Space point target luminosity space-based quantitative measurement method and device

Abstract

The invention discloses a spatial point target luminosity space-based quantitative measurement method and a spatial point target luminosity space-based quantitative measurement device, which solve the problem of how to improve the efficiency and the precision of spatial point target luminosity space-based quantitative measurement. Belongs to the photoelectric detection field. Comprising the following steps: performing non-uniform correction and bilateral filtering denoising on an original image to obtain a preprocessed image; estimating a dark field value of the preprocessed image as a background gray value by adopting a mode method; if a point target is detected in the preprocessed image, performing photometric aperture calculation to obtain a photometric aperture when the optical signal-to-noise ratio is maximum, otherwise, directly feeding back invalid information; inputting a photometric aperture parameter into the calibration response relation function, and calculating an inversion photometric value of the point target; and according to the point target luminosity value error model or the point target luminosity value error transmission model, calculating a star magnitude error or a star magnitude standard deviation, and verifying the space point target luminosity space-based quantitative measurement precision. According to the invention, the spatial point target photometric measurement efficiency and precision are improved.

Description

Technical Field

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

[0002] In order to explore and utilize space more effectively, countries around the world have put forward higher requirements for obtaining characterization information and behavioral characteristics of space targets. As an important means of space situational 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, wide-area, and long-distance. The optical properties of space targets are closely related to the changes in the target's spatial position, attitude, and detection angle. At the same time, the material changes of the target during space operation will also cause changes in photometric values. Therefore, accurate and reliable photometric measurement devices and data measurements are particularly critical. Compared with ground-based observations, space-based observations need to focus on and meet the requirements of space illumination, particle radiation, and carrying conditions, and require specific designs 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 observations is also affected by orbits, earth occlusion, ground light conditions, ground shadow conditions, daylight conditions, moonlight conditions, and indirect conditions. It is necessary to avoid direct sunlight and ground air light interference by reasonably planning observation time and angles, and adjusting attitudes.

[0003] Space-based optical detection systems are generally required to have functions such as geometric visibility, optical scattering characteristics, photoelectric effect, orbital parameters and camera pointing calculation, as well as imaging simulation and stray light suppression. They are usually composed of space platforms, optical telescopes, photoelectric sensors, image processors, data storage and transmission devices, etc. Among them, the space platform is used to protect against severe vibrations, micrometeoroid impacts and solar radiation during the launch process. At present, high-performance space-based optical cameras are heavy. With the development of technology, some miniaturized and lightweight space optical cameras have emerged, but most of them are limited to optical imaging and have poor measurement effects. Therefore, in order to design a reliable space-based quantitative measurement device for the photometric measurement of space point targets, it is necessary to consider aspects such as optical lenses, optomechanical structures, electronic systems, and temperature control to ensure that the measurement device works stably and efficiently processes and transmits space image data. Summary of the invention

[0004] In order to solve the technical problem of how to improve the efficiency and accuracy of space-based quantitative measurement of the photometry of space point targets, the present invention proposes a space-based quantitative measurement method and device for the photometry of space point targets, which is helpful to design a lightweight and small space-based photometry measurement device, and can efficiently perform space-based space point target photometry quantitative measurement tasks, effectively improve the efficiency and accuracy of space-based quantitative measurement of the photometry of space point targets, and improve the image data processing capability of space point targets, providing reliable conditions for long-term observation, characteristic grasping and cataloging of targets.

[0005] The purpose of the present invention is specifically achieved through the following technical solutions:

[0006] The present invention discloses a space-based quantitative measurement method of the photometric properties of a space point target, comprising:

[0007] 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;

[0008] 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;

[0009] 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;

[0010] 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.

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

[0012] 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.

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

[0014] 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.

[0015] In step 2, the method of non-uniform correction includes:

[0016]

[0017] 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;

[0018]

[0019] 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;

[0020]

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

[0022]

[0023] In step 2, the bilateral filtering denoising method includes:

[0024]

[0025] 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,

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

[0027]

[0028] 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.

[0029] In step 3, the method of estimating the dark field value of the preprocessed image using the majority method includes:

[0030]

[0031] 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.

[0032] In step 4, the steps of calculating the effective area of ​​the point target using the photometric aperture method include:

[0033]

[0034] 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;

[0035] 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.

[0036] In step 5, the calibration response relationship function is:

[0037]

[0038] 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 coefficient coupled with detector pixel size and focal length; d is the detector pixel size and f is the camera focal length.

[0039] 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:

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

[0041] ΔE obj =E obj -E0

[0042] 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;

[0043] The conversion method for magnitude error is:

[0044] ΔM=M′-M0

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

[0046]

[0047] 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:

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

[0049]

[0050] In the formula, 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;

[0051] Magnitude standard deviation σ m The conversion method is:

[0052]

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

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

[0055] 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;

[0056] 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;

[0057] 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;

[0058] 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;

[0059] 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;

[0060] 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.

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

[0062] Through a space-based quantitative measurement method and device for the photometric measurement of a space point target disclosed by the present invention, non-uniform correction and bilateral filtering denoising are used to effectively suppress interference caused by the detector itself and stray light in the space scene, obtain a pre-processed image, use the majority method to estimate the dark field value of the pre-processed image, and use the dark field value as the background gray value of the pre-processed image, thereby reducing the deviation caused by cosmic rays, galaxies, bright stars, etc.; for the pre-processed image, the photometric aperture method is used to calculate the effective area of ​​the target, and the photometric aperture obtained when the optical signal-to-noise ratio is the maximum 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 transmission model, the magnitude error or the magnitude standard deviation is calculated, and the space-based quantitative measurement accuracy of the photometric measurement of the space point target is evaluated. The present invention can be directly applied to a space-based onboard photometric measurement device, efficiently perform space-based space point target photometric quantitative measurement tasks, and improve the efficiency and accuracy of space point target photometric measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The present invention is further described in detail below based on the accompanying drawings and embodiments.

[0064] Figure 1 Schematic diagram of the relationship between point target and observation distance.

[0065] Figure 2 Schematic diagram of the error of the inverted photometric value under laboratory conditions.

[0066] Figure 3 Schematic diagram of the error in inverted photometric values ​​under space-based observation of stars. DETAILED DESCRIPTION

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

[0068] 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.

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

[0070] Non-uniform correction, that is, under the condition of uniform light irradiation and non-saturation of each pixel, the error of gray value output by each pixel due to inconsistent response is counted. Since background noise and bad pixels in the space target images taken by the onboard device will affect the measurement accuracy, the present invention uses bilateral filtering to remove noise, which can effectively filter out noise, protect image edges, eliminate the non-uniformity caused by different environmental responses of each pixel, temperature and various levels of amplifier circuits, and thus eliminate the internal deviation of the device.

[0071] 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.

[0072] Ideally, the histogram is solved for its center after one-dimensional Gaussian fitting. The center value is the point with the highest frequency of background grayscale values, and 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 grayscale mean, median and histogram peak (mode) are not the same. Therefore, the present invention uses the mode method 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, 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, that is, to determine an optimal segmentation threshold and output the corresponding photometric aperture parameters, otherwise, directly feedback invalid information;

[0074] Step 5: Input the photometric aperture parameters into the calibration response relationship function to calculate the inverted photometric value of the point target;

[0075] 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.

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

[0077] 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.

[0078] In step 2, the method of 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 grayscale of the preprocessed image, and mean is the mean of the background grayscale of the preprocessed image.

[0095] In step 4, the steps of calculating the effective area of ​​the point target using the photometric aperture method include:

[0096]

[0097] 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;

[0098] 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.

[0099] In step 5, the calibration response relationship function is:

[0100]

[0101] 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, reflecting the slope, g Bias is the random error radiation calibration coefficient, reflecting the random error, α gain k gain Calibration factor coupled to detector pixel size and focal length, β Bias g Bias Calibration coefficient coupled with detector pixel size and focal length; d is the detector pixel size and f is the camera focal length.

[0102] 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:

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

[0104] ΔE obj =E obj -E0

[0105] 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;

[0106] The conversion method for magnitude error is:

[0107] ΔM=M′-M0

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

[0109]

[0110] In step 6, when there is no real photometric value, within the linear range of the detector, when the grayscale value DN of the point target is high, the dark current noise, readout noise and background noise can be ignored compared with the shot noise. In this method, the measurement error of the radiation calibration coefficient and the noise error coupled with the target signal are mainly considered. Then, the standard deviation of the inverted photometric value is calculated according to the error transfer model of the point target photometric value, and the method of converting it into the standard deviation of the magnitude includes:

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

[0112]

[0113] In the formula, 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;

[0114] Magnitude standard deviation σ m The conversion method is:

[0115]

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

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

[0118] 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;

[0119] 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;

[0120] 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;

[0121] 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;

[0122] 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;

[0123] 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.

[0124] Application examples:

[0125] When the satellite orbit and the state of the space-based quantitative measurement device for the photometric measurement of a space point target disclosed in the present invention are determined, the observation distance and phase angle can be basically determined, and the factors affecting the apparent magnitude of the target are mainly the size of the point target and the reflectivity. For the moving point target detection system, a small detector pixel size is beneficial to improving the angle measurement accuracy, but it will reduce the residence 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 GMAX3265 chip of Gpixel is selected as the detector.

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

[0127] See also Figure 2 , under laboratory conditions, the error of the inverted photometric value is Figure 2 shown.

[0128] See also Figure 3 Under the condition of space-based observation of stars, the error of the inverted luminosity value is as follows: Figure 3 shown.

[0129] The accuracy evaluation of space-based quantitative photometric measurements of space point targets was carried out under two conditions: laboratory and space-based observation of stars:

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

[0131] Table 1

[0132]

[0133]

[0134]

[0135] 40 photos were collected at 10ms exposure time and 5Mv illumination, and the error of the inverted photometric value was calculated. It can be obtained that the magnitude error under 5Mv illumination is ±0.1Mv. The error of the inverted photometric value is as follows: Figure 2 shown.

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

[0137] The HR7950 star is selected as the photometric evaluation benchmark. The following conditions must be met: the radiation flux is stable; the peak wavelength of the radiation is close to 0.55μm, and the spectrum type is G type. The HR7950 star is selected as the radiation benchmark. The wavelength flux curve is as follows: Figure 3 The magnitude errors of HR7950 stars are shown in Table 2.

[0138] Table 2

[0139] Test No. 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:

[0141] Through a space-based quantitative measurement method and device for the photometric measurement of a space point target disclosed by the present invention, non-uniform correction and bilateral filtering denoising are used to effectively suppress interference caused by the detector itself and stray light in the space scene, obtain a pre-processed image, use the majority method to estimate the dark field value of the pre-processed image, and use the dark field value as the background gray value of the pre-processed image, thereby reducing the deviation caused by cosmic rays, galaxies, bright stars, etc.; for the pre-processed image, the photometric aperture method is used to calculate the effective area of ​​the target, and the photometric aperture obtained when the optical signal-to-noise ratio is the maximum 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 transmission model, the magnitude error or the magnitude standard deviation is calculated, and the space-based quantitative measurement accuracy of the photometric measurement of the space point target is evaluated. The present invention can be directly applied to a space-based onboard photometric measurement device, efficiently perform space-based space point target photometric quantitative measurement tasks, and improve the efficiency and accuracy of space point target photometric measurement.

[0142] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the 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, 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 photometric 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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