Hartmann wavefront recovery method and apparatus

Abstract

The application relates to the field of optical technology, and provides a Hartmann wavefront recovery method and device, wherein the method comprises the following steps: acquiring a light spot image collected by a Hartmann sensor; performing partition processing on the light spot image to obtain a plurality of sub-light spot images with intersection relations; performing wavefront recovery and difference processing on each sub-light spot image to obtain a plurality of sub-difference wave surface images; and performing recovery splicing processing on the plurality of sub-difference wave surface images according to the intersection relations to obtain a wavefront recovery image. Compared with the prior art, the Hartmann wavefront recovery method and device provided by the application realize wavefront reconstruction of optical systems with different shapes and apertures, and improve the universality of the optical systems.

Description

Technical Field

[0001] This invention relates to the field of optical technology, and more specifically, to a Hartmann wavefront recovery method and apparatus. Background Technology

[0002] Hartmann sensors have been widely used in adaptive optics systems. They can simultaneously measure the phase and intensity distributions of a light field at very high sampling frequencies, and can be pre-calibrated with a high-quality reference beam, eliminating the need for a reference beam during on-site measurements and making them insensitive to environmental conditions. Therefore, Hartmann wavefront sensors have been successfully applied in numerous fields, including laser beam quality diagnostics, optical component and system inspection, and atmospheric disturbance measurement.

[0003] Hartmann waves fronts measure the wavefront phase slope, requiring wavefront reconstruction to determine the phase value. There are two main types of reconstruction methods: the region method and the mode method. The Hartmann mode method calculates the wavefront phase error based on the wavefront slopes of each sub-aperture measured by the Hartmann sensor. In practical applications of Hartmann sensors, optical systems are often circular or annular; in applications such as laser beam quality measurement, rectangular aperture systems are also frequently encountered. The Hartmann mode method is relatively mature only for circular regions and has good results for Hartmann wavefront reconstruction with circular apertures. For non-circular apertures, the Hartmann wavefront reconstruction effect is poor. Therefore, different wavefront reconstruction methods are needed for optical systems with different aperture shapes, resulting in low versatility of optical systems. Summary of the Invention

[0004] The purpose of this invention is to provide a Hartmann wavefront reconstruction method and apparatus to improve the problem in the prior art that different wavefront reconstruction methods are required for optical systems with different aperture shapes, resulting in low versatility of the optical systems.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows:

[0006] In a first aspect, embodiments of the present invention provide a Hartmann wavefront restoration method, the method comprising: acquiring a spot image collected by a Hartmann sensor; partitioning the spot image to obtain multiple sub-spot images with an intersection relationship; performing wavefront restoration and differential processing on each sub-spot image to obtain multiple sub-differential wavefront images; and performing restoration and stitching processing on the multiple sub-differential wavefront images according to the intersection relationship to obtain a wavefront restored image.

[0007] Furthermore, the step of performing wavefront restoration and differential processing on each of the sub-spot images to obtain multiple sub-differential wavefront images includes: performing wavefront restoration on each of the sub-spot images to obtain multiple sub-wavefront images; and performing differential processing on each sub-wavefront image to obtain multiple sub-differential wavefront images.

[0008] Furthermore, the step of performing differential processing on each sub-wavefront image to obtain multiple sub-differential wavefront images includes: acquiring pixel data of each column in each sub-wavefront image; calculating the difference in pixel data between adjacent columns in each sub-wavefront image to obtain multiple sub-differential wavefront images.

[0009] Furthermore, the step of performing differential processing on each sub-wavefront image to obtain multiple sub-differential wavefront images includes: acquiring pixel data of each row in each sub-wavefront image; calculating the difference in pixel data between adjacent rows in each sub-wavefront image to obtain multiple sub-differential wavefront images.

[0010] Furthermore, the step of restoring and stitching multiple sub-difference wavefront images according to the intersection relationship to obtain a wavefront restored image includes: stitching and fusing multiple sub-difference wavefront images according to the intersection relationship to obtain a difference fused image; and integrating the difference fused image to obtain the wavefront restored image.

[0011] Secondly, embodiments of the present invention provide a Hartmann wavefront restoration device, comprising: an image acquisition module for acquiring a spot image collected by a Hartmann sensor; a partitioning processing module for partitioning the spot image to obtain multiple sub-spot images with an intersection relationship; a restoration difference module for performing wavefront restoration and difference processing on each sub-spot image to obtain multiple sub-difference wavefront images; and a restoration stitching module for performing restoration stitching processing on the multiple sub-difference wavefront images according to the intersection relationship to obtain a wavefront restored image.

[0012] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0013] This invention provides a Hartmann wavefront reconstruction method and apparatus, which acquires a spot image collected by a Hartmann sensor; partitions the spot image to obtain multiple sub-spot images with an intersection relationship; performs wavefront reconstruction and differential processing on each sub-spot image to obtain multiple sub-differential wavefront images; and performs reconstruction and stitching processing on the multiple sub-differential wavefront images according to the intersection relationship to obtain a wavefront reconstruction image. This method enables wavefront reconstruction of optical systems with different aperture shapes and improves the versatility of optical systems. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For users of ordinary skills in the art, other related drawings can be obtained from these drawings without creative effort.

[0015] Figure 1 A schematic diagram of the structure of the Hartmann sensor provided in an embodiment of the present invention is shown;

[0016] Figure 2 A flowchart of the Hartmann wavefront restoration method provided in an embodiment of the present invention is shown;

[0017] Figure 3 A schematic diagram of light spot images with different aperture shapes provided in embodiments of the present invention is shown;

[0018] Figure 4 for Figure 2 The flowchart of the sub-steps of step S3 is shown below;

[0019] Figure 5 A schematic diagram of a sub-wavefront image provided in an embodiment of the present invention is shown;

[0020] Figure 6 A schematic diagram of a sub-differential wavefront image provided in an embodiment of the present invention is shown;

[0021] Figure 7 for Figure 4 The flowchart of the first sub-step of step S32 is shown below;

[0022] Figure 8 for Figure 4 The flowchart of the second sub-step of step S32 is shown below;

[0023] Figure 9 for Figure 2 The flowchart of the sub-steps of step S4 is shown below;

[0024] Figure 10 A schematic diagram of a differential fusion image provided in an embodiment of the present invention is shown;

[0025] Figure 11 A schematic diagram of a wavefront-restored image provided in an embodiment of the present invention is shown;

[0026] Figure 12 A block diagram of the Hartmann wavefront recovery device provided in an embodiment of the present invention is shown;

[0027] Reference numerals: 200 - Hartmann wavefront restoration device; 210 - Image acquisition module; 220 - Partition processing module; 230 - Restoration difference module; 240 - Restoration stitching module. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0029] The Hartmann wavefront recovery method provided in this invention is applied to Hartmann sensors. Please refer to [link / reference]. Figure 1 , Figure 1 The diagram illustrates the structure of a Hartmann sensor provided in an embodiment of the present invention. The Hartmann sensor includes a microlens array and a complementary metal-oxide-semiconductor (CMOS) unit. The microlens array modulates the measured optical field image into a speckle / dot matrix image. The microlens array can be circular or hexagonal. The CMOS unit is used to acquire the speckle image of the measured optical field modulated by the microlens array, which contains wavefront phase information. The CMOS unit can be an ON Semiconductor 5000.

[0030] First Embodiment

[0031] Please see Figure 2 , Figure 2 A flowchart of the Hartmann wavefront recovery method provided in an embodiment of the present invention is shown. The Hartmann wavefront recovery method includes the following steps:

[0032] S1, acquire the light spot image collected by the Hartmann sensor.

[0033] In this embodiment of the invention, the light spot image can be a spot image of the measured light field modulated by a microlens array and incorporating wavefront phase information, acquired by a CMOS unit. When the aperture of the Hartmann sensor has different shapes, the acquired light spot images will also be different. The aperture of the Hartmann sensor can be rectangular, triangular, elliptical, or other irregular shapes. Please refer to [link / reference]. Figure 3 , Figure 3 The diagram illustrates light spot images of different shapes and apertures provided in embodiments of the present invention.

[0034] S2, partition the spot image to obtain multiple sub-spot images with overlapping relationships.

[0035] In this embodiment of the invention, a sub-spot image can be an image of a circular sub-region within a spot image. The step of partitioning the spot image to obtain multiple intersecting sub-spot images can be understood as partitioning the spot image using circles of the same size to obtain multiple sub-spot images of equal size. The union of all sub-spot images constitutes the spot image, and for any one of these sub-spot images, it has an intersection with at least one other sub-spot image.

[0036] S3. Wavefront restoration and differential processing are performed on each sub-spot image to obtain multiple sub-differential wavefront images.

[0037] Please see Figure 4 Step S3 may include the following sub-steps:

[0038] S31, wavefront restoration is performed on each sub-spot image to obtain multiple sub-wavefront images.

[0039] In this embodiment of the invention, the wavefront image can be the image obtained after wavefront reconstruction of the sub-spot image. Please refer to [link to relevant documentation]. Figure 5 , Figure 5 A schematic diagram of a sub-wavefront image provided in an embodiment of the present invention is shown. The step of performing wavefront restoration on each sub-spot image to obtain multiple sub-wavefront images can be understood as follows: wavefront restoration is performed on the sub-spot images using the Hartmann mode method or the region reconstruction method to obtain sub-wavefront images. The same processing described above is performed on each sub-spot image to obtain multiple sub-wavefront images.

[0040] The Hartmann mode method is an algorithm for calculating the wavefront phase error based on the wavefront slope of each sub-aperture measured by the Hartmann sensor. Among the Hartmann mode methods, the Zernike mode method is a commonly used wavefront reconstruction algorithm. For wavefront phase distortion in a circular region, reconstruction is usually performed using circular domain Zernike polynomials that are orthogonal in the circular domain.

[0041] A complete wavefront Φ(x,y) can be described using Zernike polynomials:

[0042]

[0043] Where a0 is the average phase wavefront, a k Z represents the coefficient of the k-th Zernike polynomial. k Let ε be the k-th Zernike polynomial, and ε be the wavefront phase measurement error. After obtaining the mode coefficients of the wavefront error from the slope measurements, the expression for the entire wavefront can be obtained, and thus the wavefront error at each control point can be calculated. For example, for a Hartmann sensor, the relationship between the slope data within the sub-aperture and the Zernike polynomial coefficients is:

[0044]

[0045] Where ε x ε y The wavefront phase measurement error is represented by n, where n is the mode order and S is the wavefront phase measurement error. i Let be the normalized area of ​​the sub-aperture. The relationship between the n Zernike coefficients of the slopes of the m sub-apertures can be represented by a matrix as follows:

[0046]

[0047] It is denoted as: G = DA + ε

[0048] Due to the imperfect orthogonality of the Zernike function's partial derivatives and its non-orthogonality at finite sampling points, the rank of matrix D may be incomplete, and the condition number of the equation may also vary. For any 2m and n, the least-squares solution to the above equation can be obtained using the generalized inverse D. + express:

[0049] A = D + G+(ID + D)Y

[0050] Where Y is an arbitrary vector, and when Y = 0, the equation lies in least squares ||D. + The solutions in the sense of DA||=min and minimum norm ||A||=min are:

[0051] A = D + G

[0052] Where ||·|| denotes the Euclidean norm. Thus, we only need to find the inverse matrix D of D. + That is, the Zernike coefficient α can be calculated. k Calculate the wavefront phase. Calculate the inverse matrix D of D. + There are generally three methods for solving this problem: ordinary least squares, Gram-Schmidt orthogonalization, and singular value decomposition (SVD). Among them, SVD is an algorithm with excellent numerical stability. Regardless of the matrix condition number, the generalized inverse equation obtained by SVD can always yield a stable solution in the least squares minimum norm sense.

[0053] The principle of the region reconstruction method is to interpolate the wavefront phase using the measured slopes at the four neighboring positions (no more than four points) of the phase point to be estimated. If it is assumed that the boundary effects can be approximately ignored after appropriate segmentation of the sub-aperture array, then independent wavefront reconstruction of each block with the addition of specific correction values ​​is equivalent to the usual algorithm described above. This reduces computational load without significantly impacting estimation accuracy; this is the basic idea behind segmented wavefront reconstruction. Region-based wavefront reconstruction recovers the wavefront phase value from the wavefront slope measured by the wavefront detector.

[0054] S32, perform differential processing on each sub-wavefront image to obtain multiple sub-differential wavefront images.

[0055] In this embodiment of the invention, the sub-difference wavefront image can be the image obtained after performing difference processing on a sub-wavefront image. Please refer to [link to relevant documentation]. Figure 6 , Figure 6 The diagram illustrates a sub-difference wavefront image provided in an embodiment of the present invention. The step of performing differential processing on each sub-wavefront image to obtain multiple sub-difference wavefront images can be understood as follows: the sub-wavefront images are differentially processed using rows / columns as the standard to obtain sub-difference wavefront images; the same processing described above is performed on each sub-wavefront image to obtain multiple sub-difference wavefront images.

[0056] Please see Figure 7 Step S32 may include the following sub-steps:

[0057] S321, obtain the pixel data of each column in each sub-wavefront image.

[0058] In this embodiment of the invention, pixel data can represent pixel values.

[0059] S322, calculate the pixel data difference between adjacent columns in each sub-wavefront image to obtain multiple sub-difference wavefront images.

[0060] In this embodiment of the invention, the step of calculating the pixel data difference between adjacent columns in each sub-wavefront image to obtain multiple sub-difference wavefront images can be understood as follows: The pixel data difference is obtained by subtracting the pixel data of the left column from the pixel data of the right column of the sub-wavefront image. This pixel data difference is then used to construct the sub-difference wavefront image (subtracting the first column from the second column of the sub-wavefront image pixel data yields the first column of the sub-difference wavefront image pixel data; subtracting the second column from the third column yields the second column of the sub-difference wavefront image pixel data, and so on, but the last column has no pixel data on its right side, so it is discarded, thus obtaining the sub-difference wavefront image). Performing the same processing on each sub-wavefront image yields multiple sub-difference wavefront images.

[0061] Please see Figure 8 Step S32 may also include the following sub-steps:

[0062] S323, obtain the pixel data of each row in each sub-wavefront image.

[0063] S324, calculate the pixel data difference between adjacent rows in each sub-wavefront image to obtain multiple sub-difference wavefront images.

[0064] In this embodiment of the invention, the step of calculating the pixel data difference between adjacent rows in each sub-wavefront image to obtain multiple sub-difference wavefront images can be understood as follows: The pixel data difference is obtained by subtracting the pixel data of the previous row from the pixel data of the next row of the sub-wavefront image. This pixel data difference is then used to construct the sub-difference wavefront image (subtracting the first row from the second row of pixel data in the sub-wavefront image yields the first row of pixel data; subtracting the second row from the third row yields the second row, and so on, until the last row, which is discarded due to the lack of pixel data). Performing the same processing on each sub-wavefront image yields multiple sub-difference wavefront images.

[0065] S4. Based on the intersection relationship, multiple sub-difference wavefront images are restored and stitched together to obtain the wavefront restored image.

[0066] Please see Figure 9 Step S4 may include the following sub-steps:

[0067] S41. Multiple sub-difference wavefront images are stitched and fused according to the intersection relationship to obtain a difference fused image.

[0068] In this embodiment of the invention, the differentially fused image can be an image obtained by stitching and fusing multiple sub-differential wavefront images according to their intersection relationship. Please refer to [link to relevant documentation]. Figure 10 , Figure 10 This diagram illustrates a differential fusion image provided by an embodiment of the present invention. When restoring sub-spot images using the Hartmann mode method or region reconstruction method, the relative wavefront undulations between sub-spot images cannot be measured; therefore, the relative undulation offset of the restored wavefronts of the sub-spot images is required for stitching. After differential processing of the sub-wavefront images, there is no relative undulation offset between the sub-differential wavefront images, allowing for direct stitching. During segmentation, the sub-wavefront images have an intersection relationship; therefore, the pixel data in the intersection is consistent. Using image stitching, all sub-differential wavefront images are matched to find the corresponding relationships. Then, all sub-differential wavefront images are transformed into a coordinate system, and by merging the overlapping pixel data, they are fused into a differential fusion image with a larger canvas.

[0069] S42, integrate the differential fusion image to obtain the wavefront reconstruction image.

[0070] In this embodiment of the invention, the wavefront-reconstructed image is the image obtained by integrating the differentially fused image. Please refer to [link / reference]. Figure 11 , Figure 11This diagram illustrates a wavefront reconstruction image provided by an embodiment of the present invention. The step of integrating the differentially fused image to obtain the wavefront reconstruction image can be understood as integrating the differentially fused image using rows / columns as the standard to obtain the wavefront reconstruction image. Specifically, the differentially fused image undergoes integration processing corresponding to step S32 to obtain the wavefront reconstruction image. When step S32 uses rows as the standard for differencing, step S42 integrates using rows as the standard; when step S32 uses columns as the standard for differencing, step S42 integrates using columns as the standard.

[0071] Compared with the prior art, the embodiments of the present invention have the following advantages:

[0072] By acquiring the spot image collected by the Hartmann sensor, the spot image is partitioned to obtain multiple sub-spot images with an intersection relationship. Wavefront reconstruction and differential processing are performed on each sub-spot image to obtain multiple sub-differential wavefront images. Based on the intersection relationship, the multiple sub-differential wavefront images are restored and stitched together to obtain the wavefront restored image. This method realizes wavefront reconstruction of optical systems with different shapes and apertures, improves the versatility of the optical system, and omits the scanning process, thereby increasing the speed of wavefront reconstruction and stitching.

[0073] Second Embodiment

[0074] Please see Figure 12 , Figure 12 A block diagram of a Hartmann wavefront restoration device provided in an embodiment of the present invention is shown. The Hartmann wavefront restoration device 200 includes an image acquisition module 210, a partitioning processing module 220, a restoration difference module 230, and a restoration stitching module 240.

[0075] Image acquisition module 210 is used to acquire the light spot image collected by the Hartmann sensor.

[0076] This can be understood as the image acquisition module 210 performing the above step S1.

[0077] The partitioning module 220 is used to partition the spot image to obtain multiple sub-spot images with overlapping relationships.

[0078] This can be understood as the partition processing module 220 performing the above step S2.

[0079] The restoration difference module 230 is used to perform wavefront restoration and difference processing on each sub-spot image to obtain multiple sub-difference wavefront images.

[0080] This can be understood as the restoration difference module 230 performing the above step S3.

[0081] In this embodiment of the invention, the restoration difference module 230 includes a wavefront restoration unit and a difference processing unit. The wavefront restoration unit is used to perform wavefront restoration on each sub-spot image to obtain multiple sub-wavefront images; the difference processing unit is used to perform difference processing on each sub-wavefront image to obtain multiple sub-difference wavefront images.

[0082] The differential processing unit is specifically used to: acquire the pixel data of each column in each sub-wavefront image; calculate the difference in pixel data between adjacent columns in each sub-wavefront image to obtain multiple sub-differential wavefront images.

[0083] The differential processing unit can also be specifically used to: acquire pixel data of each row in each sub-wavefront image; calculate the difference in pixel data between adjacent rows in each sub-wavefront image to obtain multiple sub-differential wavefront images.

[0084] The restoration and stitching module 240 is used to restore and stitch multiple sub-difference wavefront images based on their intersection relationship to obtain a wavefront restoration image.

[0085] This can be understood as the restoration and splicing module 240 performing the above step S4.

[0086] In this embodiment of the invention, the restoration and stitching module is specifically used to: stitch and fuse multiple sub-differential wavefront images according to the intersection relationship to obtain a differential fused image; and integrate the differential fused image to obtain a wavefront restoration image.

[0087] In summary, embodiments of the present invention provide a Hartmann wavefront reconstruction method and apparatus. The method includes: acquiring a spot image collected by a Hartmann sensor; partitioning the spot image to obtain multiple sub-spot images with intersection; performing wavefront reconstruction and differential processing on each sub-spot image to obtain multiple sub-differential wavefront images; and performing reconstruction and stitching processing on the multiple sub-differential wavefront images according to their intersection to obtain a wavefront-reconstructed image. Compared with the prior art, the Hartmann wavefront reconstruction method provided by embodiments of the present invention has the following advantages: it enables wavefront reconstruction for optical systems with different aperture shapes, improves the versatility of optical systems, and eliminates the scanning process, thereby increasing the speed of wavefront reconstruction and stitching.

[0088] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0089] If the aforementioned function is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0090] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0091] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of protection of the invention. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

Claims

1. A Hartmann wavefront reconstruction method, characterized by, The method comprises: acquiring a light spot image collected by a Hartmann sensor; performing partition processing on the light spot image to obtain a plurality of sub-light spot images having an intersection relationship; performing wavefront reconstruction and difference processing on each of the sub-light spot images to obtain a plurality of sub-difference wave surface images; wherein the wavefront reconstruction and difference processing comprises: performing wavefront reconstruction on each of the sub-light spot images to obtain a plurality of sub-wave surface images; and performing difference processing on each of the sub-wave surface images to obtain a plurality of sub-difference wave surface images; wherein the difference processing comprises: acquiring pixel data of each column in each of the sub-wave surface images and calculating a difference in pixel data between adjacent columns, or acquiring pixel data of each row in each of the sub-wave surface images and calculating a difference in pixel data between adjacent rows; performing reconstruction splicing processing on the plurality of sub-difference wave surface images according to the intersection relationship to obtain a wavefront reconstruction image; wherein the reconstruction splicing processing comprises: splicing and fusing the plurality of sub-difference wave surface images according to the intersection relationship to obtain a difference fusion image; and integrating the difference fusion image.

2. A Hartmann wavefront reconstruction device, characterized by The Hartmann wavefront reconstruction device comprises: an image acquisition module configured to acquire a light spot image collected by a Hartmann sensor; a partition processing module configured to perform partition processing on the light spot image to obtain a plurality of sub-light spot images having an intersection relationship; a reconstruction and difference module configured to perform wavefront reconstruction and difference processing on each of the sub-light spot images to obtain a plurality of sub-difference wave surface images; wherein the reconstruction and difference module comprises: a wavefront reconstruction unit configured to perform wavefront reconstruction on each of the sub-light spot images to obtain a plurality of sub-wave surface images; and a difference processing unit configured to perform difference processing on each of the sub-wave surface images to obtain a plurality of sub-difference wave surface images; wherein the difference processing unit is specifically configured to: acquire pixel data of each column in each of the sub-wave surface images and calculate a difference in pixel data between adjacent columns, or acquire pixel data of each row in each of the sub-wave surface images and calculate a difference in pixel data between adjacent rows; a reconstruction and splicing module configured to perform reconstruction splicing processing on the plurality of sub-difference wave surface images according to the intersection relationship to obtain a wavefront reconstruction image; wherein the reconstruction and splicing module is specifically configured to: splicing and fuse the plurality of sub-difference wave surface images according to the intersection relationship to obtain a difference fusion image; and integrate the difference fusion image to obtain the wavefront reconstruction image.

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