A Shack-Hartmann wavefront detector centroid calculation method and related device

Abstract

The application discloses a Shack-Hartmann wavefront detector centroid calculation method and related equipment, and relates to the field of optical measurement, and comprises the following steps: acquiring a spot array gray scale image, detecting local maximum values of each spot and dividing a sub-aperture image area corresponding to a microlens one by one according to the local maximum values; extracting a gray scale matrix of each sub-aperture image area, respectively determining one-dimensional regions of a main lobe of a spot in a row direction and a column direction, and obtaining a main lobe region by intersection; forming a threshold calculation region by deducting the main lobe region from the sub-aperture image area, and selecting a maximum value of gray scales of the threshold calculation region as a threshold value; executing threshold value reduction on pixels in the sub-aperture image area and setting negative values to zero, and calculating a spot centroid position based on the processed image. The method realizes adaptive threshold value of the sub-aperture and local background removal, avoids loss of weak spot information caused by a unified threshold value, and improves the accuracy of centroid calculation and wavefront recovery.

Description

Technical Field

[0001] This invention relates to the field of optical measurement, specifically to a method for calculating the centroid of a Shaker-Hartmann wavefront detector and related equipment. Background Technology

[0002] The Shak-Hartmann wavefront detector is an instrument capable of detecting wavefront errors, widely used in adaptive optics, optical mirror inspection, medical instruments, and laser beam diagnostics. It consists of a microlens array and a photodetector located on its focal plane. The wavefront incident on the Shak-Hartmann wavefront detector is focused onto the focal plane by the microlens array, forming an array of light spots, which are then acquired by the photodetector. The wavefront aberration is then recovered by calculating the deviation of the centroid of each sub-aperture spot relative to the calibrated centroid. To reduce the effects of photodetector noise, stray light, and microlens diffraction, the image of the light spot array needs to be thresholded before calculating the centroid of the sub-aperture spots.

[0003] In the traditional Shaker-Hartmann wavefront detector centroid calculation, the threshold size of the overall image is determined based on the noise of the detector and the level of stray light in the optical path. Then, the threshold determined by the above method is subtracted from the entire image, and the parts of the image that are less than zero are set to zero, thus completing the threshold reduction processing of the spot array image.

[0004] In reality, the intensity distribution of stray light and the wavefront being measured is not uniform. Traditional Shaker-Hartmann wavefront detectors, by selecting the same threshold across the entire image, will result in thresholds that are too large or too small in some areas, thus affecting the accuracy of centroid calculation. In optical measurements of conventional accuracy, because the intensity distribution is relatively uniform, the error introduced by threshold selection is far less than the required measurement accuracy, and its influence can be ignored during measurement.

[0005] However, projection exposure apparatuses used in large-scale integrated circuit fabrication require projection objective lens wavefront aberration RMS values ​​to be less than 3 nm. Such high-precision optical systems necessitate sub-nanometer level measurement accuracy for the system wavefront aberration detection device. The non-uniformity of light intensity distribution leads to differences in the total light intensity across different sub-apertures of the photodetector. The centroid calculation error introduced by selecting the same threshold for the entire image can have a significant impact under these conditions, necessitating a new threshold selection method to reduce the influence of non-uniform light intensity distribution. Summary of the Invention

[0006] The technical problem this invention aims to solve is that existing methods for calculating the centroid of a Shaker-Hartmann wavefront detector can lead to the loss of effective light spots in weaker areas due to non-uniform distribution of incident light intensity, resulting in the removal of some sub-aperture image information. The purpose is to provide a method and related equipment for calculating the centroid of a Shaker-Hartmann wavefront detector, which solves the problem of non-uniform distribution of sub-aperture light intensity, making adaptive compensation impossible, and the loss of light spot information easily caused by existing centroid calculation methods.

[0007] This invention is achieved through the following technical solution:

[0008] A method for calculating the centroid of a Shaker-Hartmann wavefront detector includes:

[0009] Acquire a grayscale image of the light spot array of the Shaker-Hartmann wavefront detector, detect the coordinates of the grayscale maxima of each spot on the grayscale image, and divide the light spot array image into sub-aperture image regions corresponding one-to-one with the microlenses according to the coordinates of the grayscale maxima.

[0010] For each sub-aperture image region, the pixel gray values ​​within the sub-aperture image region are extracted to form a sub-aperture gray matrix. Based on the sub-aperture gray matrix, the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction are obtained respectively. The intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction is obtained to obtain the main lobe region of the light spot.

[0011] The threshold calculation region is obtained by subtracting the main lobe region from the sub-aperture image region;

[0012] The maximum gray value within the threshold calculation area is selected as the threshold of the sub-aperture image region;

[0013] A threshold reduction process is performed on all pixel grayscale values ​​within the sub-aperture image region to obtain a processed sub-aperture image for centroid calculation;

[0014] Based on the processed sub-aperture image, the position of the spot centroid is calculated in each sub-aperture image region.

[0015] Furthermore, the step of obtaining the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction based on the sub-aperture grayscale matrix, and obtaining the main lobe region of the light spot by finding the intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction, includes:

[0016] The sub-aperture grayscale matrix is ​​summed along the row and column directions to obtain row and column vectors, respectively. The row and column vectors are then subjected to first-order difference to obtain row gradient sequences and column gradient sequences. The local maxima and local minima corresponding to the rising and falling edges of the row and column gradient sequences are determined, respectively. The one-dimensional image region in the row direction and the one-dimensional image region in the column direction are determined by the interval between the local maxima and local minima. The intersection of the two regions is the main lobe region of the light spot.

[0017] Furthermore, the step of detecting the grayscale maximum coordinates of each spot on the grayscale image, and dividing the spot array image into sub-aperture image regions corresponding one-to-one with the microlenses based on the grayscale maximum coordinates, includes:

[0018] The gray-scale maximum coordinates of each spot are detected on the gray-scale image; taking each gray-scale maximum coordinate as the geometric center, the distance between it and the nearest neighboring gray-scale maximum coordinate is taken as the side length, and a square window centered on the geometric center is constructed, and the square window is used as the corresponding sub-aperture image region, and the boundaries of adjacent sub-aperture image regions are connected but do not overlap.

[0019] Furthermore, the threshold reduction process includes:

[0020] Within each sub-aperture image region, the gray value of each pixel is subtracted from the corresponding threshold, and the gray value of pixels whose gray value is less than zero after subtracting the threshold is set to zero, thus obtaining a processed image for calculating the centroid position of the spot.

[0021] Furthermore, when performing gradient operations on row vectors and column vectors, the gradient operation is a discrete first-order difference operation, the difference operator is selected as [−1, +1], and the boundary processing strategy of mirroring or zero-filling is adopted for the two endpoints.

[0022] Furthermore, the step of determining the one-dimensional image region in the row direction and the one-dimensional image region in the column direction based on the interval between local maxima and local minima includes:

[0023] Obtain the local maximum and local minimum coordinates in the row direction, determine the range of the local maximum and local minimum coordinates, and use it as a one-dimensional image region in the row direction;

[0024] Obtain the local maximum and local minimum coordinates in the column direction, determine the range of the local maximum and local minimum coordinates, and use it as a one-dimensional image region in the column direction;

[0025] When defining the range by the two coordinate intervals corresponding to the local maxima and local minima, the minimum and maximum widths of the range are constrained so that the one-dimensional image region satisfies the preset width range.

[0026] Furthermore, when the main lobe region is obtained by intersecting the one-dimensional image regions in the row direction and the one-dimensional image regions in the column direction, if the intersection region is empty or does not meet the preset area threshold, a backoff strategy is triggered: the one-dimensional candidate range of the row or column is expanded and the intersection is re-calculated to obtain a valid main lobe region.

[0027] This invention also provides a Shaker-Hartmann wavefront detector centroid calculation system for implementing the Shaker-Hartmann wavefront detector centroid calculation method described above, characterized in that it includes:

[0028] Segmentation module: used to acquire the grayscale image of the light spot array of the Shaker-Hartmann wavefront detector, detect the grayscale maximum coordinates of each light spot on the grayscale image, and divide the light spot array image into sub-aperture image regions corresponding one-to-one with the microlenses according to the grayscale maximum coordinates.

[0029] The main lobe image extraction module is used to extract the pixel gray values ​​within each sub-aperture image region to form a sub-aperture gray matrix. Based on the sub-aperture gray matrix, it obtains the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction respectively. The intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction is used to obtain the main lobe region of the light spot.

[0030] Threshold calculation module: used to obtain a threshold calculation region by subtracting the main lobe region from the sub-aperture image region, and select the maximum gray value in the threshold calculation region as the threshold of the sub-aperture image region;

[0031] Threshold reduction module: used to perform threshold reduction processing on all pixel grayscale within the sub-aperture image area to obtain a processed sub-aperture image for centroid calculation;

[0032] Spot centroid calculation module: used to calculate the position of the spot centroid in each sub-aperture image region based on the processed sub-aperture image.

[0033] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the program to implement the Shaker-Hartmann wavefront detector centroid calculation method as described above.

[0034] The present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the program is executed by a processor, it implements the Shaker-Hartmann wavefront detector centroid calculation method as described above.

[0035] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0036] This invention determines the threshold independently within each sub-aperture, making the threshold only related to the light intensity distribution of the image of that sub-aperture. This effectively avoids the erroneous reduction of weak spots by the uniform threshold method and improves the adaptability and stability of centroid calculation.

[0037] By independently setting thresholds for each sub-aperture and performing threshold reduction processing, this invention can still retain the main energy information of each spot even under conditions of large light intensity differences, ensuring that the centroid calculation results truly reflect the local changes of the incident wavefront, thereby improving the accuracy of the overall wavefront reconstruction.

[0038] This method takes a grayscale image as input, obtains sub-aperture regions through geometric division, and performs main lobe determination, threshold determination and threshold reduction processing within the local area. The algorithm has a clear structure and moderate computational load, and can be directly embedded into the signal processing module of the existing Shaker-Hartmann wavefront detection system. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0040] Figure 1 Here is a flowchart of the method for calculating the centroid of the Shaker-Hartmann wavefront detector in Example 1;

[0041] Figure 2 This is a structural diagram of the Shaker-Hartmann wavefront detector centroid calculation system in Example 2;

[0042] Figure 3 This is a diagram illustrating the existing technology implementation of the Shaker-Hartmann wavefront detector's center of mass meter. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0044] Example 1

[0045] A method for calculating the centroid of a Shaker-Hartmann wavefront detector, such as Figure 1 As shown, it includes:

[0046] Acquire a grayscale image of the light spot array of the Shaker-Hartmann wavefront detector, detect the coordinates of the grayscale maxima of each spot on the grayscale image, and divide the light spot array image into sub-aperture image regions corresponding one-to-one with the microlenses according to the coordinates of the grayscale maxima.

[0047] For each sub-aperture image region, the pixel gray values ​​within the sub-aperture image region are extracted to form a sub-aperture gray matrix. Based on the sub-aperture gray matrix, the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction are obtained respectively. The intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction is obtained to obtain the main lobe region of the light spot.

[0048] The threshold calculation region is obtained by subtracting the main lobe region from the sub-aperture image region;

[0049] The maximum gray value within the threshold calculation area is selected as the threshold of the sub-aperture image region;

[0050] A threshold reduction process is performed on all pixel grayscale values ​​within the sub-aperture image region to obtain a processed sub-aperture image for centroid calculation;

[0051] Based on the processed sub-aperture image, the position of the spot centroid is calculated in each sub-aperture image region.

[0052] like Figure 3 The diagram illustrates the measurement process of the Hartmann-Shack sensor and the distribution of light spots on the target surface of its photodetector. The Hartmann-Shack sensor uses a microlens array 1 to divide the incident signal wavefront into sub-apertures. The light signal within each sub-aperture is focused onto the subsequent photodetector 2. The centroid position is calculated using the energy distribution on the target surface of photodetector 2.

[0053] Figure 3 The dashed line in the left-middle shows the propagation of the sensor's reference light wavefront. The distribution of the light spot formed by the dot matrix of this wavefront after being collected by photodetector 2 can be obtained from... Figure 3 As can be seen on the right, the boxes represent the sub-apertures divided by each microlens, and the symbol  in the figure represents the lattice formed by the reference wavefront. Figure 3 The solid line in the left-center shows the propagation of incident light rays on the wavefront being measured (represented by an incline in the figure). The distribution of the light spot after the lattice formed by this wavefront is collected by the photodetector can be obtained from... Figure 3 As shown on the right, the symbol ⊕ in the figure represents the lattice distribution formed by the distorted wavefront. By calculating the offset between the two lattices using the centroid position, the wavefront of the distorted wavefront can be reconstructed using the wavefront reconstruction algorithm.

[0054] The Hartmann-Shack wavefront sensor needs to calculate the centroid position of the light spot during the measurement process. The Hartmann-Shack wavefront sensor mainly calculates the centroid position of the light spot according to the following formula ( ):

[0055]

[0056]

[0057] In the formula, m=1~M, n=1~N are the pixel regions corresponding to the sub-aperture mapped onto the photosensitive target surface of the photodetector, and I nm It is the signal received by the (n,m)th pixel on the photosensitive target surface of the photodetector, x nm ,y nm These are the x and y coordinates of the (n, m)th pixel, respectively.

[0058] Then calculate the wavefront slope g of the incident wavefront according to the following formula. xi ,g yi :

[0059]

[0060]

[0061] In the formula, (x0, y0) represents the reference position of the center of the light spot obtained by the reference beam on the Hartmann-Shack sensor; when the Hartmann-Shack sensor detects wavefront distortion, as... Figure 2 As shown in the figure (the solid line indicates the actual focusing position of the distorted wavefront, and the dashed line indicates the focusing of the light rays from the reference wavefront), the center of the light spot shifts to (x... i ,y i Using the slope values ​​of the measured wavefront at each sub-aperture calculated by the above formula, the wavefront is finally reconstructed using the pattern method or the region method.

[0062] It can be seen that existing Shaker-Hartmann wavefront detectors typically select a uniform threshold across the entire light spot array image for thresholding to eliminate the influence of microlens diffraction and background light on centroid calculation. However, when the incident light intensity distribution is non-uniform, the effective light spot in the weak light region may be misjudged as background due to thresholding, resulting in partial loss of sub-aperture image information and affecting the accuracy of wavefront reconstruction. To overcome the above defects, this invention proposes a centroid calculation method based on independent thresholding of molecular apertures. By independently determining the threshold within each sub-aperture according to its grayscale distribution characteristics and performing thresholding, adaptive compensation for non-uniform light intensity distribution is achieved, ensuring complete preservation of light spot information and improving the accuracy and stability of wavefront detection.

[0063] This invention determines the threshold independently within each sub-aperture, making the threshold only related to the light intensity distribution of the image of that sub-aperture. This effectively avoids the erroneous reduction of weak spots by the uniform threshold method and improves the adaptability and stability of centroid calculation.

[0064] By independently setting thresholds for each sub-aperture and performing threshold reduction processing, this invention can still retain the main energy information of each spot even under conditions of large light intensity differences, ensuring that the centroid calculation results truly reflect the local changes of the incident wavefront, thereby improving the accuracy of the overall wavefront reconstruction.

[0065] This method takes a grayscale image as input, obtains sub-aperture regions through geometric division, and performs main lobe determination, threshold determination and threshold reduction processing within the local area. The algorithm has a clear structure and moderate computational load, and can be directly embedded into the signal processing module of the existing Shaker-Hartmann wavefront detection system.

[0066] like Figure 1 As shown, the step of obtaining the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction based on the sub-aperture grayscale matrix, and obtaining the main lobe region of the light spot by finding the intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction, includes:

[0067] The sub-aperture grayscale matrix is ​​summed along the row and column directions to obtain row and column vectors, respectively. The row and column vectors are then subjected to first-order difference to obtain row gradient sequences and column gradient sequences. The local maxima and local minima corresponding to the rising and falling edges of the row and column gradient sequences are determined, respectively. The one-dimensional image region in the row direction and the one-dimensional image region in the column direction are determined by the interval between the local maxima and local minima. The intersection of the two regions is the main lobe region of the light spot.

[0068] Specifically,

[0069] a) Row direction processing: Summing the sub-aperture grayscale matrix along the row direction to obtain a row vector; performing first-order difference on the row vector to obtain a row gradient sequence; determining the local maximum position corresponding to the rising edge and the local minimum position corresponding to the falling edge in the row gradient sequence, and using the interval between the two as the main lobe one-dimensional image region in the row direction.

[0070] (b) Column direction processing: The sub-aperture grayscale matrix is ​​summed along the column direction to obtain a column vector; the column vector is subjected to first-order difference to obtain a column gradient sequence; the local maximum position corresponding to the rising edge and the local minimum position corresponding to the falling edge are determined in the column gradient sequence, and the interval between the two is taken as the one-dimensional image region of the main lobe in the column direction.

[0071] (c) Determination of the main lobe region: The intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction is obtained to obtain the main lobe region of the light spot.

[0072] like Figure 1As shown, the step of detecting the grayscale maximum coordinates of each spot on the grayscale image and dividing the spot array image into sub-aperture image regions corresponding one-to-one with the microlenses based on the grayscale maximum coordinates includes:

[0073] The gray-scale maximum coordinates of each spot are detected on the gray-scale image; taking each gray-scale maximum coordinate as the geometric center, the distance between it and the nearest neighboring gray-scale maximum coordinate is taken as the side length, and a square window centered on the geometric center is constructed, and the square window is used as the corresponding sub-aperture image region, and the boundaries of adjacent sub-aperture image regions are connected but do not overlap.

[0074] Maximum value detection is performed on the entire grayscale image to obtain the set of spot peaks. Each grayscale maximum value is used as the geometric center. The pixel spacing of the nearest neighboring peaks in the horizontal and vertical directions is calculated, and the average of the two is taken as the side length. A square sub-aperture window centered on the grayscale maximum value is established. The boundaries of adjacent windows are connected and do not overlap. Windows located at the imaging boundary are cropped according to the image range. When individual peaks are missed or over-detected, they can be screened and filled through neighborhood consistency (minimum / maximum spacing constraint) to ensure a one-to-one correspondence between the sub-aperture set and the microlens array.

[0075] The threshold reduction process includes: within each sub-aperture image region, subtracting the corresponding threshold from the gray value of each pixel, and setting the gray value of pixels with a gray value less than zero after threshold reduction to zero, thereby obtaining a processed image for calculating the centroid position of the light spot.

[0076] For each sub-aperture image region, pixel-by-pixel subtraction is first performed on all pixels in the region based on the threshold of that sub-aperture image region, and the pixel grayscale is updated. To avoid introducing background noise into the centroid calculation, non-negative truncation is performed on grayscale values ​​that are less than zero after subtraction, and they are uniformly set to 0, forming a processed image that only contains the effective spot signal. Then, the centroid position is calculated using the processed image as input, thereby suppressing the interference of background and side lobes on the centroid calculation while preserving the main lobe energy.

[0077] like Figure 1 As shown, when performing gradient operations on row vectors and column vectors, the gradient operation is a discrete first-order difference operation, the difference operator is selected as [−1, +1], and the boundary processing strategy of mirroring or zero-filling is adopted for the two endpoints.

[0078] like Figure 1 As shown, determining the one-dimensional image region in the row direction and the one-dimensional image region in the column direction by the interval between local maxima and local minima includes:

[0079] Obtain the local maximum and local minimum coordinates in the row direction, determine the range of the local maximum and local minimum coordinates, and use it as a one-dimensional image region in the row direction;

[0080] Obtain the coordinates of local maxima and local minima in the column direction, determine the range of the coordinates of local maxima and local minima, and use it as a one-dimensional image region in the column direction;

[0081] When defining the range by the two coordinate intervals corresponding to the local maxima and local minima, the minimum and maximum widths of the range are constrained so that the one-dimensional image region satisfies the preset width range.

[0082] When the intersection of a one-dimensional image region in the row direction and a one-dimensional image region in the column direction is taken to obtain the main lobe region, if the intersection region is empty or does not meet the preset area threshold, a backoff strategy is triggered: the one-dimensional candidate range of the row or column is expanded and the intersection is re-found to obtain a valid main lobe region.

[0083] Example 2

[0084] A Shaker-Hartmann wavefront detector centroid calculation system, such as Figure 2 As shown, the method for calculating the centroid of the Shaker-Hartmann wavefront detector described in Example 1 includes:

[0085] Segmentation module: used to acquire the grayscale image of the light spot array of the Shaker-Hartmann wavefront detector, detect the grayscale maximum coordinates of each light spot on the grayscale image, and divide the light spot array image into sub-aperture image regions corresponding one-to-one with the microlenses according to the grayscale maximum coordinates.

[0086] The main lobe image extraction module is used to extract the pixel gray values ​​within each sub-aperture image region to form a sub-aperture gray matrix. Based on the sub-aperture gray matrix, it obtains the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction respectively. The intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction is used to obtain the main lobe region of the light spot.

[0087] Threshold calculation module: used to obtain a threshold calculation region by subtracting the main lobe region from the sub-aperture image region, and select the maximum gray value in the threshold calculation region as the threshold of the sub-aperture image region;

[0088] Threshold reduction module: used to perform threshold reduction processing on all pixel grayscale within the sub-aperture image area to obtain a processed sub-aperture image for centroid calculation;

[0089] Spot centroid calculation module: used to calculate the position of the spot centroid in each sub-aperture image region based on the processed sub-aperture image.

[0090] Example 3

[0091] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the program to implement the Shaker-Hartmann wavefront detector centroid calculation method as described in Example 1.

[0092] Example 4

[0093] A computer-readable storage medium having a computer program stored thereon, characterized in that, when executed by a processor, the program implements the Shaker-Hartmann wavefront detector centroid calculation method as described in Example 1.

[0094] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0095] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0096] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0098] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for calculating the centroid of a Shaker-Hartmann wavefront detector, characterized in that, include: Acquire a grayscale image of the light spot array of the Shaker-Hartmann wavefront detector, detect the coordinates of the grayscale maxima of each spot on the grayscale image, and divide the light spot array image into sub-aperture image regions corresponding one-to-one with the microlenses according to the coordinates of the grayscale maxima. For each sub-aperture image region, the pixel gray values ​​within the sub-aperture image region are extracted to form a sub-aperture gray value matrix. Based on the sub-aperture gray value matrix, the one-dimensional image regions of the main lobe of the light spot in the row direction and the one-dimensional image regions in the column direction are obtained respectively. The intersection of the one-dimensional image regions in the row direction and the one-dimensional image regions in the column direction is obtained to obtain the main lobe region of the light spot. Specifically, this includes: summing the sub-aperture gray value matrix along the row direction and the column direction respectively to obtain row vectors and column vectors; performing first-order difference on the row vectors and column vectors to obtain row gradient sequences and column gradient sequences; determining the local maximum position corresponding to the rising edge and the local minimum position corresponding to the falling edge of the row gradient sequence and the column gradient sequence respectively; and determining the one-dimensional image regions in the row direction and the one-dimensional image regions in the column direction based on the interval between the local maximum and the local minimum; and obtaining the main lobe region of the light spot by the intersection of the two. The threshold calculation region is obtained by subtracting the main lobe region from the sub-aperture image region; The maximum gray value within the threshold calculation area is selected as the threshold of the sub-aperture image region; A threshold reduction process is performed on all pixel grayscale values ​​within the sub-aperture image region to obtain a processed sub-aperture image for centroid calculation; Based on the processed sub-aperture image, the position of the spot centroid is calculated in each sub-aperture image region.

2. The method for calculating the centroid of a Shaker-Hartmann wavefront detector according to claim 1, characterized in that, The step of detecting the grayscale maximum coordinates of each spot on the grayscale image and dividing the spot array image into sub-aperture image regions corresponding one-to-one with the microlenses based on the grayscale maximum coordinates includes: The gray-scale maximum coordinates of each spot are detected on the gray-scale image; taking each gray-scale maximum coordinate as the geometric center, the distance between it and the nearest neighboring gray-scale maximum coordinate is taken as the side length, and a square window centered on the geometric center is constructed, and the square window is used as the corresponding sub-aperture image region, and the boundaries of adjacent sub-aperture image regions are connected but do not overlap.

3. The method for calculating the centroid of a Shaker-Hartmann wavefront detector according to claim 1, characterized in that, The threshold reduction process includes: Within each sub-aperture image region, the gray value of each pixel is subtracted from the corresponding threshold, and the gray value of pixels whose gray value is less than zero after subtracting the threshold is set to zero, thus obtaining a processed image for calculating the centroid position of the spot.

4. The method for calculating the centroid of a Shaker-Hartmann wavefront detector according to claim 2, characterized in that, When performing gradient operations on row vectors and column vectors, the gradient operation is a discrete first-order difference operation, the difference operator is selected as [−1, +1], and the boundary processing strategy of mirroring or zero-filling is adopted for the two endpoints.

5. The method for calculating the centroid of a Shaker-Hartmann wavefront detector according to claim 2, characterized in that, The method of determining the one-dimensional image region in the row direction and the one-dimensional image region in the column direction by the interval between local maxima and local minima includes: Obtain the local maximum and local minimum coordinates in the row direction, determine the range of the local maximum and local minimum coordinates, and use it as a one-dimensional image region in the row direction; Obtain the local maximum and local minimum coordinates in the column direction, determine the range of the local maximum and local minimum coordinates, and use it as a one-dimensional image region in the column direction; When defining the range by the two coordinate intervals corresponding to the local maxima and local minima, the minimum and maximum widths of the range are constrained so that the one-dimensional image region satisfies the preset width range.

6. The method for calculating the centroid of a Shaker-Hartmann wavefront detector according to claim 1, characterized in that, When the intersection of a one-dimensional image region in the row direction and a one-dimensional image region in the column direction is taken to obtain the main lobe region, if the intersection region is empty or does not meet the preset area threshold, a backoff strategy is triggered: the one-dimensional candidate range of the row or column is expanded and the intersection is re-found to obtain a valid main lobe region.

7. A Shaker-Hartmann wavefront detector centroid calculation system, used to implement the Shaker-Hartmann wavefront detector centroid calculation method according to any one of claims 1-6, characterized in that, include: Segmentation module: used to acquire the grayscale image of the light spot array of the Shaker-Hartmann wavefront detector, detect the grayscale maximum coordinates of each light spot on the grayscale image, and divide the light spot array image into sub-aperture image regions corresponding one-to-one with the microlenses according to the grayscale maximum coordinates. The main lobe image extraction module is used to extract the pixel gray values ​​within each sub-aperture image region to form a sub-aperture gray matrix. Based on the sub-aperture gray matrix, it obtains the one-dimensional image region of the main lobe of the light spot in the row direction and the one-dimensional image region in the column direction respectively. The intersection of the one-dimensional image region in the row direction and the one-dimensional image region in the column direction is used to obtain the main lobe region of the light spot. Threshold calculation module: used to obtain a threshold calculation region by subtracting the main lobe region from the sub-aperture image region, and select the maximum gray value in the threshold calculation region as the threshold of the sub-aperture image region; Threshold reduction module: used to perform threshold reduction processing on all pixel grayscale within the sub-aperture image area to obtain a processed sub-aperture image for centroid calculation; Spot centroid calculation module: used to calculate the position of the spot centroid in each sub-aperture image region based on the processed sub-aperture image.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for calculating the centroid of a Shaker-Hartmann wavefront detector as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for calculating the centroid of the Shaker-Hartmann wavefront detector as described in any one of claims 1 to 6.

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