Method for correcting dust on focal plane of super-large array space camera

Abstract

The application discloses a method for correcting dust on a focal plane of a super-large area array space camera, which takes the irradiance distribution of an on-orbit calibration device of the super-large area array space camera as a reference, compares an image of the on-orbit calibration device with an image of a laboratory calibration device, obtains the variation of a pixel of the super-large area array space camera in orbit, and applies the variation to a laboratory relative correction coefficient to obtain an on-orbit relative correction coefficient. In addition, the application also proposes that a uniform image obtained by the on-orbit calibration device is used to detect the position of the dust, so as to make up for the defects of the existing method in practical application. The on-orbit relative calibration method improves the calibration precision, reduces the calibration cost, and guarantees the precision of subsequent absolute radiation correction and inversion.

Description

Technical Field

[0001] This invention relates to a method for correcting moving dust on the focal plane of an ultra-large area array space camera, belonging to the field of optical remote sensing science and technology. Background Technology

[0002] The purpose of relative radiometric correction for space optical cameras is to remove detector-level errors caused by differences in the response of individual pixels in the sensor itself. It is an important way to improve the radiometric quality of satellites. Its uncertainty can be transferred to absolute radiometric correction, affecting the correction accuracy and inversion accuracy.

[0003] Currently, the internationally accepted methods for calibrating on-orbit space cameras mainly include dark current calibration, which is commonly used in foreign remote sensing satellite cameras, such as SPOT5, Landsat8, and WorldView series satellite cameras; and relative gain calibration (which is mainly divided into on-board calibration device calibration, on-orbit uniform field calibration, and statistical calibration), which is widely used in remote sensing cameras both domestically and internationally.

[0004] Onboard calibration devices typically use calibration lamps or diffuse reflectors as uniform surface light sources to perform on-orbit relative radiometric calibration of space cameras. For example, the ALOS satellite used its onboard calibration lamps for on-orbit relative radiometric calibration, while the MODISAqua satellite used its onboard diffuse reflectors. However, these two methods are difficult to apply to the calibration of large-aperture, wide-field-of-view remote sensors.

[0005] The relative calibration method based on uniform fields is only applicable to remote sensors with narrow fields of view. For large-area array space cameras with wide fields of view, it is impossible to find a uniform field on the ground that can fill the camera's field of view. On the other hand, relative calibration based on statistical methods requires massive amounts of remote sensing satellite image data, which affects the timeliness of relative calibration.

[0006] A large-area array camera, due to its large detector area and unsealed front lens barrel, encountered dust during camera assembly, adjustment, and launch. This dust adhered to the cover plate of the focal plane detector, shifted, and detached, ultimately resulting in black or grayish-white dust shadows on the images. Statistics show that over ten new or moving dust spots appeared on a 10K*10K focal plane detector, ranging in size from tens to hundreds of pixels, appearing as grayish-black or grayish-white circular or flocculent patches. These patches first affected the relative radiometric correction accuracy, causing a local decrease in relative radiometric correction accuracy of 0.1%–0.5%. Secondly, these patches reduced the accuracy of ground feature classification and target detection rate. Traditional correction methods mainly address inconsistencies between pixels, between images, and inconsistencies caused by slow changes in devices after orbit insertion, but cannot solve the inconsistencies caused by new and moving dust on the focal plane.

[0007] Currently, the laboratory calibration data mainly used in orbit to correct in-orbit images increases the non-uniformity of the images. In addition, this method requires first calculating the irradiance distribution of the calibration component on the camera focal plane, and then using this distribution to calculate the on-board relative calibration coefficients. The calibration link is long, which will affect the final relative calibration accuracy. Therefore, the applicability of this method is limited. Summary of the Invention

[0008] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a correction method for moving dust on the focal plane of an ultra-large area array space camera. This solves the problem that existing on-orbit relative correction methods for space cameras cannot address the correction of newly added or moving dust areas on the camera's focal plane, and obtains a stable relative correction coefficient that can be used for a long time.

[0009] The technical solution of this invention is:

[0010] This invention discloses a method for correcting moving dust on the focal plane of an ultra-large area array space camera, comprising:

[0011] Using on-board calibration equipment, several frames of high-brightness uniform images and low-brightness uniform images of a large-area array space camera were obtained under different imaging parameters.

[0012] The arithmetic mean of several frames of high-brightness uniform images and low-brightness uniform images is calculated to obtain high-brightness average images and low-brightness average images, respectively.

[0013] Edge extraction is performed on the high-brightness average image to obtain the dust area image;

[0014] Calculate the rate of change of each pixel in the dust region image based on the high-brightness average image and the low-brightness average image;

[0015] Calculate the correction coefficient for the dust area image based on the rate of change;

[0016] By using the correction coefficients of the dust area image, the corrected on-orbit image is obtained.

[0017] Furthermore, in the above method, the specific method for extracting edges from the high-brightness average image to obtain the dust region image is as follows:

[0018] Calculate the gradient intensity and direction of each pixel in the high-brightness average image;

[0019] Based on the gradient intensity and direction of each pixel, non-edge points in the on-orbit high-brightness uniform image are removed to obtain edge points;

[0020] By using double thresholding, edge points are connected to obtain an image of the dusty area.

[0021] Furthermore, in the above method, the calculation of the gradient intensity and direction of each pixel in the high-brightness average image specifically involves:

[0022] G(i,j) x =[MI orb_H (i+1,j-1)+2*MI orb_H (i+1,j)+MI orb_H (i+1,j+1)]

[0023] -[MI orb_H (i-1,j-1)+2*MI orb_H [(i-1,j)]+MI orb_H (i-1,j+1)]

[0024] G(i,j) y =[MI orb_H (i-1,j-1)+2*MI orb_H (i,j-1)+MI orb_H (i+1,j-1)]

[0025] -[MI orb_H (i-1,j+1)+2*MI orb_H (i,j+1)+MI orb_H (i+1,j+1)]

[0026]

[0027] Among them, MI orb_H Let G(x) be the average in-orbit highlighted image, G(x) be the horizontal gradient intensity of each pixel in the average in-orbit highlighted image, G(x) be the vertical gradient intensity of each pixel in the average in-orbit highlighted image, G be the total gradient intensity of each pixel in the average in-orbit highlighted image, and θ be the gradient direction of each pixel in the average in-orbit highlighted image.

[0028] Furthermore, in the above method, the step of removing non-edge points from the on-orbit high-brightness uniform image based on the gradient intensity and direction of each pixel to obtain edge points specifically involves:

[0029]

[0030] Where, I(i,j) orb_dust The image is marked with dust, where dusty areas are represented by 1 and non-dusty areas by 0.

[0031] Furthermore, in the above method, calculating the rate of change of each pixel in the dust region image specifically involves:

[0032]

[0033] Among them, MIorb_H MI is the average value of a high-brightness image. orb_L For low-brightness averaged images, I lab_calib_H For laboratory calibration of highlighted images, I lab_calib_L For calibrating low-brightness images in the laboratory, I lab_dark For laboratory dark current images, K lab and B lab Let R(i,j) be the laboratory correction coefficient. orb_H R(i,j) represents the average rate of change of the highlighted image. orb_L The average rate of change of low-brightness image, R(i,j) is the average rate of change.

[0034] Furthermore, in the above method, the calculation of the correction coefficient for the dust area image specifically involves:

[0035] K orb (i, j) = K lab (i, j)*R orb (i, j)

[0036] B orb (i, j) = B lab (i, j)*R orb (i, j)

[0037] Among them, K lab and B lab R is the laboratory correction factor. orb (i, j) represents the average rate of change.

[0038] Furthermore, in the above method, the step of obtaining the corrected on-orbit image using the correction coefficients of the dust region image specifically involves:

[0039] PI orb (i, j) = K orb (i, j)*PI orb_ori (i, j) + B orb (i, j)

[0040] Among them, PI orb (i, j) represents the corrected on-orbit image, K orb (i, j) and B orb (i, j) are the correction coefficients for the dust area image, PI orb_ori These are images taken in orbit.

[0041] The advantages of this invention over the prior art are as follows:

[0042] (1) The present invention uses a combination of Candy edge detection technology and on-board calibration device to determine the position of moving dust on the camera focal plane, and uses on-board calibration device to calculate the brightness change rate of the moving dust area on the focal plane. Based on this, the laboratory calibration coefficient of the area is corrected, which can achieve the technical effect of correcting the decrease in local relative radiometric correction accuracy and solve the problem that the current laboratory calibration data cannot adapt to the changes of moving dust on the camera focal plane, thus increasing the non-uniformity of the image.

[0043] (2) The present invention uses a multi-frame (10 frames) averaging method to adjust the noise at the dust edge, which effectively improves the edge detection accuracy.

[0044] (3) The dust correction method for the focal plane of a large array space camera based on the on-board calibration device of the present invention can effectively solve the problem of the decrease in the accuracy of the correction result caused by the addition or movement of dust in the orbit of the large array space camera, eliminate the image noise caused by the uncorrelated pixels in the dust area, and improve the correction accuracy and image quality.

[0045] (4) The focal plane dust correction method of the present invention can effectively remove dust pollution on remote sensing satellite images of the earth, make up for the defects of existing methods in practical applications, and also provide new ideas for image correction of other types of space cameras.

[0046] (5) This invention only corrects the laboratory calibration data of the moving dust area of ​​the camera focal plane. It can improve the calibration and application accuracy through data processing without adding hardware equipment. Attached Figure Description

[0047] Figure 1 This is a flowchart of the testing method of the present invention. Detailed Implementation

[0048] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] This invention discloses a method for correcting moving dust on the focal plane of an ultra-large area array space camera, comprising:

[0050] Using on-board calibration equipment, several frames of high-brightness uniform images and low-brightness uniform images of a large-area array space camera were obtained under different imaging parameters.

[0051] The arithmetic mean of several frames of high-brightness uniform images and low-brightness uniform images is calculated to obtain high-brightness average images and low-brightness average images, respectively.

[0052] Edge extraction is performed on the high-brightness average image to obtain the dust area image;

[0053] Calculate the rate of change of each pixel in the dust region image based on the high-brightness average image and the low-brightness average image;

[0054] Calculate the correction coefficient for the dust area image based on the rate of change;

[0055] By using the correction coefficients of the dust area image, the corrected on-orbit image is obtained.

[0056] Preferably, edge extraction is performed on the high-brightness average image to obtain the dust area image. The specific method is as follows:

[0057] Calculate the gradient intensity and direction of each pixel in the high-brightness average image;

[0058] Based on the gradient intensity and direction of each pixel, non-edge points in the on-orbit high-brightness uniform image are removed to obtain edge points;

[0059] By using double thresholding, edge points are connected to obtain an image of the dusty area.

[0060] Preferably, the gradient intensity and direction of each pixel in the high-brightness average image are calculated, specifically as follows:

[0061] G(i,j) x =[MI orb_H (i+1,j-1)+2*MI orb_H (i+1,j)+MI orb_H (i+1,j+1)]

[0062] -[MI orb_H (i-1,j-1)+2*MI orb_H [(i-1,j)]+MI orb_H (i-1,j+1)]

[0063] G(i,j) y =[MI orb_H (i-1,j-1)+2*MI orb_H (i,j-1)+MI orb_H (i+1,j-1)]

[0064] -[MI orb_H (i-1,j+1)+2*MI orb_H (i,j+1)+MI orb_H (i+1,j+1)]

[0065]

[0066] Among them, MI orb_HLet G(x) be the average in-orbit highlighted image, G(x) be the horizontal gradient intensity of each pixel in the average in-orbit highlighted image, G(x) be the vertical gradient intensity of each pixel in the average in-orbit highlighted image, G be the total gradient intensity of each pixel in the average in-orbit highlighted image, and θ be the gradient direction of each pixel in the average in-orbit highlighted image.

[0067] Preferably, based on the gradient intensity and direction of each pixel, non-edge points in the on-orbit high-brightness uniform image are removed to obtain edge points, specifically:

[0068]

[0069] Where, I(i,j) orb_dust The image is marked with dust, where dusty areas are represented by 1 and non-dusty areas by 0.

[0070] Preferably, the rate of change of each pixel in the dust region image is calculated, specifically as follows:

[0071]

[0072] Among them, MI orb_H MI is the average value of a high-brightness image. orb_L For low-brightness averaged images, I lab_calib_H For laboratory calibration of highlighted images, I lab_calib_L For calibrating low-brightness images in the laboratory, I lab_dark For laboratory dark current images, K lab and B lab Let R(i,j) be the laboratory correction coefficient. orb_H R(i,j) represents the average rate of change of the highlighted image. orb_L The average rate of change of low-brightness image, R(i,j) is the average rate of change.

[0073] Preferably, the correction coefficients for the image of the dusty area are calculated as follows:

[0074] B orb (i, j) = K lab (i, j)*R orb (i, j)

[0075] B orb (i, j) = B lab (i, j)*R orb (i, j)

[0076] Among them, K lab and B lab R is the laboratory correction factor. orb (i, j) represents the average rate of change.

[0077] Preferably, the corrected on-orbit image is obtained using the correction coefficients of the dust area image, specifically as follows:

[0078] PI orb (i, j) = K orb (i, j)*PI orb_ori (i, j) + B orb (i, j)

[0079] Among them, PI orb (i, j) represents the corrected on-orbit image, K orb (i, j) and B orb (i, j) are the correction coefficients for the dust area image, PI orb_ori These are images taken in orbit.

[0080] Example

[0081] Relative radiometric calibration removes errors caused by differences in response of the sensor elements themselves, so that different pixels have a consistent output response under the same radiation input. It is a key step in unifying the radiation reference of each sensor element, and its accuracy will be transferred to absolute radiometric calibration, increasing the uncertainty of absolute radiometric calibration.

[0082] The inhomogeneity between pixels in a focal plane array detector is unavoidable, resulting in inconsistent output responses from different pixels under the same input radiation. Relative radiometric calibration is a crucial step in bringing the imaging reference back to consistency. The accuracy of inhomogeneity correction affects the accuracy of subsequent absolute radiometric calibration, introducing additional uncertainty into absolute radiometric calibration. The causes of these differences in responsivity and bias between pixels include: manufacturing process level, inherent non-uniformity of the components, and errors in the processing and assembly of the optical system. For ultra-large area array space cameras, due to the large detector area and the lack of a sealed front lens barrel, dust can enter and adhere to the cover plate of the focal plane detector during camera assembly and launch. During launch and in orbit, this dust detaches and shifts, rendering the relative calibration coefficients acquired in the laboratory at the original dust location inapplicable in that area. Ultimately, this results in black or grayish-white dust shadows in the image, severely impacting the accuracy of relative radiometric correction.

[0083] Currently, on-orbit non-uniformity correction for large-area space cameras mainly includes dark current correction, laboratory integrating sphere correction, on-board calibration device correction, on-orbit uniform field correction, and statistical correction. Each of these methods has its limitations: dark current correction can only effectively correct response non-uniformity when there is no light entering the pupil; laboratory integrating sphere correction has good stability in the visible light range, but cannot correct for large changes in local areas after launch and orbit insertion; on-orbit uniform field correction can only correct small-field space cameras, and it is difficult to find a uniform field with a single type of ground feature for large-area, large-field cameras; statistical correction is only suitable for non-uniformity correction of small-area or linear pushbroom cameras. None of the above methods can effectively solve the problem of moving dust on the focal plane during the assembly, adjustment, and launch of ultra-large-area space cameras.

[0084] Therefore, this embodiment combines laboratory integrating sphere correction data and the dust correction method for the moving focal plane of a large-area space camera in the on-orbit calibration field. It utilizes the stable irradiance distribution generated by the on-board calibration components on the camera focal plane during on-orbit operation, and establishes a change mapping by combining it with laboratory integrating sphere correction data to obtain the non-uniformity correction data of the local area.

[0085] like Figure 1 As shown, the method for correcting moving dust on the focal plane of a large-area array space camera provided in this embodiment includes the following steps:

[0086] (1) Turn off the on-board calibration lamps and acquire the on-orbit dark current image I. orb_dark 1 frame,

[0087] (2) Turn on the calibration lamp on the satellite, adjust the parameters to 60% full-well under a certain parameter, sample 10 frames, acquire a high-brightness uniform image and perform an arithmetic average to obtain the image MI. orb_H ;

[0088] (3) Adjust the parameters to 30% full-well under a certain parameter, sample 10 frames, acquire a low-brightness uniform image and perform an arithmetic average to obtain the image MI. orb_L ;

[0089] (4) Given the laboratory calibration image I under certain parameters lab_calib_H (mean is 60% full trap), I lab_calib_L (mean value is 30% full well), Dark current image I lab_dark Laboratory correction factor K lab and B lab ;

[0090] (5) Using the Candy algorithm, the image MI orb_H Perform edge extraction:

[0091] (5.1) Using the Sobel operator, the gradients in the x-axis and y-axis directions are obtained, and the gradient intensity and direction of each pixel are calculated.

[0092] G(i,j) x =[MI orb_H (i+1,j-1)+2*MI orb_H (i+1,j)+MI orb_H (i+1,j+1)]

[0093] -[MI orb_H (i-1,j-1)+2*MI orb_H [(i-1,j)]+MI orb_H (i-1,j+1)]

[0094] G(i,j) y =[MI orb_H (i-1,j-1)+2*MI orb_H (i,j-1)+MI orb_H (i+1,j-1)]

[0095] -[MI orb_H (i-1,j+1)+2*MI orb_H (i,j+1)+MI orb_H (i+1,j+1)]

[0096]

[0097] Among them, MI orb_H Let G(x) be the average in-orbit highlighted image, G(x) be the horizontal gradient intensity of each pixel in the average in-orbit highlighted image, G(x) be the vertical gradient intensity of each pixel in the average in-orbit highlighted image, G be the total gradient intensity of each pixel in the average in-orbit highlighted image, and θ be the gradient direction of each pixel in the average in-orbit highlighted image.

[0098] (5.2) Using dual threshold detection, non-edge points are removed, and edge connection processing is performed to obtain the dust area image I. orb_dust and I orb_dust The pixel value of the dust area is marked as 1, and the pixel value of the rest is marked as 0;

[0099]

[0100] I(i,j) orb_dust The image is marked with dust, where dusty areas are represented by 1 and non-dusty areas by 0.

[0101] (6) Calculate the rate of change of the dust area point by point:

[0102]

[0103] R orb (i, j) = (R) orb_H (i, j) + R orb_L (i, j) / 2

[0104] Among them, MI orb_H To highlight the average image, MI orb_L For low-brightness average images, I lab_calib_H For laboratory calibration of highlighted images, I lab_calib_L For calibrating low-brightness images in the laboratory, I lab_dark For laboratory dark current images, K lab and B lab Let R(i,j) be the laboratory correction coefficient. orb_H R(i,j) represents the average rate of change of the highlighted image. orb_L The average rate of change of low-brightness image, R(i,j) is the average rate of change.

[0105] (7) Calculate the correction coefficient for each dust area:

[0106] K orb (i, j) = K lab (i, j)*R orb (i, j)

[0107] B orb (i, j) = B lab (i, j)*R orb (i, j)

[0108] Among them, K lab and B lab R is the laboratory correction factor. orb (i, j) represents the average rate of change.

[0109] (8) Update the laboratory correction coefficients at the dust location and use the new correction coefficients to correct the on-orbit image PI. orb_ori :

[0110] PI orb (i, j) = K orb (i, j)*PI orb_ori (i, j) + B orb (i, j)

[0111] Among them, PI orb (i, j) represents the corrected on-orbit image, K orb (i, j) and B orb (i, j) are the correction coefficients for the dust area image, PI orb_ori These are images taken in orbit.

[0112] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

[0113] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for correcting dust on a focal plane of a super large array space camera, characterized in that, include: Using on-board calibration equipment, several frames of high-brightness uniform images and low-brightness uniform images of a large-area array space camera were obtained under different imaging parameters. The arithmetic mean of several frames of high-brightness uniform images and low-brightness uniform images is calculated to obtain high-brightness average images and low-brightness average images, respectively. Edge extraction is performed on the high-brightness average image to obtain the dust area image; Calculate the rate of change of each pixel in the dust region image based on the high-brightness average image and the low-brightness average image; Calculate the correction coefficient for the dust area image based on the rate of change; By using the correction coefficients of the dust area image, the corrected on-orbit image is obtained; The method for extracting edges from the high-brightness average image to obtain the dust region image is as follows: Calculate the gradient intensity and direction of each pixel in the high-brightness average image; Based on the gradient intensity and direction of each pixel, non-edge points in the on-orbit high-brightness uniform image are removed to obtain edge points; By using a double threshold, edge points are connected to obtain an image of the dusty area; The calculation of the gradient intensity and direction of each pixel in the high-brightness average image is specifically as follows: wherein, is the on-orbit high-light average image, is the transverse gradient intensity of each pixel of the on-orbit high-light average image, is the longitudinal gradient intensity of each pixel of the on-orbit high-light average image, is the total gradient intensity of each pixel of the on-orbit high-light average image, is the gradient direction of each pixel of the on-orbit high-light average image; The calculation of the rate of change of each pixel in the dust region image is specifically as follows: in, The average value of the high-brightness image. For low-brightness average images, Highlight the image for laboratory calibration. To calibrate low-brightness images for the laboratory, This is a laboratory dark current image. and This is the laboratory correction factor. The average image change rate is highlighted. Average image change rate in low brightness This represents the average rate of change.

2. The method for correcting moving dust on the focal plane of a large-area array space camera according to claim 1, characterized in that, The process of removing non-edge points from the on-orbit high-brightness uniform image based on the gradient intensity and direction of each pixel to obtain edge points is as follows: in, The image is marked with dust, where dusty areas are represented by 1 and non-dusty areas by 0.

3. The method for correcting moving dust on the focal plane of a large-area array space camera according to claim 1, characterized in that, The correction coefficients for calculating the dust region image are specifically as follows: in, and This is the laboratory correction factor. This represents the average rate of change.

4. The method for correcting moving dust on the focal plane of a large-area array space camera according to claim 1, characterized in that, The process of obtaining the corrected on-orbit image using the correction coefficients of the dust region image is as follows: in, The corrected on-orbit image. and The correction coefficients for the dusty area image are: These are images taken in orbit.

Images