Aspherical surface shape detection distortion correction method, device, equipment and medium

Abstract

The application provides a non-spherical surface shape detection distortion correction method, device, equipment and medium, and relates to the optical technology field. The method determines the first CCD coordinates corresponding to each data point without distortion by operating the preset distortion model of the distortion parameter, determines the second CCD coordinates in the case of distortion, and then fills in each data point without distortion. The mapping relationship between the actual mirror and the CGH is used to establish the relationship between the actual mirror and the CCD coordinates by taking the CGH as a medium, so as to complete the correction of the imaging distortion and output more accurate non-spherical surface shape data. The above process does not need to set up physical markers on the actual mirror, avoids the influence of the physical markers on the high-precision optical element, simplifies the operation process of the non-spherical surface shape detection, and improves the distortion correction efficiency and accuracy.

Description

Technical Field

[0001] This application relates to the field of optical technology, and in particular to a method, apparatus, device and medium for aspherical surface shape detection and distortion correction. Background Technology

[0002] In recent years, ultra-precision optical components have been increasingly used in astronomical optics and applied optics, thus placing higher demands on high-precision optical processing and inspection technologies. With the development of optical inspection technology, computer-generated holograms (CGHs) are being used more and more widely in the field of optical inspection. CGHs are characterized by their small size, high degree of design freedom, ease of assembly and adjustment, and ability to inspect aspherical and free-form surface components with high asphericity. However, CGH inspection introduces distortion, and interferometers also suffer from aberrations such as spherical aberration, coma, and astigmatism during inspection, affecting the final inspection results. To achieve high-precision manufacturing of complex surfaces, distortion correction is necessary.

[0003] Traditional distortion correction methods require making numerous marks on the actual mirror surface of the optical element. The distortion error of the entire surface is then calculated by comparing the actual and post-detection positions of these marks. This method is complex and time-consuming, impacting correction efficiency. Furthermore, improper selection of the mark positions can lead to larger calculation errors, affecting the accuracy of distortion correction and making it difficult to measure the actual surface shape of the optical element. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, device, and medium for aspherical surface shape detection and distortion correction, aiming to solve the technical problem of how to quickly and accurately detect the surface shape of aspherical optical elements.

[0005] To achieve the above objectives, this application provides a method for aspherical surface shape detection distortion correction, the steps of which include:

[0006] Obtain the first CCD coordinates of several data points in a distortion-free space;

[0007] Substitute each of the first CCD coordinates into a preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space.

[0008] Each of the second CCD coordinates is filled into the corresponding data points in the distortion-free space to obtain the geometrically corrected interference image.

[0009] Based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface, the imaging distortion of the interference image is corrected to obtain aspherical surface shape data.

[0010] In one embodiment, before the step of substituting each of the first CCD coordinates into a preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space, the method further includes:

[0011] Several targets are set up in the alignment area of ​​the CGH;

[0012] Obtain the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target.

[0013] Based on the design coordinates of each CGH and the pixel coordinates of each CCD, the distortion coefficients of the initial distortion model are solved.

[0014] The distortion coefficients are substituted into the initial distortion model to obtain the preset distortion model.

[0015] In one embodiment, the distortion coefficients include radial distortion coefficients and tangential distortion coefficients, and the step of solving the distortion coefficients of the initial distortion model based on the design coordinates of each CGH and the pixel coordinates of each CCD includes:

[0016] Calculate the angular offset between the CGH design coordinates and the CCD pixel coordinates;

[0017] Based on the angle offset, obtain the CCD prediction coordinates corresponding to each of the CGH design coordinates in the distortion-free space;

[0018] Obtain the corresponding sets of residuals between the predicted coordinates of each CCD and the pixel coordinates of each CCD;

[0019] The radial distortion coefficient and the tangential distortion coefficient of the initial distortion model are obtained by solving the residuals of each group using the nonlinear least squares method.

[0020] In one embodiment, the step of obtaining the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target includes:

[0021] Determine the target shape for each of the aforementioned targets;

[0022] When the target shape is a polygon or a marker graphic with multiple non-collinear feature points, the vertices of each polygon or the feature points of the marker graphic are used as the corresponding calibration points, and the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point are obtained.

[0023] Alternatively, when the target shape is circular, the center of each circle is taken as the corresponding calibration point, and the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point are obtained.

[0024] In one embodiment, the step of obtaining the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model by solving for each group of residuals using the nonlinear least squares method includes:

[0025] The design matrix and transpose matrix are obtained by using the coordinates of each CCD pixel and its corresponding radial distance.

[0026] Based on the design matrix, the transpose matrix, and the observation vectors corresponding to each set of residuals, the first equation of the nonlinear least squares method is solved to obtain the radial distortion coefficient and the tangential distortion coefficient.

[0027] In one embodiment, the step of obtaining the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model by solving for each group of residuals using the nonlinear least squares method includes:

[0028] The design matrix is ​​obtained by using the coordinates of each CCD pixel and its corresponding radial distance, and the observation vector is obtained by using each set of residuals.

[0029] Singular value decomposition is performed on the design matrix to obtain the second equation of the nonlinear least squares method;

[0030] Based on the observed value vector, the second equation is solved to obtain the radial distortion coefficient and the tangential distortion coefficient.

[0031] In one embodiment, before the step of correcting the imaging distortion of the interferometric image based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface to obtain aspherical surface shape data, the method further includes:

[0032] The preset mapping relationship is obtained by using a preset ray tracing file.

[0033] Furthermore, to achieve the above objectives, this application also provides an aspherical surface shape detection distortion correction device, the aspherical surface shape detection distortion correction device comprising:

[0034] The distortion-free data acquisition module is used to acquire the first CCD coordinates of several data points in the distortion-free space;

[0035] The distortion data acquisition module is used to substitute each of the first CCD coordinates into a preset distortion model for calculation, and obtain the corresponding second CCD coordinates in the distortion space.

[0036] The data geometric correction module is used to fill each of the second CCD coordinates onto the corresponding data points in the distortion-free space to obtain the geometrically corrected interference image.

[0037] The mirror data output module corrects the imaging distortion of the interference image based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface, thereby obtaining aspherical surface shape data.

[0038] In addition, to achieve the above objectives, this application also provides an aspherical surface shape detection distortion correction device, the aspherical surface shape detection distortion correction device comprising: a memory, a processor, and an aspherical surface shape detection distortion correction program stored in the memory and executable on the processor, the aspherical surface shape detection distortion correction program being configured to implement the steps of the aspherical surface shape detection distortion correction method as described above.

[0039] In addition, to achieve the above objectives, this application also provides a storage medium, which is a computer-readable storage medium, storing an aspherical surface shape detection distortion correction program. When the aspherical surface shape detection distortion correction program is executed by a processor, it implements the steps of the aspherical surface shape detection distortion correction method described above.

[0040] This application provides a method, apparatus, device, and medium for aspherical surface shape detection and distortion correction. The aspherical surface shape detection and distortion correction method includes the following steps: acquiring the coordinates of a plurality of data points in a distortion-free space using a first CCD; substituting the first CCD coordinates into a preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space; filling the corresponding data points in the distortion-free space with the second CCD coordinates to obtain a geometrically corrected interference image; and correcting the imaging distortion of the interference image based on a preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface to obtain aspherical surface shape data.

[0041] By calculating the first CCD coordinates corresponding to each distortion-free data point using a preset distortion model with defined distortion parameters, the second CCD coordinates under distortion conditions are determined and then filled into the distortion-free data points. Then, utilizing the mapping relationship between the actual mirror surface and the CGH (Chip GH), a relationship between the actual mirror surface and the CCD coordinates is established using the CGH as a medium, thereby completing the correction of imaging distortion and facilitating the output of more accurate aspherical surface shape data. This process eliminates the need for physical markings on the actual mirror surface, avoiding the influence of physical markings on high-precision optical components, simplifying the aspherical surface shape detection operation, and improving distortion correction efficiency and accuracy. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating an embodiment of the aspherical surface shape detection distortion correction method of this application.

[0045] Figure 2 This is a flowchart illustrating Embodiment 2 of the aspherical surface shape detection distortion correction method of this application;

[0046] Figure 3 A schematic diagram of the first target shape provided in this application;

[0047] Figure 4 A schematic diagram of the second target shape provided in this application;

[0048] Figure 5 A schematic diagram of the third target shape provided in this application;

[0049] Figure 6 This is a flowchart illustrating Embodiment 3 of the aspherical surface shape detection distortion correction method of this application;

[0050] Figure 7 This is a schematic diagram of the module structure of the aspherical surface shape detection and distortion correction device according to an embodiment of this application;

[0051] Figure 8 This is a schematic diagram of the aspherical surface shape detection and distortion correction device according to an embodiment of this application.

[0052] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0054] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0055] This application presents a first embodiment of the aspherical surface shape detection distortion correction method. Please refer to [link / reference]. Figure 1 The steps of the aspherical surface shape detection distortion correction method include:

[0056] Step S10: Obtain the coordinates of the first CCD for several data points in the distortion-free space;

[0057] It should be understood that, in this embodiment, the executing entity can be a device or apparatus for surface shape detection of an optical element with an aspherical surface, which can accurately detect complex aspherical surface shapes through CGH detection.

[0058] It should be noted that when using the CGH (Concurrent Headlight) detection method, an interferometer is typically used as the light source. A beam splitter divides the laser light from the source into two paths: one path serves as a reference beam, which is reflected by a standard mirror inside the interferometer to generate an ideal reference wavefront; the other path serves as the test beam, which, after passing through the CGH, becomes a test wavefront that perfectly matches the theoretical shape of the aspheric surface, and is then directed towards the mirror under test. The CGH can convert the planar test wavefront into a theoretical aspheric wavefront, compensating for the significant deviation between the aspheric surface and the best-fit sphere. The test wavefront is reflected by the mirror, passes through the CGH again, carrying information about the mirror's true surface shape error, and returns to the interferometer. The returning test wavefront and the reference wavefront superimpose at the beam splitter, forming interference fringes. At this point, the charge-coupled device (CCD) camera located at the interferometer's imaging port can capture the entire fringe pattern in one image, converting the light signal into a digital image and sending it to the computer. Finally, the computer, using a specific algorithm, maps the pixel coordinates on the CCD image to the actual mirror coordinates, completing the surface shape detection of the aspheric optical element. However, when using CGH to inspect the surface shape of optical elements, distortion is introduced, so distortion correction is still required.

[0059] It should be understood that traditional surface shape detection methods require attaching alignment targets to the actual mirror surface of the optical element to provide a measurement scale, thereby establishing a mapping relationship between pixel coordinates on the CCD image and actual mirror surface coordinates. This method not only contaminates the actual mirror surface of the optical element, but its accuracy is also limited by the manufacturing and assembly errors of the CGH.

[0060] It should be noted that the CGH design file can be understood as a digital drawing used when designing the CGH, which is used to convert the ideal wavefront aberration into a machinable microstructure. In this embodiment, the CCD coordinates corresponding to the ideal data points in distortion-free space, i.e., the aforementioned first CCD coordinates, can be obtained through the CGH design file.

[0061] It is worth noting that, in this embodiment, the data points obtained in the distortion-free space that have not undergone distortion can specifically be N*M data points, which together form a matrix to improve the calculation accuracy.

[0062] Step S30: Substitute each of the first CCD coordinates into the preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space;

[0063] It should be noted that, in this embodiment, the preset distortion model refers to a pre-trained computational model used to characterize the distortion behavior of each pixel in a CCD image.

[0064] It is easy to understand that, in this embodiment, the first CCD coordinates that have not undergone distortion can be substituted into a preset distortion model for calculation, thereby obtaining the CCD coordinates corresponding to each data point in the distortion space, that is, the aforementioned second CCD coordinates.

[0065] Step S40: Fill each of the second CCD coordinates into the corresponding data points in the distortion-free space to obtain the geometrically corrected interference image;

[0066] It is easy to understand that, in this embodiment, after obtaining the distorted coordinates of each second CCD, they can be sequentially filled back into the corresponding data points in the originally defined distortion-free space, thereby obtaining an interference image composed of the distorted second CCD coordinates in the distortion-free space. This process is equivalent to eliminating the CCD's imaging distortion by mapping the coordinates of each data point in the CCD image before and after distortion; therefore, it can also be understood as obtaining a geometrically corrected interference image.

[0067] It is worth noting that, in this embodiment, the coordinates of each point on the interferometric image after the above geometric correction can be regarded as CGH coordinates on CGH.

[0068] Step S50: Based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface, the imaging distortion of the interference image is corrected to obtain aspherical surface shape data.

[0069] It should be noted that there is a mapping relationship between the CGH and the actual mirror surface of the optical element, namely the aforementioned preset mapping relationship. This preset mapping relationship is a known quantity derived during the CGH design stage. In this embodiment, the aforementioned preset mapping relationship can be used to correct the imaging distortion of the geometrically corrected interference image, and the aspherical surface shape data of the optical element under test can be output simultaneously with the completion of imaging distortion correction.

[0070] It is worth noting that in this embodiment, a two-level mapping is constructed between the CCD pixel coordinates, CGH design coordinates, and actual mirror coordinates through a preset distortion model and the aforementioned preset mapping relationship. Pixel distortion is removed using the CGH and the preset distortion model, and then the CGH coordinates are accurately converted to the physical mirror coordinates using the preset mapping relationship. This not only improves the accuracy of surface shape measurement but also eliminates the need to design alignment targets on the actual mirror surface of the optical element, reducing contamination of the actual mirror surface and further improving measurement accuracy and efficiency.

[0071] This application provides a distortion correction method for aspherical surface shape detection. This method calculates the first CCD coordinates corresponding to each distortion-free data point using a preset distortion model with determined distortion parameters, and then determines the second CCD coordinates under distortion conditions, which are then filled into the distortion-free data points. Furthermore, utilizing the mapping relationship between the actual mirror surface and the CGH (Chip-Glass Frame), a relationship between the actual mirror surface and the CCD coordinates is established using the CGH as a medium, thereby completing the correction of imaging distortion and facilitating the output of more accurate aspherical surface shape data. The above process eliminates the need for physical markings on the actual mirror surface, avoiding the influence of physical markings on high-precision optical components, simplifying the aspherical surface shape detection operation, and improving distortion correction efficiency and accuracy.

[0072] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 3 , Figure 4 as well as Figure 5 In this embodiment, before the step of substituting each of the first CCD coordinates into a preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space, the method further includes:

[0073] Step S21: Set up several targets in the alignment area of ​​CGH;

[0074] It should be noted that the CGH mainly includes a main detection area for measurement and an alignment area surrounding the main detection area. The alignment area contains auxiliary patterns to provide positional references for the CGH image. In this embodiment, instead of setting alignment targets on the actual mirror surface, several alignment targets are set in the alignment area of ​​the CGH, with the number being 12 to 20.

[0075] Step S22: Obtain the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target.

[0076] It should be noted that the target can be a specific pattern, and calibration points for calibration can be set within the pattern. In this embodiment, the theoretical coordinates of the calibration points of each target in the CGH design file, i.e., the aforementioned CGH design coordinates, can be obtained through the CGH design file. Simultaneously, the actual pixel coordinates of the calibration points of each target in the CCD image can also be obtained, i.e., the aforementioned CCD pixel coordinates.

[0077] Step S23: Based on the design coordinates of each CGH and the pixel coordinates of each CCD, solve for the distortion coefficients of the initial distortion model;

[0078] Step S24: Input the distortion coefficients into the initial distortion model to obtain the preset distortion model.

[0079] It is easy to understand that, in this embodiment, there is a one-to-one mapping relationship between the CGH design coordinates corresponding to each target on the CGH and the CCD pixel coordinates corresponding to each target in the CCD image. Therefore, by substituting the above two sets of data into the initial distortion model, we can determine how each target is distorted between the CGH and CCD, thereby solving for the unknowns set in the initial distortion model, namely the distortion coefficients used to describe the distortion behavior. Subsequently, the solved distortion coefficients can be substituted back into the initial distortion model to obtain the preset distortion model that determines the distortion coefficients.

[0080] Further, in this embodiment, the step of obtaining the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target includes:

[0081] Step S221: Determine the target shape of each target;

[0082] It should be noted that the target is mainly used for position calibration, and its shape can be selected according to actual needs. In this embodiment, the target shape can be specifically set as a polygon (e.g., Figure 3 The rectangular / rectangular shape shown) and the labeled image with multiple non-collinear feature points (e.g. Figure 4 (as shown in the cross shape) or as Figure 5 The circle shown.

[0083] Step S222: When the target shape is a polygon or a marker graphic with multiple non-collinear feature points, the vertices of each polygon or the feature points of the marker graphic are used as the corresponding calibration points, and the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point are obtained.

[0084] Step S223, or, when the target shape is circular, take the center of each circle as the corresponding calibration point, and obtain the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point.

[0085] It is easy to understand that in this embodiment, if the target shape is a polygon, then each vertex of the polygon can be used as the aforementioned calibration point; if the target shape is a marker image with multiple non-collinear feature points, then each feature point of the marker image can be used as the aforementioned calibration point; if the target shape is circular, then the center of the circle can be used as the aforementioned calibration point. After establishing the calibration points of the current target, the corresponding CGH design coordinates of each calibration point for each target in the CGH design file can be obtained, and the CCD pixel coordinates corresponding to the images of each calibration point observed on the CCD can be obtained.

[0086] Furthermore, in this embodiment, the distortion coefficients include radial distortion coefficients and tangential distortion coefficients, and the step of solving the distortion coefficients of the initial distortion model based on the design coordinates of each CGH and the pixel coordinates of each CCD includes:

[0087] Step S231: Calculate the angular offset between each of the CGH design coordinates and each of the CCD pixel coordinates;

[0088] It is easy to understand that, in this embodiment, after obtaining the design coordinates of each CGH and the corresponding CCD pixel coordinates, the angular error between the CGH's angular placement and the CCD's relative position can be fitted through the correspondence between the two sets of data, that is, the angular offset between the images formed by the two sets of coordinates.

[0089] Step S232: Based on the angle offset, obtain the CCD prediction coordinates corresponding to each of the CGH design coordinates in the distortion-free space;

[0090] It is easy to understand that, in this embodiment, the CCD coordinates under ideal conditions, i.e., the CCD predicted coordinates, can be recalculated and determined in a distortion-free space based on the design coordinates of each CGH using the aforementioned angular offset.

[0091] Step S233: Obtain the corresponding set of residuals between each CCD predicted coordinate and each CCD pixel coordinate;

[0092] Step S234: Solve the residuals of each group using the nonlinear least squares method to obtain the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model.

[0093] It should be noted that residuals refer to the difference between observed and predicted values. In this embodiment, CCD pixel coordinates are the observed values ​​on the CCD image, and CCD predicted coordinates are the predicted values ​​on the CCD image. The difference between each CCD pixel coordinate and its corresponding CCD predicted coordinate can be calculated to obtain several sets of residuals.

[0094] It is easy to understand that, in this embodiment, the residuals of each group can be fitted and solved by nonlinear least squares method, thereby obtaining the unknown distortion coefficients in the initial distortion model.

[0095] It is worth noting that, in this embodiment, the unknown distortion coefficients in the initial distortion model may include radial distortion coefficients and tangential distortion coefficients. The radial distortion coefficient refers to the distortion coefficient caused by lens quality, corresponding to the phenomenon that light rays are more curved further away from the lens center than closer to it; while the tangential distortion coefficient refers to the distortion coefficient caused by the lens itself not being parallel to the imaging plane of the CCD camera. Therefore, the distortion model proposed in this embodiment can also be understood as a tangential distortion model that includes the corresponding radial distortion model and the corresponding tangential distortion coefficients. The expression for the radial distortion model is as follows:

[0096] ;

[0097] ;

[0098] ;

[0099] in, and Let represent the coordinates before and after distortion, respectively. and It can be understood as a coefficient used to characterize the state before and after distortion; With the center coordinates, Radial distance, as well as These are the radial distortion coefficients in two mutually perpendicular directions.

[0100] Correspondingly, the expression for the tangential distortion model is as follows:

[0101] ;

[0102] ;

[0103] ;

[0104] in, and Let represent the coordinates before and after distortion, respectively. and It can be understood as a coefficient used to characterize the state before and after distortion; With the center coordinates, Radial distance, as well as These are the tangential distortion coefficients in two mutually perpendicular directions.

[0105] Based on the first and / or second embodiments of this application, in the third embodiment of this application, the content that is the same as or similar to that in embodiments one and two above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 The step of obtaining the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model by solving the residuals of each group using the nonlinear least squares method includes:

[0106] Step S2341: Obtain the corresponding design matrix and transpose matrix using the coordinates of each CCD pixel and its corresponding radial distance;

[0107] Step S2342: Based on the design matrix, the transpose matrix, and the observation vectors corresponding to each group of residuals, solve the first equation of the nonlinear least squares method to obtain the radial distortion coefficient and the tangential distortion coefficient.

[0108] It should be understood that, in this embodiment, the design matrix refers to the coefficient matrix calculated from the radial distances between each CCD pixel coordinate observed and its center coordinate; the transpose matrix refers to the coefficient matrix obtained by transposing the design matrix; adjacent observations are vectors composed of multiple sets of residuals; and the first equation of the nonlinear least squares method refers to the normal equation corresponding to the nonlinear least squares method.

[0109] It is easy to understand that, in this embodiment, as a method, the corresponding design matrix and transpose matrix can be obtained by the coordinates of each CCD pixel and their corresponding radial distances, and the observation vector composed of each set of residuals can be obtained at the same time. Then, the design matrix, transpose matrix and observation values ​​are substituted into the first equation of the nonlinear least squares method for solving, and the radial distortion coefficient and tangential distortion coefficient of the distortion model can be obtained respectively.

[0110] Furthermore, in this embodiment, the step of obtaining the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model by solving the residuals of each group using the nonlinear least squares method includes:

[0111] Step S2343: Obtain the corresponding design matrix through the coordinates of each CCD pixel and its corresponding radial distance, and obtain the corresponding observation vector through each group of residuals;

[0112] Step S2344: Perform singular value decomposition on the design matrix to obtain the second equation of the nonlinear least squares method;

[0113] Step S2345: Based on the observed value vector, solve the second equation to obtain the radial distortion coefficient and the tangential distortion coefficient.

[0114] It should be understood that, in this embodiment, the second equation of the nonlinear least squares method refers to the stable solution equation constructed from the decomposition results obtained by performing singular value decomposition on the design matrix.

[0115] It is easy to understand that, in this embodiment, as another approach, the design matrix can be obtained by matching the coordinates of each CCD pixel with its corresponding radial distances, and the observation vector composed of each set of residuals can also be obtained. Subsequently, singular value decomposition is performed on the design matrix to obtain the singular value decomposition results, and a second equation for the nonlinear least squares method is constructed. Finally, the adjacent observations are substituted into the second equation of the nonlinear least squares method for solving, which also yields the radial distortion coefficients and tangential distortion coefficients of the distortion model.

[0116] Furthermore, in this embodiment, before the step of correcting the imaging distortion of the interference image based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface to obtain aspherical surface shape data, the method further includes:

[0117] Step S501: Obtain the preset mapping relationship through the preset ray tracing file.

[0118] It should be noted that the preset ray tracing file refers to a file generated during the CGH design process that characterizes the mapping relationship between the coordinate points on the CGH and the coordinate points on the actual mirror surface. This is achieved by simulating countless rays of light traveling from the light source through the optical system to the detector. In this embodiment, the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface can be determined by reading the data obtained after tracing the transmission of a large number of rays stored in the preset observation tracing file.

[0119] It is worth noting that in this embodiment, a mapping relationship between the CCD image before and after distortion is constructed through a preset distortion model. Combined with the mapping relationship between the CGH image and the actual mirror surface provided by a preset ray tracing file, a mapping relationship among the three is established, optimizing the accuracy and efficiency of distortion correction. Furthermore, by employing the nonlinear least squares method, the relevant data of the aspherical surface shape of the optical element can be obtained more quickly. This method only requires using the original target on the CGH image as the calibration basis, eliminating the need to place and align the target on the actual mirror surface of the optical element, greatly improving the testing efficiency of aspherical surface shapes. Since the target setting on the actual mirror surface is eliminated, there is no contamination of the actual mirror surface, further improving the testing accuracy of aspherical surface shapes, making it suitable for high-precision aspherical optical elements.

[0120] Furthermore, this application also provides an aspherical surface shape detection distortion correction device, please refer to... Figure 7 The aspherical surface shape detection distortion correction device includes:

[0121] The distortion-free data acquisition module 10 is used to acquire the first CCD coordinates of several data points in the distortion-free space;

[0122] Distortion model generation module 20 is used to generate a preset distortion model;

[0123] The distortion data acquisition module 30 is used to substitute each of the first CCD coordinates into a preset distortion model for calculation, and obtain the corresponding second CCD coordinates in the distortion space.

[0124] The data geometry correction module 40 is used to fill each of the second CCD coordinates onto the corresponding data points in the distortion-free space to obtain the geometrically corrected interference image.

[0125] The mirror data output module 50 corrects the imaging distortion of the interference image based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface, and obtains aspherical surface shape data.

[0126] The aspherical surface shape detection distortion correction device provided in this application, employing the aspherical surface shape detection distortion correction method described in the above embodiments, can solve the technical problem of how to quickly and accurately detect the surface shape of aspherical optical elements. Compared with the prior art, the beneficial effects of the aspherical surface shape detection distortion correction device provided in this application are the same as those of the aspherical surface shape detection distortion correction method described in the above embodiments, and other technical features in the aspherical surface shape detection distortion correction device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0127] This application provides an aspherical surface shape detection distortion correction device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the aspherical surface shape detection distortion correction method in the above embodiment 1.

[0128] The following is for reference. Figure 8 The diagram illustrates a structural schematic suitable for implementing an aspherical surface shape detection and distortion correction device according to embodiments of this application. The aspherical surface shape detection and distortion correction device in embodiments of this application may include, but is not limited to, fixed terminals such as vehicle-mounted terminals. Figure 8 The aspherical surface shape detection distortion correction device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0129] like Figure 8 As shown, the aspherical surface shape detection distortion correction device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the aspherical surface shape detection distortion correction device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the aspherical surface distortion correction device to communicate wirelessly or wiredly with other devices to exchange data. Although aspherical surface distortion correction devices with various systems are shown in the figures, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0130] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0131] The aspherical surface shape detection distortion correction device provided in this application, employing the aspherical surface shape detection distortion correction method described in the above embodiments, can solve the technical problem of how to quickly and accurately perform surface shape detection on aspherical optical elements. Compared with the prior art, the beneficial effects of the aspherical surface shape detection distortion correction device provided in this application are the same as those of the aspherical surface shape detection distortion correction method provided in the above embodiments, and other technical features in this aspherical surface shape detection distortion correction device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0132] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0133] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0134] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the aspherical surface shape detection distortion correction method in the above embodiments.

[0135] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0136] The aforementioned computer-readable storage medium may be included in the aspherical surface shape detection and distortion correction device; or it may exist independently and not assembled into the aspherical surface shape detection and distortion correction device.

[0137] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the aspherical surface shape detection and distortion correction device, the aspherical surface shape detection and distortion correction device: acquires the coordinates of each first CCD for several data points in a distortion-free space; substitutes each first CCD coordinate into a preset distortion model for calculation to acquire the corresponding second CCD coordinates in the distortion space; fills each second CCD coordinate into the corresponding data points in the distortion-free space to acquire a geometrically corrected interference image; and corrects the imaging distortion of the interference image based on a preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface to obtain aspherical surface shape data.

[0138] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0139] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. 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 indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated 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 the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0140] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0141] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described aspherical surface shape detection distortion correction method, thereby solving the technical problem of how to quickly and accurately perform surface shape detection on aspherical optical elements. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the aspherical surface shape detection distortion correction method provided in the above embodiments, and will not be repeated here.

[0142] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for detecting and correcting distortion in aspherical surface shapes, characterized in that, The steps of the aspherical surface shape detection distortion correction method include: Using the CGH design file, obtain the first CCD coordinates of several data points in a distortion-free space; Substitute each of the first CCD coordinates into a preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space. Each of the second CCD coordinates is filled into the corresponding data points in the distortion-free space to obtain the geometrically corrected interference image. Based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface of the optical element under test, the imaging distortion of the interference image is corrected to obtain aspherical surface shape data.

2. The aspherical surface shape detection distortion correction method as described in claim 1, characterized in that, Before the step of substituting each of the first CCD coordinates into a preset distortion model for calculation to obtain the corresponding second CCD coordinates in the distortion space, the method further includes: Several targets are set up in the alignment area of ​​the CGH; Obtain the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target. Based on the design coordinates of each CGH and the pixel coordinates of each CCD, the distortion coefficients of the initial distortion model are solved. Substitute the distortion coefficients into the initial distortion model to obtain the preset distortion model.

3. The aspherical surface shape detection distortion correction method as described in claim 2, characterized in that, The steps of obtaining the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target include: Determine the target shape for each of the aforementioned targets; When the target shape is a polygon, the vertices of each polygon are used as corresponding calibration points, and the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point are obtained. Alternatively, when the target shape is circular, the center of each circle is taken as the corresponding calibration point, and the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point are obtained.

4. The aspherical surface shape detection distortion correction method as described in claim 2, characterized in that, The steps of obtaining the CGH design coordinates corresponding to the calibration points of each target and the CCD pixel coordinates corresponding to the calibration points of each target include: Determine the target shape for each of the aforementioned targets; When the target shape is a marker pattern with multiple non-collinear feature points, each feature point of the marker pattern is used as a corresponding calibration point, and the CGH design coordinates and CCD pixel coordinates corresponding to each calibration point are obtained.

5. The aspherical surface shape detection distortion correction method as described in claim 2, characterized in that, The distortion coefficients include radial distortion coefficients and tangential distortion coefficients. The step of solving the distortion coefficients of the initial distortion model based on the design coordinates of each CGH and the pixel coordinates of each CCD includes: Calculate the angular offset between the CGH design coordinates and the CCD pixel coordinates; Based on the angle offset, obtain the CCD prediction coordinates corresponding to each of the CGH design coordinates in the distortion-free space; Obtain the corresponding sets of residuals between the predicted coordinates of each CCD and the pixel coordinates of each CCD; The radial distortion coefficient and the tangential distortion coefficient of the initial distortion model are obtained by solving the residuals of each group using the nonlinear least squares method.

6. The aspherical surface shape detection distortion correction method as described in claim 5, characterized in that, The step of obtaining the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model by solving the residuals of each group using the nonlinear least squares method includes: The design matrix and transpose matrix are obtained by using the coordinates of each CCD pixel and its corresponding radial distance. Based on the design matrix, the transpose matrix, and the observation vectors corresponding to each set of residuals, the first equation of the nonlinear least squares method is solved to obtain the radial distortion coefficient and the tangential distortion coefficient.

7. The aspherical surface shape detection distortion correction method as described in claim 5, characterized in that, The step of obtaining the radial distortion coefficient and the tangential distortion coefficient of the initial distortion model by solving the residuals of each group using the nonlinear least squares method includes: The design matrix is ​​obtained by using the coordinates of each CCD pixel and its corresponding radial distance, and the observation vector is obtained by using each set of residuals. Singular value decomposition is performed on the design matrix to obtain the second equation of the nonlinear least squares method; Based on the observed value vector, the second equation is solved to obtain the radial distortion coefficient and the tangential distortion coefficient.

8. The aspherical surface shape detection distortion correction method as described in claim 1, characterized in that, Before the step of correcting the imaging distortion of the interference image and obtaining aspherical surface shape data based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface of the optical element under test, the method further includes: The preset mapping relationship is obtained by using a preset ray tracing file.

9. A non-spherical surface shape detection distortion correction device, characterized in that, The aspherical surface shape detection and distortion correction device includes: The distortion-free data acquisition module is used to acquire the first CCD coordinates of several data points in the distortion-free space using the CGH design file; The distortion data acquisition module is used to substitute each of the first CCD coordinates into a preset distortion model for calculation, and obtain the corresponding second CCD coordinates in the distortion space. The data geometric correction module is used to fill each of the second CCD coordinates onto the corresponding data points in the distortion-free space to obtain the geometrically corrected interference image. The mirror data output module corrects the imaging distortion of the interference image based on the preset mapping relationship between the CGH coordinates on the CGH and the mirror coordinates on the actual mirror surface of the optical element under test, and obtains aspherical surface shape data.

10. A non-spherical surface shape detection distortion correction device, characterized in that, The aspherical surface shape detection distortion correction device includes: a memory, a processor, and an aspherical surface shape detection distortion correction program stored in the memory and executable on the processor, wherein the aspherical surface shape detection distortion correction program is configured to implement the steps of the aspherical surface shape detection distortion correction method as described in any one of claims 1 to 8.

11. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and the computer-readable storage medium stores an aspherical surface shape detection distortion correction program. When the aspherical surface shape detection distortion correction program is executed by a processor, it implements the steps of the aspherical surface shape detection distortion correction method as described in any one of claims 1 to 8.

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