A method for automatic locating and extracting dispersion fringe and accurate calculation of slope

Abstract

The application relates to a method for automatically positioning and extracting a dispersion fringe and accurately calculating a slope, belonging to the field of optical detection, and comprising the following steps: collecting a raw coarse common phase image containing a dispersion fringe; transforming the raw coarse common phase image into a one-dimensional image; extracting the dispersion fringe according to the coordinate values corresponding to the maximum value and the minimum value of the one-dimensional image; and calculating the slope of the dispersion fringe. The application can effectively overcome the influence of irrelevant interference dispersion fringes in the coarse common phase image caused by a microlens array on the coarse common phase adjustment stage, can accurately position and extract the dispersion fringe of a region of interest, can calculate the slope of the dispersion fringe of the region of interest, can solve the technical problem that the dispersion fringe is difficult to accurately position and extract, and can greatly improve the precision of the subsequent dispersion fringe method, that is, the precision of the common phase adjustment between each sub-mirror in a serial primary mirror structure, and can provide favorable guarantee for the high-precision adjustment of the subsequent dispersion fringe method.

Description

Technical Field

[0001] This invention relates to the field of optical detection technology, specifically to a method for automatic positioning and extraction of dispersion fringes and accurate calculation of slope. Background Technology

[0002] Large-aperture space telescopes play a crucial role in cosmological and celestial research, extraterrestrial life system research, disaster monitoring, resource exploration, and mapping. With the continuous increase in the aperture of space telescopes, significant challenges arise in mirror fabrication, testing, and the transportation and launch of the entire telescope. Therefore, modular telescopes have emerged. Since modular telescopes employ a modular primary mirror structure, it is essential to ensure that all sub-mirrors within the modular primary mirror structure are in phase. Currently, the phase adjustment process among the sub-mirrors in a modular primary mirror structure generally follows a coarse-to-fine, gradually converging approach, completing the wavefront sensing tasks at each stage in the sequence of "coarse confocal → fine confocal → coarse co-phase → fine co-phase." For the coarse co-phase stage, the dispersion fringe method is commonly used for coarse co-phase adjustment, such as the modular mirror phase error correction method based on dispersion fringe slope analysis disclosed in Chinese Patent Publication No. CN111207910A. However, due to the presence of the microlens array, irrelevant interfering dispersion fringes exist in the coarse cophase image. Therefore, to address the impact of these irrelevant interfering dispersion fringes on the coarse cophase adjustment stage and improve the accuracy of the dispersion fringe method, it is first necessary to accurately locate and extract the dispersion fringe region, and simultaneously, accurately calculate the slope of the extracted dispersion fringes. However, since it is difficult to accurately locate and extract dispersion fringes, no methods for accurately locating, extracting, and calculating the slope of dispersion fringes have been reported to date. Summary of the Invention

[0003] The purpose of this invention is to provide a method for automatic positioning and extraction of dispersion fringes and accurate calculation of their slope, so as to solve the problem that it is difficult to achieve accurate positioning and extraction of dispersion fringes.

[0004] The technical solution adopted by this invention to solve the technical problem is as follows:

[0005] The present invention provides a method for automatic positioning and extraction of dispersion fringes and accurate calculation of slope, comprising the following steps:

[0006] Step S1: Acquire the raw coarse cophase image containing dispersion fringes;

[0007] Step S2: Transform the original coarse co-phase image into a one-dimensional image;

[0008] Step S3: Extract dispersion fringes based on the coordinate values ​​corresponding to the maxima and minima of the one-dimensional image;

[0009] Step S4: Calculate the slope of the dispersion fringes.

[0010] Furthermore, the specific operation process of step S2 is as follows:

[0011] Step S2.1: Preprocess the original coarse co-phase image;

[0012] Step S2.2: Project the preprocessed original coarse cophase image horizontally and vertically, that is, accumulate it along the direction of the dispersion fringes, and transform the original coarse cophase image into a one-dimensional image.

[0013] Furthermore, in step S2.1, the preprocessing employs median filtering to remove noise.

[0014] Furthermore, the specific operation process of step S3 is as follows:

[0015] Step S3.1: Perform smoothing filtering on the one-dimensional image;

[0016] Step S3.2: Calculate the maximum value V of the filtered one-dimensional image. max and the minimum value V min Preserve the maximum value V max The corresponding coordinate value X max and the minimum value V min The corresponding coordinate value X min ;

[0017] Step S3.3: Extract coordinate values ​​X from the original coarse co-phase image max The corresponding image rows are then subjected to smoothing filtering;

[0018] Step S3.4: Calculate the number of maxima in each row of the filtered image. The row with the most maxima is the center row of the dispersion fringe, and the coordinates of the maxima corresponding to the center row of this dispersion fringe are X. center ;

[0019] Step S3.5: Set the coordinate value X min With coordinate value X center A comparison is made when the following relationship is satisfied: X min (i) <X center <X min (i+1), X min (i) and X min (i+1) represent the coordinates of the lower and upper bound rows of the one-dimensional image, respectively, where i = 0…(n-1), and n is the minimum value V of the one-dimensional image. min The number of fringe patterns indicates that the region between the lower and upper bounds of the one-dimensional image in the original coarse co-phase image is the extracted dispersion fringe image.

[0020] Furthermore, the specific operation process of step S4 is as follows:

[0021] Step S4.1: Obtain the connected components of the dispersion fringes in the dispersion fringe image;

[0022] Step S4.2: Obtain the center line of the dispersion fringe in the connected region of the dispersion fringe;

[0023] Step S4.3: Obtain the slope of the center line of the dispersion fringes using the least squares method;

[0024] Step S4.4: Calculate the final slope of the dispersion fringes.

[0025] Furthermore, the specific operation process of step S4.1 is as follows:

[0026] S4.1.1: Perform binarization processing on the obtained dispersive fringe image;

[0027] S4.1.2: Obtain the connected components of the dispersive fringe from the binarized dispersive fringe image.

[0028] Furthermore, the specific operation process of step S4.2 is as follows:

[0029] Step S4.2.1: Obtain the minimum bounding rectangle of the dispersive fringe connected region;

[0030] Step S4.2.2: Extract the region corresponding to the minimum bounding rectangle of the dispersive fringe connected region;

[0031] Step S4.2.3: Extract the center line of the dispersion fringe in the region corresponding to the smallest bounding rectangle of the dispersion fringe connected region.

[0032] Furthermore, in step S4.2.3, the center line of the dispersion fringe in the region corresponding to the minimum bounding rectangle of the dispersion fringe connected domain is extracted using the Steger algorithm or the gray-scale centroid method.

[0033] Furthermore, the specific operation process of step S4.4 is as follows:

[0034] Step S4.4.1: Repeat steps S4.1-S4.3 to obtain the slope of the center line of all dispersion fringes;

[0035] Step S4.4.2: Based on the least squares method, fit the final slope of the dispersion fringes using the slopes of the center lines of all the obtained dispersion fringes.

[0036] The beneficial effects of this invention are:

[0037] This invention provides an automatic method for locating and extracting dispersion fringes and accurately calculating their slope. The method involves acquiring a raw coarse co-phase image containing dispersion fringes, transforming the raw coarse co-phase image into a one-dimensional image, extracting the dispersion fringes based on the coordinates corresponding to the maxima and minima of the one-dimensional image, and finally calculating the slope of the dispersion fringes. This invention effectively overcomes the influence of irrelevant interfering dispersion fringes in the coarse co-phase image caused by the presence of microlens arrays on the coarse co-phase adjustment stage. It can accurately locate and extract dispersion fringes in the region of interest and simultaneously calculate the slope of the dispersion fringes in that region of interest. This solves the technical problem of accurately locating and extracting dispersion fringes. As a necessary prerequisite for implementing the dispersion fringe method, this invention can greatly improve the accuracy of subsequent dispersion fringe methods, namely, the co-phase adjustment accuracy between the sub-mirrors in a connected primary mirror structure, providing a favorable guarantee for high-precision adjustment of subsequent dispersion fringe methods. Attached Figure Description

[0038] Figure 1 This is a flowchart of a method for automatic positioning, extraction, and accurate slope calculation of dispersion fringes according to the present invention.

[0039] Figure 2 The original coarse cophase image containing dispersion fringes acquired in step S1;

[0040] Figure 3 From Figure 2 Extracting the maximum value V from the original coarse cophase image shown max Corresponding coordinate value X max The corresponding image row data;

[0041] Figure 4 Data for the center row of the dispersion fringes;

[0042] Figure 5 V is the minimum value of a one-dimensional image. min Corresponding coordinate value X min The coordinate value X corresponding to the maximum value of the central row of the dispersion fringes center The comparison results are shown in the figure, X min (i) represents the coordinates corresponding to the lower bound row of the one-dimensional image, and the corresponding image row data on the right is the lower bound row of the one-dimensional image; X center X represents the coordinates of the maximum values ​​corresponding to the center row of the dispersion fringes; the corresponding image row data on the right represents the center row of the dispersion fringes. min (i+1) represents the coordinate value corresponding to the upper limit row of the one-dimensional image, and the corresponding image row data on the right is the upper limit row of the one-dimensional image;

[0043] Figure 6The figure shows the horizontal projection curve of a one-dimensional image. In the figure, a, c, e, g, and i are maxima, and b, d, f, and h are minima. The coordinates corresponding to the minimum value d are the coordinates corresponding to the lower limit row of the one-dimensional image, and the coordinates corresponding to the maximum value e are the coordinates X corresponding to the maximum value of the center row of the dispersion fringes. center The coordinates corresponding to the minimum value f are the coordinates corresponding to the upper row of the one-dimensional image;

[0044] Figure 7 The image is the dispersive fringe image extracted in step S3.5;

[0045] Figure 8 The center line of the dispersion fringes extracted in step S4.2.3. Detailed Implementation

[0046] The present invention provides a method for automatic positioning and extraction of dispersion fringes and accurate calculation of slope, which mainly includes the following steps:

[0047] Step S1: Acquire the raw coarse cophase image containing dispersion fringes;

[0048] Step S2: Transform the original coarse co-phase image into a one-dimensional image;

[0049] Step S3: Extract dispersion fringes;

[0050] Step S4: Calculate the slope of the dispersion fringes.

[0051] The present invention will be further described in detail below with reference to the accompanying drawings.

[0052] like Figure 1 As shown, the present invention provides an automatic method for locating and extracting dispersion fringes and accurately calculating their slope, which specifically includes the following steps:

[0053] Step S1: After the mosaic telescope completes confocalization, acquire the original coarse co-phase image (img) containing dispersion fringes, such as... Figure 2 As shown;

[0054] Step S2: Transform the original coarse co-phase image img into a one-dimensional image Cimg;

[0055] The specific steps are as follows:

[0056] Step S2.1: Perform preprocessing such as image median filtering on the original coarse co-phase image img to remove image noise;

[0057] Step S2.2: Project the preprocessed original coarse cophase image img horizontally and vertically, that is, accumulate along the direction of the dispersion fringes, so as to transform the original coarse cophase image img into a one-dimensional image Cimg.

[0058] Step S3: Extract the dispersion fringes based on the coordinate values ​​corresponding to the maxima and minima of the one-dimensional image Cimg obtained above;

[0059] The specific steps are as follows:

[0060] Step S3.1: Perform smoothing filtering on the one-dimensional image Cimg obtained above to remove maxima and minima caused by noise;

[0061] Step S3.2: Calculate the maximum value V of the filtered one-dimensional image Cimg. max and the minimum value V min The result is as follows Figure 6 As shown, the maximum value V of the one-dimensional image Cimg is saved. max The corresponding coordinate value X max The minimum value V of the one-dimensional image Cimg min The corresponding coordinate value X min ;

[0062] Step S3.3: From the original coarse co-phase image img( Figure 2 Extracting the maximum value V from ) max Corresponding coordinate value X max The corresponding image row img(X) max The result is as follows Figure 3 As shown; for the image row img(X) max Perform smoothing filtering to remove maxima and minima caused by noise;

[0063] Step S3.4: Calculate the filtered image row img(X) max The number of maxima in the image (img(X)), where the image row containing the most maxima is the one with the highest number of maxima. max This represents the central row of the dispersion fringes, and the coordinates corresponding to the maximum values ​​of this central row are X. center The data of the center row of the dispersive fringes are as follows: Figure 4 As shown;

[0064] Step S3.5: Find the minimum value V of the one-dimensional image Cimg. min The corresponding coordinate value X min The coordinate value X corresponding to the maximum value of the central row of the dispersion fringes center Compare them when they satisfy the following relationship: X min (i) <X center And X min (i+1)>X center , that is, X min (i) <X center <X min (i+1), where Xmin (i) and X min (i+1) represent the coordinates of the lower bound row and the upper bound row of the one-dimensional image Cimg, respectively, where i = 0…(n-1), and n is the minimum value V of the one-dimensional image Cimg. min Number, such as Figure 5 As shown, the region between the lower bound and the upper bound of the one-dimensional image Cimg in the original coarse co-phase image img is considered to be the extracted dispersion fringe image. Figure 7 As shown;

[0065] Step S4: Calculate the slope of the dispersion fringes;

[0066] Step S4.1: Obtain the connected components of the dispersion fringes in the dispersion fringe image;

[0067] The specific steps are as follows:

[0068] S4.1.1: Perform binarization processing on the dispersive fringe image obtained above;

[0069] S4.1.2: Obtain the connected components of the dispersive fringe from the binarized dispersive fringe image;

[0070] Step S4.2: Obtain the center line of the dispersion fringe in the connected region of the dispersion fringe;

[0071] The specific steps are as follows:

[0072] Step S4.2.1: Obtain the minimum bounding rectangle of the dispersive fringe connected region;

[0073] Step S4.2.2: Extract the region corresponding to the minimum bounding rectangle of the dispersive fringe connected region;

[0074] Step S4.2.3: Extract the center line of the dispersion fringes in the region corresponding to the minimum bounding rectangle of the dispersion fringe connected region, such as... Figure 8 As shown, the methods used for extraction include, but are not limited to: Steger algorithm (line center extraction algorithm), grayscale centroid method, etc.

[0075] Step S4.3: Obtain the slope of the center line of the dispersion fringes using the least squares method;

[0076] Step S4.4: Calculate the final slope of the dispersion fringes;

[0077] The specific steps are as follows:

[0078] Step S4.4.1: Repeat steps S4.1-S4.3 above to obtain the slope of the center line of all dispersion fringes;

[0079] Step S4.4.2: Based on the least squares method, fit the final slope of the dispersion fringes using the slopes of the center lines of all the dispersion fringes obtained above.

[0080] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for automatic positioning, extraction, and accurate slope calculation of dispersive fringes, characterized in that, Includes the following steps: Step S1: Acquire the raw coarse cophase image containing dispersion fringes; Step S2: Transform the original coarse co-phase image into a one-dimensional image; Step S3: Extract dispersion fringes based on the coordinate values ​​corresponding to the maxima and minima of the one-dimensional image; Step S3.1: Perform smoothing filtering on the one-dimensional image; Step S3.2: Calculate the maximum value V of the filtered one-dimensional image. max and the minimum value V min Preserve the maximum value V max The corresponding coordinate value X max and the minimum value V min The corresponding coordinate value X min ; Step S3.3: Extract coordinate values ​​X from the original coarse co-phase image max The corresponding image rows are then subjected to smoothing filtering; Step S3.4: Calculate the number of maxima in each row of the filtered image. The row with the most maxima is the center row of the dispersion fringe, and the coordinates of the maxima corresponding to the center row of this dispersion fringe are X. center ; Step S3.5: Set the coordinate value X min With coordinate value X center A comparison is made when the following relationship is satisfied: X min (i) <X center <X min (i+1), X min (i) and X min (i+1) represent the coordinates of the lower and upper bound rows of the one-dimensional image, respectively, where i = 0…(n-1), and n is the minimum value V of the one-dimensional image. min The number of fringe patterns indicates that the region between the lower and upper bounds of the one-dimensional image in the original coarse co-phase image is the extracted dispersion fringe image. Step S4: Calculate the slope of the dispersion fringes; Step S4.1: Obtain the connected components of the dispersion fringes in the dispersion fringe image; S4.1.1: Perform binarization processing on the obtained dispersive fringe image; S4.1.2: Obtain the connected components of the dispersive fringe from the binarized dispersive fringe image; Step S4.2: Obtain the center line of the dispersion fringe in the connected region of the dispersion fringe; Step S4.2.1: Obtain the minimum bounding rectangle of the dispersive fringe connected region; Step S4.2.2: Extract the region corresponding to the minimum bounding rectangle of the dispersive fringe connected region; Step S4.2.3: Extract the center line of the dispersion fringe in the region corresponding to the minimum bounding rectangle of the dispersion fringe connected region; Step S4.3: Obtain the slope of the center line of the dispersion fringes using the least squares method; Step S4.4: Calculate the final slope of the dispersion fringes; Step S4.4.1: Repeat steps S4.1-S4.3 to obtain the slope of the center line of all dispersion fringes; Step S4.4.2: Based on the least squares method, fit the final slope of the dispersion fringes using the slopes of the center lines of all the obtained dispersion fringes.

2. The method for automatic positioning, extraction, and accurate slope calculation of dispersive fringes according to claim 1, characterized in that, The specific operation process of step S2 is as follows: Step S2.1: Preprocess the original coarse co-phase image; Step S2.2: Project the preprocessed original coarse cophase image horizontally and vertically, that is, accumulate it along the direction of the dispersion fringes, and transform the original coarse cophase image into a one-dimensional image.

3. The method for automatic positioning, extraction, and accurate slope calculation of dispersive fringes according to claim 2, characterized in that, In step S2.1, the preprocessing uses median filtering to remove noise.

4. The method for automatic positioning, extraction, and accurate slope calculation of dispersive fringes according to claim 1, characterized in that, In step S4.2.3, the center line of the dispersion fringe in the region corresponding to the minimum bounding rectangle of the dispersion fringe connected region is extracted using the Steger algorithm or the gray-scale centroid method.

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