] Step 3: Use the mode method to estimate the dark field value of the preprocessed image, and use the dark field value as the background gray value of the preprocessed image;

[0010] Step 4: If a point target is detected in the preprocessed image, use the photometric aperture method to calculate the effective area of the point target, obtain the photometric aperture when the optical signal-to-noise ratio is the largest, and output the corresponding photometric aperture parameters; otherwise, directly feedback invalid information;

[0011] Step 5: Input the photometric aperture parameters into the calibration response relationship function to calculate the retrieved photometric value of the point target;

[0012] Step 6: When there is a true photometric value, calculate the error of the retrieved photometric value according to the point target photometric value error model and convert it into a magnitude error; when there is no true photometric value, calculate the standard deviation of the retrieved photometric value according to the point target photometric value error propagation model and convert it into a magnitude standard deviation; evaluate the space-based quantitative measurement accuracy of the space point target photometry by the magnitude error or the magnitude standard deviation.

[0013] In Step 1, the method for parsing the on-board image data includes:

[0014] According to the satellite imaging system and the whole satellite auxiliary data protocol, parse the on-board image data, cache 3500 lines of imaging code stream data each time, each line includes 64 bytes of auxiliary data and 4672×2 bytes of image full chromatographic segment data, and obtain the original image.

[0015] In Step 2, the method for non-uniform correction includes:

[0016]

[0017] In the formula, G′(i,j) is the gray value of any point in the original image after non-uniform correction, G(i,j) is the gray value of any point in the original image; I(i,j) is the gray value of any point in the obtained image after removing the influence of the background image; is the overall gray value estimate of the flat field image after removing the influence of the background image; is the background gray value estimate of the background image; where,

[0018]

[0019] Wherein, B(i,j) is the gray value of any point in the background image obtained by the optoelectronic device without light source input, and M and N are the ranges of the number of row and column pixels of the background image respectively;

[0020]

[0021] Wherein, F(i,j) is the gray value of any point in the flat-field image obtained by irradiating with a uniform light source;

[0022]

[0023] In step two, the method of bilateral filtering denoising processing includes:

[0024]

[0025] Wherein, g(i,j) is the pixel gray value of any point in the preprocessed image, and (i,j) is the pixel coordinate of the current pixel point in the preprocessed image; G′(m,n) is the pixel gray value of any point neighborhood in the image after non-uniform correction of the original image, and (m,n) is the pixel coordinate of the current pixel point neighborhood in the image after non-uniform correction of the original image, and ω(i,j,m,n) is the weighting coefficient obtained by the pixel value of the preprocessed image depending on the neighborhood pixel value; among them,

[0026] The calculation method of the weighting coefficient ω(i,j,m,n) includes:

[0027]

[0028] Wherein, σ d is the distance standard deviation, σ r is the gray value standard deviation. The larger the distance standard deviation, the more blurred the image, and the larger the gray value standard deviation, the more blurred the image details.

[0029] In step three, the method of estimating the dark field value of the preprocessed image by the mode method includes:

[0030]

[0031] Wherein, mode is the mode, median is the median of the background gray value of the preprocessed image, and mean is the mean of the background gray value of the preprocessed image.

[0032] In step four, the steps of calculating the effective area of the point target by the photometric aperture method include:

[0033]

[0034] Wherein, SNR is the optical signal-to-noise ratio, g(i,j) is the pixel gray value of any point in the preprocessed image, and DN background is the background gray value of the preprocessed image, is the variance of the background gray value of the preprocessed image, and DN Th is the gray segmentation threshold of the preprocessed image;

[0035] Traverse DN Th , when SNR is the maximum value, the corresponding DN Th is the segmentation threshold of the photometric aperture, the photometric aperture with the maximum optical signal-to-noise ratio is obtained, and the corresponding photometric aperture parameter DN (x,y) is output, where (x,y) is the coordinate of the photometric aperture parameter.

[0036] In step five, the calibration response relationship function is:

[0037]

[0038] Wherein, E0 is the retrieved photometric value of the point target, k is the number of pixels occupied by the point target in the preprocessed image, and DN (x,y) is the photometric aperture parameter, DN background is the background gray value of the preprocessed image, k gain is the slope radiation calibration coefficient, g Bias is the random error radiation calibration coefficient, α gain is k gain is the calibration coefficient coupled with the detector pixel size and focal length, β Bias is g Bias is the calibration coefficient coupled with the detector pixel size and focal length; d is the detector pixel size, and f is the camera focal length.

[0039] In step six, when there is a true photometric value, the method for calculating the error of the retrieved photometric value according to the point target photometric value error model and converting it into a magnitude error includes:

[0040] The point target photometric value error model is:

[0041] ΔE obj = E obj - E0

[0042] Wherein, ΔE obj is the error of the retrieved photometric value, E obj is the true photometric value of the point target, and E0 is the retrieved photometric value of the point target;

[0043] The conversion method of the magnitude error is:

[0044] ΔM = M′ - M0

[0045] Where, ΔM is the magnitude error, M′ is the retrieved magnitude of the point target, and M0 is the true magnitude corresponding to M′;

[0046]

[0047] In step six, when there is no true photometric value, the method for calculating the standard deviation of the retrieved photometric value according to the point target photometric value error transfer model and converting it into the standard deviation of magnitude includes:

[0048] The point target photometric value error transfer model is:

[0049]

[0050] Where, is the standard deviation of the retrieved photometric value, DN (x,y) is the photometric aperture parameter, σ Gain is the standard deviation of the radiometric calibration response coefficient, Gain is the gain calibration coefficient, ΔDN (x,y) is the deviation of the gray value of the point target caused by noise, d is the detector pixel size, and f is the camera focal length;

[0051] The conversion method of the magnitude standard deviation σ m is:

[0052]

[0053] Where, m is the magnitude of the point target.

[0054] The present invention also provides a space point target photometric space-based quantitative measurement device, including:

[0055] A data analysis module, which is used to parse and compress the on-orbit image data, and then transmit the obtained original image to the ground processing system through the data transmission system;

[0056] An image preprocessing module, which is used to perform non-uniform correction on the obtained original image and then perform denoising processing through bilateral filtering to obtain a preprocessed image;

[0057] A dark field value estimation module, which is used to estimate the dark field value of the preprocessed image by using the mode method and use the dark field value as the background gray value of the preprocessed image;

[0058] A star point detection module, which is used to calculate the effective area of the point target by using the photometric aperture method when a point target is detected in the preprocessed image, obtain the photometric aperture when the optical signal-to-noise ratio is the largest, and output the corresponding photometric aperture parameter, otherwise, directly feedback invalid information;

[0059] A retrieved calculation module, which is used to input the photometric aperture parameter into the calibration response relationship function to calculate the retrieved photometric value of the point target;

[0060] An error calculation module is used to calculate the error of the retrieved photometric value according to the point target photometric value error model and convert it into the magnitude error when there is a true photometric value; when there is no true photometric value, it calculates the standard deviation of the retrieved photometric value according to the point target photometric value error transfer model and converts it into the magnitude standard deviation; the space point target photometric space-based quantitative measurement accuracy is evaluated by the magnitude error or the magnitude standard deviation.

[0061] The beneficial effects of the present invention are:

[0062] Through a space point target photometric space-based quantitative measurement method and device disclosed by the present invention, non-uniform correction and bilateral filtering denoising processing are adopted to effectively suppress the interference caused by the detector itself and stray light in the space scene, and a preprocessed image is obtained. The mode method is used to estimate the dark field value of the preprocessed image, and the dark field value is used as the background gray value of the preprocessed image, reducing the deviation caused by cosmic rays, galaxies, bright stars, etc.; for the preprocessed image, the photometric aperture method is used to calculate the target effective area, and the photometric aperture obtained when the optical signal-to-noise ratio is the largest is the optimal aperture. On this basis, according to the calibration response relationship function and the point target photometric value error model or the point target photometric value error transfer model, the magnitude error or the magnitude standard deviation is calculated, and the space point target photometric space-based quantitative measurement accuracy is evaluated. The present invention can be directly applied to the space-based photometric measurement device, efficiently execute the space-based space point target photometric quantitative measurement task, and improve the space point target photometric measurement efficiency and accuracy. Description of the Drawings

[0063] The present invention will be further described in detail below with reference to the drawings and embodiments.

[0064] Figure 1 It is a schematic diagram of the relationship between the point target and the observation distance.

[0065] Figure 2 It is a schematic diagram of the error of the retrieved photometric value under laboratory conditions.

[0066] Figure 3 It is a schematic diagram of the error of the retrieved photometric value under the condition of space-based observation of stars. Detailed Embodiments

[0067] The embodiment of the present invention provides a space point target photometric space-based quantitative measurement method disclosed by the present invention, including:

[0068] Step 1: Parse and compress the on-orbit image data, and then the downlink system transmits the obtained original image to the ground processing system.

[0069] Step 2: The ground processing system performs non-uniform correction on the obtained original image and then performs bilateral filtering denoising processing to obtain a preprocessed image.

[0070] Non-uniform correction means that, under uniform light illumination and when each pixel point is not saturated, the gray value error of each pixel output caused by inconsistent responses is statistically analyzed. In the space target images captured by on-board devices, background noise and pixel bad points will affect the measurement accuracy. Therefore, in the present invention, bilateral filtering denoising processing is performed. Bilateral filtering can effectively filter out noise, protect the image edges, eliminate the non-uniformity caused by the inconsistent responses of each pixel to the environment, temperature, and various amplification circuits, and further eliminate the internal deviation of the device.

[0071] Step 3: Estimate the dark field value of the preprocessed image using the mode method, and use the dark field value as the background gray value of the preprocessed image.

[0072] Ideally, after one-dimensional Gaussian fitting of the histogram, the center is solved, and the center value is the point with the highest frequency of the background gray value. The center value can be used as the estimated value of the background. However, cosmic rays, galaxies, bright stars, etc. in the image will cause deviations, and the values of the gray mean, median, and histogram peak (mode) are not the same. Therefore, in the present invention, the mode method is used to estimate the dark field value of the denoised image in Step 2.

[0073] Step 4: If a point target is detected in the preprocessed image, use the photometric aperture method to calculate the effective area of the point target, obtain the photometric aperture when the optical signal-to-noise ratio is the largest, that is, determine an optimal segmentation threshold, and output the corresponding photometric aperture parameter; otherwise, directly feedback invalid information.

[0074] Step 5: Input the photometric aperture parameter into the calibration response relationship function to calculate the inversion photometric value of the point target.

[0075] Step 6: When there is a true photometric value, calculate the error of the inversion photometric value according to the point target photometric value error model and convert it into a magnitude error; when there is no true photometric value, calculate the standard deviation of the inversion photometric value according to the point target photometric value error transfer model and convert it into a magnitude standard deviation; evaluate the space point target photometric space-based quantitative measurement accuracy by the magnitude error or magnitude standard deviation.

[0076] In Step 1, the method for parsing on-board image data includes:

[0077] Parse the on-board image data according to the satellite imaging system and the whole satellite auxiliary data protocol. Each time, cache 3500 lines of imaging code stream data. Each line includes 64 bytes of auxiliary data and 4672×2 bytes of image full-color spectrum data to obtain the original image.

[0078] In Step 2, the method for non-uniform correction includes:

[0079]

[0080] Where G′(i,j) is the gray value of any point in the original image after non-uniform correction, G(i,j) is the gray value of any point in the original image; I(i,j) is the gray value of any point in the image after removing the background image. It is the overall estimated value of the grayscale of the flat field image after removing the influence of the background image; is the estimated grayscale value of the background image;

[0081]

[0082] Where B(i,j) is the gray value of any point in the background image obtained by the optoelectronic device when there is no light input, and M and N are the row and column pixel number ranges of the background image respectively;

[0083]

[0084] Where F(i,j) is the gray value of any point in the flat-field image obtained by irradiation with a uniform light source;

[0085]

[0086] In step 2, the bilateral filtering denoising method includes:

[0087]

[0088] Where g(i,j) is the grayscale value of any pixel in the preprocessed image, (i,j) is the pixel coordinate of the current pixel in the preprocessed image; G′(m,n) is the pixel grayscale value of the neighborhood of any point in the original image after non-uniform correction, (m,n) is the pixel coordinate of the neighborhood of the current pixel in the original image after non-uniform correction, and the neighborhood range can be set to 3×3; ω(i,j,m,n) is the weighting coefficient obtained by the pixel value of the preprocessed image depending on the neighborhood pixel value; where,

[0089] The calculation method of the weighting coefficient ω(i,j,m,n) includes:

[0090]

[0091] In the formula, σ d is the distance standard deviation, σ r The larger the distance standard deviation, the more blurred the image is. The larger the gray value standard deviation, the more blurred the image details are. In the embodiment of the present invention, the template size can be selected as 3×3, the distance standard deviation is 3, and the gray value standard deviation is 10.

[0092] In step 3, the method of estimating the dark field value of the preprocessed image using the majority method includes:

[0093]

[0094] Where mode is the mode, median is the median of the background gray level of the preprocessed image, and mean is the mean of the background gray level of the preprocessed image.

[0095] In step four, the steps of calculating the effective area of the point target by using the photometric aperture method include:

[0096]

[0097] Where SNR is the optical signal-to-noise ratio, g(i,j) is the pixel gray value of any point in the preprocessed image, DN background is the background gray value of the preprocessed image, is the variance of the background gray value of the preprocessed image, DN Th is the gray level segmentation threshold of the preprocessed image;

[0098] Traverse DN Th When SNR is the maximum value, the corresponding DN Th is the segmentation threshold of the photometric aperture, and the photometric aperture with the maximum optical signal-to-noise ratio is obtained, and the corresponding photometric aperture parameter DN (x,y) , (x,y) is the coordinate of the photometric aperture parameter.

[0099] In step five, the calibration response relationship function is:

[0100]

[0101] Where E0 is the inversion photometric value of the point target, k is the number of pixels occupied by the point target in the preprocessed image, DN (x,y) is the photometric aperture parameter, DN background is the background gray value of the preprocessed image, k gain is the slope radiation calibration coefficient, reflecting the slope, g Bias is the random error radiation calibration coefficient, reflecting the random error, α gain is k gain is the calibration coefficient coupled with the detector pixel size and focal length, β Bias is g Bias is the calibration coefficient coupled with the detector pixel size and focal length; d is the detector pixel size, and f is the camera focal length.

[0102] In step six, when there is a true photometric value, the method of calculating the error of the inversion photometric value according to the point target photometric value error model and converting it into the magnitude error includes:

[0103] The point target photometric value error model is:

[0104] ΔE obj = E obj - E0

[0105] Where ΔE obj is the error of the retrieved photometric value, E obj is the true photometric value of the point target, and E0 is the retrieved photometric value of the point target;

[0106] The conversion method of the magnitude error is as follows:

[0107] ΔM = M′ - M0

[0108] Where ΔM is the magnitude error, M′ is the retrieved magnitude of the point target, and M0 is the true magnitude corresponding to M′;

[0109]

[0110] In step six, when there is no true photometric value, within the linear range of the detector, when the gray value DN of the point target is relatively high, compared with the shot noise, the dark current noise, readout noise, and background noise can be ignored. In this method, the measurement error of the radiation calibration coefficient and the noise error of the target signal coupling are mainly considered. Then, the method for calculating the standard deviation of the retrieved photometric value according to the point target photometric value error transfer model and converting it into the standard deviation of magnitude includes:

[0111] The point target photometric value error transfer model is:

[0112]

[0113] Where is the standard deviation of the retrieved photometric value, DN (x,y) is the photometric aperture parameter, σ Gain is the standard deviation of the radiation calibration response coefficient, Gain is the gain calibration coefficient, ΔDN (x,y) is the deviation of the gray value of the point target caused by noise, d is the detector pixel size, and f is the camera focal length;

[0114] The conversion method of the magnitude standard deviation σ m is as follows:

[0115]

[0116] Where m is the magnitude of the point target.

[0117] The present invention also provides a space point target photometric space-based quantitative measurement device, including:

[0118] A data analysis module for parsing and compressing the on-orbit image data and then transmitting the obtained original image to the ground processing system through the data transmission system;

[0119] An image preprocessing module for performing non-uniform correction on the acquired original image and then performing denoising processing through bilateral filtering to obtain a preprocessed image;

[0120] A dark field value estimation module, which is used to estimate the dark field value of the preprocessed image by using the mode method and take the dark field value as the background gray value of the preprocessed image;

[0121] A star point detection module, which is used to calculate the effective area of the point target by using the photometric aperture method when a point target is detected in the preprocessed image, obtain the photometric aperture when the optical signal-to-noise ratio is the largest, and output the corresponding photometric aperture parameter. Otherwise, it directly feeds back invalid information;

[0122] An inversion calculation module, which is used to input the photometric aperture parameter into the calibration response relationship function and calculate the inversion photometric value of the point target;

[0123] An error calculation module, which is used to calculate the error of the inversion photometric value according to the point target photometric value error model and convert it into magnitude error when there is a true photometric value; when there is no true photometric value, it calculates the standard deviation of the inversion photometric value according to the point target photometric value error transfer model and converts it into magnitude standard deviation; the space point target photometric space-based quantitative measurement accuracy is evaluated by the magnitude error or magnitude standard deviation.

[0124] Application example:

[0125] When the satellite orbit and the state of a space point target photometric space-based quantitative measurement device disclosed in the present invention are determined, the observation distance and phase angle can be basically determined. The main factors affecting the apparent magnitude of the target are the size and reflectivity of the point target. For a moving point target detection system, a small detector pixel size is beneficial to improving the angle measurement accuracy, but it will reduce the dwell time of the point target in the pixel. Therefore, in this example, the detector uses the binning mode to adjust the pixel size, and the long optical GMAX3265 chip is selected as the detector.

[0126] See Figure 1 , taking the surface reflectivity of 0.2 as the average value of the surface reflectivity of the point target, the relationship between the 30 cm diameter point target and the observation distance is calculated as shown in Figure 1 shown.

[0127] See Figure 2 , under laboratory conditions, the error of the inversion photometric value is as shown in Figure 2 shown.

[0128] See Figure 3 , under the conditions of space-based observation of stars, the error of the inversion photometric value is as shown in Figure 3 shown.

[0129] The space point target photometric space-based quantitative measurement accuracy evaluation is carried out under two conditions of laboratory and space-based observation of stars:

[0130] (1) Under laboratory conditions, α gain 、βBias As shown in Table 1, based on this, the error of the retrieved photometric value of the point target under the illumination condition of 5Mv is 2.15×10 -10 W / m 2 .

[0131] Table 1

[0132]

[0133]

[0134]

[0135] Under the exposure time of 10ms and the illumination of 5Mv, 40 photos are collected and the error calculation of the retrieved photometric value is carried out. The magnitude error under the illumination condition of 5Mv can be obtained as ±0.1Mv, and the error of the retrieved photometric value is as Figure 2 shown.

[0136] (2) Under the condition of space-based observation of stars,

[0137] Select the HR7950 star as the benchmark for photometric measurement evaluation, and it is necessary to meet: stable radiation flux; the peak radiation wavelength is close to 0.55μm, and the spectral type is preferably G type. Select the HR7950 star as the radiation benchmark, and the wavelength-flux curve is as Figure 3 shown, and the magnitude error of the HR7950 star is shown in Table 2.

[0138] Table 2

[0139] Test serial number V magnitude (Mv) V magnitude error (Mv) 1 3.92 0.15 2 3.70 -0.07 3 3.73 -0.04 4 3.75 -0.02 5 3.90 0.13

[0140] The beneficial effects of the embodiments of the present invention are as follows:

[0141] Through a space point target photometric space-based quantitative measurement method and device disclosed by the present invention, non-uniform correction and bilateral filtering denoising processing are adopted to effectively suppress the interference caused by the detector itself and stray light in the space scene, and a preprocessed image is obtained. The mode method is used to estimate the dark field value of the preprocessed image, and the dark field value is used as the background gray value of the preprocessed image, reducing the deviation caused by cosmic rays, galaxies, bright stars, etc.; for the preprocessed image, the method of photometric aperture is used to calculate the effective area of the target, and the photometric aperture obtained when the optical signal-to-noise ratio is the largest is the best aperture. On this basis, according to the calibration response relationship function and the point target photometric value error model or the point target photometric value error transfer model, the magnitude error or magnitude standard deviation is calculated, and the space-based quantitative measurement accuracy of the space point target photometric value is evaluated. The present invention can be directly applied to the space-based photometric measurement device, efficiently execute the space-based space point target photometric quantitative measurement task, and improve the efficiency and accuracy of the space point target photometric measurement.

[0142] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the said claims.

Claims

1. A space-based quantitative measurement method for the photometric properties of a spatial point target, characterized in that: include: Step 1: After analyzing and compressing the on-board image data, the data transmission system transmits the obtained original image to the ground processing system; Step 2: The ground processing system performs non-uniform correction on the acquired original image and then performs bilateral filtering to remove noise, thereby obtaining a pre-processed image; Step 3: Use the majority method to estimate the dark field value of the preprocessed image, and use the dark field value as the background gray value of the preprocessed image; Step 4: If a point target is detected in the preprocessed image, the effective area of ​​the point target is calculated using the photometric aperture method to obtain the photometric aperture when the optical signal-to-noise ratio is the largest, and the corresponding photometric aperture parameters are output. Otherwise, invalid information is directly fed back. Step 5: Input the photometric aperture parameters into the calibration response relationship function to calculate the inverted photometric value of the point target; Step 6: When the true photometric value is available, the error of the inverted photometric value is calculated according to the point target photometric value error model and converted into the magnitude error; when there is no true photometric value, the standard deviation of the inverted photometric value is calculated according to the point target photometric value error transfer model and converted into the magnitude standard deviation; the magnitude error or magnitude standard deviation is used to evaluate the accuracy of space-based quantitative measurement of space point target photometric values.

2. The method according to claim 1, characterized in that In step 1, the method for analyzing on-board image data includes: According to the satellite imaging system and the satellite auxiliary data protocol, the on-board image data is parsed, and 3500 lines of imaging code stream data are cached each time. Each line includes 64 bytes of auxiliary data and 4672×2 bytes of image full color spectrum segment data to obtain the original image.

3. The method according to claim 2, characterized in that In step 2, the method of non-uniform correction includes: In the formula, G′( i,j ) is the gray value of any point in the original image after non-uniform correction, G(i,j) is the gray value of any point in the original image; I(i,j) is the gray value of any point in the image after removing the influence of the background image; It is the overall estimated value of the grayscale of the flat field image after removing the influence of the background image; is the estimated grayscale value of the background image; Where B(i,j) is the gray value of any point in the background image obtained by the optoelectronic device when there is no light input, and M and N are the row and column pixel number ranges of the background image respectively; Where F(i,j) is the gray value of any point in the flat-field image obtained by irradiation with a uniform light source; 4. The method according to claim 3, characterized in that In step 2, the bilateral filtering denoising method includes: Where g(i,j) is the grayscale value of any pixel in the preprocessed image, (i,j) is the pixel coordinate of the current pixel in the preprocessed image; G′(m,n) is the pixel grayscale value of any pixel in the neighborhood of the original image after non-uniform correction, (m,n) is the pixel coordinate of the neighborhood of the current pixel in the original image after non-uniform correction, ω(i,j,m,n) is the weighting coefficient of the pixel value of the preprocessed image depending on the pixel value of the neighborhood; where, The calculation method of the weighting coefficient ω(i,j,m,n) includes: In the formula, σ d is the distance standard deviation, σ r is the gray value standard deviation. The larger the distance standard deviation, the more blurred the image. The larger the gray value standard deviation, the more blurred the image details.

5. The method according to claim 4, characterized in that In step 3, the method of estimating the dark field value of the preprocessed image using the majority method includes: Where mode is the mode, median is the median of the background grayscale of the preprocessed image, and mean is the mean of the background grayscale of the preprocessed image.

6. The method according to claim 5, characterized in that In step 4, the steps of calculating the effective area of ​​the point target using the photometric aperture method include: Where SNR is the optical signal-to-noise ratio, g(i,j) is the pixel grayscale value of any point in the preprocessed image, and DN is background is the background gray value of the preprocessed image, is the background gray value variance of the preprocessed image, DN Th is the grayscale segmentation threshold of the preprocessed image; Traversing DN Th , when SNR is at its maximum value, the corresponding DN Th is the segmentation threshold of the photometric aperture, the photometric aperture when the optical signal-to-noise ratio is the largest is obtained, and the corresponding photometric aperture parameter DN is output (x,y) , (x,y) is the coordinate of the photometric aperture parameters.

7. The method according to claim 6, characterized in that In step 5, the calibration response relationship function is: Where E0 is the inverted luminosity value of the point target, k is the number of pixels occupied by the point target in the preprocessed image, and DN is (x,y) is the photometric aperture parameter, DN background is the background gray value of the preprocessed image, k gain is the slope radiation calibration factor, g Bias is the random error radiation calibration coefficient, α gain k gain Calibration factor coupled to detector pixel size and focal length, β Bias g Bias Calibration factor coupled with detector pixel size and focal length; d is the detector pixel size and f is the camera focal length.

8. The method according to claim 7, characterized in that In step 6, when the real photometric value is available, the error of the inverted photometric value is calculated according to the point target photometric value error model, and the method of converting it into magnitude error includes: The point target photometric value error model is: ΔE obj =E obj -E0 In the formula, ΔE obj is the error of the inverted photometric value, E obj is the real photometric value of the point target, and E0 is the inverted photometric value of the point target; The conversion method for magnitude error is: ΔM=M′-M0 Where ΔM is the magnitude error, M′ is the inverted magnitude of the point target, and M0 is the true magnitude corresponding to M′; 9. The method according to claim 7, characterized in that In step 6, when there is no real photometric value, the standard deviation of the inverted photometric value is calculated according to the point target photometric value error transfer model, and the method of converting it into the magnitude standard deviation includes: The error transfer model of point target photometric value is: In the formula, σ Eobj is the standard deviation of the inverted photometric value, DN (x,y) is the photometric aperture parameter, σ Gain is the standard deviation of the radiation calibration response coefficient, Gain is the gain calibration coefficient, ΔDN (x,y) is the gray value deviation of the point target caused by noise, d is the detector pixel size, and f is the focal length of the camera; Magnitude standard deviation σ m The conversion method is: Where m is the magnitude of the point target.

10. A space-based quantitative measurement device for the photometric properties of a space point target, characterized in that: include: The data analysis module is used to analyze and compress the satellite image data and then transmit the original image obtained by the data transmission system to the ground processing system; An image preprocessing module is used to perform non-uniform correction on the acquired original image and then perform denoising processing through bilateral filtering to obtain a preprocessed image; A dark field value estimation module is used to estimate the dark field value of the preprocessed image by using a majority method, and use the dark field value as the background gray value of the preprocessed image; The star point detection module is used to calculate the effective area of ​​the point target by using the photometric aperture method when a point target is detected in the preprocessed image, obtain the photometric aperture when the optical signal-to-noise ratio is the largest, and output the corresponding photometric aperture parameters, otherwise, directly feedback invalid information; An inversion calculation module is used to input the photometric aperture parameters into the calibration response relationship function to calculate the inverted photometric value of the point target; The error calculation module is used to calculate the error of the inverted photometric value according to the point target photometric value error model when there is a real photometric value, and convert it into the magnitude error; when there is no real photometric value, the standard deviation of the inverted photometric value is calculated according to the point target photometric value error transfer model, and converted into the magnitude standard deviation; the accuracy of the space-based quantitative measurement of the space point target photometric value is evaluated by the magnitude error or the magnitude standard deviation.

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