Method for improving large-scale star orbit mask calculation efficiency
By constructing and rotating the mask base plate, the final star trail mask is generated, which solves the problems of low processing efficiency and insufficient accuracy of space target observation against dense star backgrounds, and realizes efficient target detection and image analysis.
Patent Information
- Application Number
- CN202511874657.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-12
- Publication Date
- 2026-02-27
AI Technical Summary
In space target observation, due to the presence of dense stellar backgrounds, existing technologies suffer from low processing efficiency, high computational cost, easy destruction of target information, and insufficient accuracy, resulting in low image processing efficiency, high false alarm rate, and high missed identification rate.
By constructing a mask base plate with the same size as the original observation image, performing rotation and dilation operations along the star trail direction, followed by inverse rotation and cropping, the final star trail mask is generated.
It significantly improves the processing efficiency of target detection and image analysis. The algorithm has a simple structure, fast calculation speed, wide applicability, and can effectively suppress stellar background interference.
Smart Images
Figure CN121582071A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of space target observation technology, and specifically to a method for improving the computational efficiency of large-scale star orbit masking. Background Technology
[0002] In the field of space target observation, accurately extracting space targets from images acquired by telescopes is a crucial task. However, the presence of dense stellar backgrounds within the field of view can significantly interfere with target detection and identification, severely impacting the efficiency and accuracy of the extraction process. This is especially true in high-sensitivity telescope systems, where enhanced detection capabilities often result in the presence of tens of thousands of stars within the field of view, forming a vast number of star trails. Removing these trails one by one would not only be computationally expensive but also significantly reduce image processing efficiency.
[0003] Currently, the processing of stars in space target detection data mainly employs image processing techniques, including frame differencing and masking methods. Frame differencing relies on processing multiple consecutive frames of images. Without precise star registration, additional noise is introduced; image registration increases the computational load during frame differencing. Slight jitter on the satellite platform can also lead to additional residual noise at star edges. Masking methods, in practice, often use fixed thresholds. While image filtering or morphological operations can remove residual noise, these operations can destroy target information in the original image. Both frame differencing and masking methods are image processing techniques, and their overall drawback is their reliance on the level of image recognition algorithms. Low processing efficiency, high false alarm rate, and high false negative rate are all shortcomings of these methods.
[0004] To improve the accuracy of star trail mask calculations, high-precision star catalogs can be used for matching, then the positions of all star trails can be inverted, star trail masks can be generated for each trail, and then these masks can be superimposed to obtain the final star trail mask. Because space target detection images are large (typically in the tens of millions of pixels), each star trail mask is also very large; merging thousands of large masks will severely impact computational efficiency. Alternatively, mask image downsampling can be used to reduce the mask size, but downsampling leads to low computational accuracy and a jagged star trail mask. Summary of the Invention
[0005] For existing space target observations, constant Star trail processing techniques suffer from low efficiency, high computational cost, easy destruction of target information, and insufficient accuracy. This invention proposes a method to improve the computational efficiency of large-scale star trail masking. This method is used to quickly remove dense star trails in space target observation image processing, thereby improving the overall performance and processing speed of target extraction.
[0006] The method includes the following steps: S1. In a two-dimensional coordinate system, from the origin... Starting from the observed image size, construct the original mask base plate; S2, rotate the original mask base around the origin. Rotate clockwise according to the tilt direction of the star trail to obtain a rotating mask base, and expand around the rotating mask base to obtain a rotating canvas; S3, Solving for the first [missing information] in the original mask base plate After the star trails are processed in step S2, the star trail mask is rotated in the canvas. , Indicates the total number of stars; S4. Calculate according to the calculation method in step S3. A star orbit mask is used to obtain a rotating star orbit mask; S5. Perform an inverse rotation transformation on the rotating star trail mask, and expand it around the rotated canvas after the inverse transformation to obtain the inverse transformation canvas. S6. Crop the expanded portion of the rotated and inverse transformed canvas to obtain the final star trail mask.
[0007] Furthermore, the original mask base is the same size as the observed image, and the coordinate system of the original mask base is [coordinate system not specified]. .
[0008] Furthermore, in step S2, the clockwise rotation angle of the original mask base plate The angle of inclination of the star trail.
[0009] Furthermore, in step S2, the four edges of the rotated canvas respectively contain the four vertices of the rotated mask base, and the coordinate system of the rotated canvas is... .
[0010] Furthermore, in step S3, the first The boundary of a star orbit mask in a rotating canvas is calculated as follows: , , , ,in, and They represent the first A stellar orbit mask in The lower and upper boundaries along the axis. and and They represent the first A stellar orbit mask in The lower and upper boundaries along the axis. This represents the floor function. This represents the floor function. and These represent the length and width of the star trails, respectively. Indicates the size of the rotated canvas. Indicates the first The star orbits in Coordinates in a coordinate system This represents the function that takes the minimum value. This represents the function that takes the maximum value.
[0011] Furthermore, in step S4, nested loops are used to calculate sequentially, based on the calculation method in step S3. A star orbit mask is obtained by rotating the star orbit mask.
[0012] Furthermore, in step S5, the inverse rotation transformation specifically involves rotating around the origin. Rotate counterclockwise in the direction opposite to the tilt of the star orbit, the angle of which is . .
[0013] Furthermore, in step S5, the four edges of the inverse transformation canvas each contain the four vertices of the rotated canvas after the inverse transformation, and the coordinate system of the inverse transformation canvas is... .
[0014] The beneficial effects of the method described in this invention are as follows: The method described in this invention first constructs a mask base plate with the same size as the original observed image. Then, the mask base plate is rotated along the star orbit direction, and the origin position of the rotated mask base plate in the world coordinate system is determined. Next, based on the inverted star point coordinates, the star orbit region is expanded in the form of an axis-aligned rectangle to achieve effective coverage of the star orbit region. Finally, an inverse rotation transformation is performed on the mask base plate, and the automatically expanded canvas area caused by the two rotation operations is cropped, thus obtaining the final mask result with the same size as the original image.
[0015] The method described in this invention can quickly perform masking processing on star trails in images, effectively suppressing the interference of dense stellar backgrounds on space target extraction, thereby significantly improving the processing efficiency of target detection and image analysis. This method has advantages such as simple algorithm structure, fast computation speed, and wide applicability, and can provide an efficient and reliable image preprocessing means for fields such as space target observation, inter-satellite target detection, and space debris identification. Attached Figure Description
[0016] Figure 1 This is a schematic diagram of the mask base plate rotation transformation described in this invention; Figure 2 This is a schematic diagram showing how the star trails described in this invention are transformed into axis-aligned rectangles in a rotating mask base plate; Figure 3 This is a schematic diagram of the inverse transformation of the rotating star-orbit mask described in this invention; Figure 4 This is a partial schematic diagram of the original observation image described in this invention; Figure 5 This is a schematic diagram of the rotating mask base plate described in this invention; Figure 6 This is a schematic diagram of the rotating star track mask described in this invention; Figure 7 This is a schematic diagram of the final star trail mask described in this invention; Figure 8 This is a schematic diagram of the processed space target observation image described in this invention. Detailed Implementation
[0017] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0018] Example 1 This embodiment provides a method to improve the computational efficiency of large-scale star trail masks.
[0019] S1. In a two-dimensional coordinate system, from the origin... Starting from the observed image size, construct the original mask base plate; Since the star trail mask is ultimately applied to the image that needs to be processed, therefore, as Figure 1 As shown, in a two-dimensional coordinate system, the size of the observed image is first determined... Construct an original mask base (chessboard pattern illustration). The original mask base has the same size as the observed image, and the coordinate system of the original mask base is [coordinate system not specified]. .
[0020] S2, rotate the original mask base around the origin. Rotate clockwise according to the tilt direction of the star trail to obtain a rotating mask base, and expand around the rotating mask base to obtain a rotating canvas; like Figure 1 As shown, the original mask base plate is around the origin. Rotate clockwise along the direction of the star trail tilt to obtain the rotating mask base. The clockwise rotation angle of the original mask base is... The tilt angle of the star trails. It can be obtained by statistically analyzing star trails identified from images.
[0021] like Figure 1As shown, to ensure no information is lost, the canvas is expanded around the rotating mask base to obtain a rotating canvas, which becomes the gray shaded area O′ABC in the image. The dimensions of the rotating canvas are... The solution can be found based on geometric relationships: , ,in, This represents the floor function, used to ensure the integrity of the expanded canvas. The four sides of the rotated canvas contain the four vertices of the rotated mask base. The coordinate system of the rotated canvas is... .
[0022] S3, Solving for the first [missing information] in the original mask base plate After the star trails are processed in step S2, the star trail mask is rotated in the canvas. , Indicates the total number of stars; To determine the pixel coordinates of any point in the original mask base within the rotated mask base, in addition to the coordinate transformation caused by the rotation transformation, there is also a displacement transformation OO′ caused by the canvas expansion. Therefore, it is necessary to determine the origin of the original mask base. In the coordinate system of the rotating mask base plate The position in the middle.
[0023] according to Figure 1 The geometric relationships within the equations make it easy to obtain the origin. exist The coordinates of the direction are: ; origin exist The coordinates of the direction are: ; Transform the retrieved star coordinates to the rotating mask base coordinate system, and perform dilation in the form of an axis-aligned rectangle: Stellar coordinate inversion occurs In the coordinate system, assume the first The center coordinates of the star orbits are The width of the star trails is , length is (The length of a star trail can be calculated based on the information of relatively bright star trails identified in a star chart, while the width of a star trail can be calculated based on the length of the star trail, the magnitude of the star, and the parameters of the optical system.)
[0024] Then the first The center coordinates of the star orbits are in the coordinate system of the rotating mask base plate. The coordinates in the middle are: ; Since the rotating mask base plate has already rotated Angle, therefore the first The star trails will become axis-aligned rectangles in the rotating mask base, such as Figure 2 As shown: Then the first The coordinates of the four corner points of the star orbits in the rotating mask base are: , , , ,in, and Representing the first A stellar orbit mask (axis-aligned rectangle) in The lower and upper boundaries along the axis. and Representing the first A stellar orbit mask (axis-aligned rectangle) in The lower and upper boundaries along the axis.
[0025] Considering that pixel coordinates need to be rounded and cannot exceed the canvas size of the rotating mask base, then the... The boundary of a star orbit mask in a rotating canvas is calculated as follows: , , , ,in, This represents the floor function, ensuring that the star trails are completely covered. This represents the function that takes the minimum value. This represents the function that takes the maximum value.
[0026] S4. Following the calculation method in step S3, nested loops are used to calculate sequentially. A stellar orbit mask is created by expanding the coordinates of each stellar point into a rectangular star orbit, thus obtaining a rotated star orbit mask.
[0027] The nested loop is specifically as follows:
[0028]
[0029]
[0030]
[0031]
[0032] in, The image matrix variable represents the rotating mask base. They represent the first row and number The index value of the variable in the column. And so on, generating all star trail masks in the rotating mask base in a loop; the mask generated in this step is defined as the rotating star trail mask.
[0033] S5. Perform an inverse rotation transformation on the rotating star trail mask, and expand it around the rotated canvas after the inverse transformation to obtain the inverse transformation canvas. To overlay a mask onto the original image, the rotating star trail mask is first subjected to an inverse rotational transformation, that is, the rotating mask is rotated counterclockwise around the origin in the direction opposite to the tilt of the star trail (-). The counterclockwise rotation angle is ,like Figure 3 As shown, the canvas is then expanded around the rotated canvas after the inverse transformation to obtain the inverse transformed canvas. The four sides of the inverse transformed canvas contain the four vertices of the rotated canvas after the inverse transformation. The coordinate system of the inverse transformed canvas is... ; S6. Crop the expanded portion of the rotated and inverse transformed canvas to obtain the final star trail mask.
[0034] like Figure 3 As shown, at this point, simply cropping the expanded canvas portions twice will yield the final star trail mask. The dimensions after the second canvas expansion are... ,according to Figure 3 The geometric relationship in the middle can be obtained as follows: , ; The origin of the original mask base plate coordinates The initial coordinates in the inverse transform star orbit mask are: , ,in, This represents the rounding function.
[0035] Assume the image matrix variables of the inverse transform mask are The final star trail mask The matrix index is: .
[0036] Using steps S1 to S5 to perform star orbit mask calculations has the following advantages: (1) It can significantly improve the computational efficiency of star trail masks; (2) The mask is inverted using mathematical and geometric methods, and its derivation process is rigorous and logically clear; (3) Compared with image processing methods, it is more accurate and efficient in calculation.
[0037] Example 2 This embodiment further defines Embodiment 1. This embodiment uses a space target observation image captured by the Jilin-1 platform 02A01 satellite as an example and implements the method described in Embodiment 1: A partial schematic diagram of the original observation image is shown below. Figure 4 As shown, the original image size is (3520, 16989). Based on image recognition, the outlines of brighter star trails can be obtained, thus determining the length and width of the star trails (in this embodiment, the length of the star trail is 70 pixels and the width is 12 pixels). By matching with a high-precision star catalog, the center coordinates of 1057 star trails are obtained. Simultaneously, based on the identified star trail outlines, the rotation angle of the star trails is statistically determined to be 96.114°.
[0038] A mask base plate is constructed according to the observed image size (3520, 16989), and then rotated 96.114° to generate a rotated mask base plate, as shown below. Figure 5 As shown, according to step S2, the dimensions of the expanded (rotated) canvas are (17268, 5310), with the origin at... Its position in the coordinate system of the rotating mask base plate is (5311, 376).
[0039] For each star orbit coordinate, calculate its position in the coordinate system of the rotating mask base plate according to steps S3 and S4, then calculate the coordinates of the four corner points of the axisymmetric rectangle, and use nested loops to modify and assign values to the image matrix variables of the rotating mask base plate.
[0040] This process is repeated to generate 1057 star trails in a rotating mask base, resulting in a rotating star trail mask as shown below. Figure 6 As shown: According to step S5, the rotating star-orbit mask is first inversely transformed, and then the origin of the original mask base plate coordinates is calculated. The starting coordinate position in the inverse transform star orbit mask is (1800, 375). The final star orbit mask is obtained from the starting coordinate position shown. The schematic diagram of the final star orbit mask is shown below. Figure 7 As shown: This embodiment uses the final star trail mask to process the space target observation image. Figure 8 This is a partial schematic diagram of the processed space target observation image, from... Figure 8 As can be seen, the star trails have been completely removed.
[0041] Example 3 This embodiment further defines Embodiment 1. This embodiment statistically analyzes the methods described in this invention, the "calculate star trail masks line by line + merge masks" method, and the "calculate star trail masks line by line + 0.5x downsampling + merge masks" method. Under the same conditions, the running time of 1000 star trail masks is calculated, and the statistical data is shown in Table 1. Table 1:
[0042] According to the data analysis in Table 1, compared with the method of calculating and superimposing masks for each star orbit, the test results show that, taking 1000 star orbits as an example, the running time on the same computer can be reduced from 16 seconds to 0.8 seconds, and the calculation efficiency is improved by 20 times.
Claims
1. A method for improving the computational efficiency of large-scale star orbit masking, characterized in that, The method includes the following steps: S1. In a two-dimensional coordinate system, from the origin... Starting from the observed image size, construct the original mask base plate; S2, rotate the original mask base around the origin. Rotate clockwise according to the tilt direction of the star trail to obtain a rotating mask base, and expand around the rotating mask base to obtain a rotating canvas; S3, Solving for the first [missing information] in the original mask base plate After the star trails are processed in step S2, the star trail mask is rotated in the canvas. , Indicates the total number of stars; S4. Calculate according to the calculation method in step S3. A star orbit mask is used to obtain a rotating star orbit mask; S5. Perform an inverse rotation transformation on the rotating star trail mask, and expand it around the rotated canvas after the inverse transformation to obtain the inverse transformation canvas. S6. Crop the expanded portion of the rotated and inverse transformed canvas to obtain the final star trail mask.
2. The method for improving the computational efficiency of large-scale star orbit masks according to claim 1, characterized in that, The original mask base is the same size as the observed image, and the coordinate system of the original mask base is [coordinate system not specified]. .
3. The method for improving the computational efficiency of large-scale star orbit masks according to claim 2, characterized in that, In step S2, the clockwise rotation angle of the original mask base plate The angle of inclination of the star trail.
4. The method for improving the computational efficiency of large-scale star orbit masks according to claim 3, characterized in that, In step S2, the four edges of the rotated canvas respectively contain the four vertices of the rotated mask base, and the coordinate system of the rotated canvas is... .
5. The method for improving the computational efficiency of large-scale star orbit masks according to claim 4, characterized in that, In step S3, the first The boundary of a star orbit mask in a rotating canvas is calculated as follows: , , , ,in, and They represent the first A stellar orbit mask in The lower and upper boundaries along the axis. and and They represent the first A stellar orbit mask in The lower and upper boundaries along the axis. This represents the floor function. This represents the floor function. and These represent the length and width of the star trails, respectively. Indicates the size of the rotated canvas. Indicates the first The star orbits in Coordinates in a coordinate system This represents the function that takes the minimum value. This represents the function that takes the maximum value.
6. The method for improving the computational efficiency of large-scale star orbit masks according to claim 5, characterized in that, In step S4, nested loops are used to calculate sequentially, based on the calculation method in step S3. A star orbit mask is obtained by rotating the star orbit mask.
7. The method for improving the computational efficiency of large-scale star orbit masks according to claim 6, characterized in that, In step S5, the inverse rotation transformation specifically involves rotating around the origin. Rotate counterclockwise in the direction opposite to the tilt of the star orbit, the angle of which is . .
8. A method for improving the computational efficiency of large-scale star orbit masks according to claim 7, characterized in that, In step S5, the four edges of the inverse transformation canvas each contain the four vertices of the rotated canvas after the inverse transformation, and the coordinate system of the inverse transformation canvas is... .