Personalized wavefront compensation method based on wearing geometric optical path
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 南通诺瞳奕目医疗科技有限公司
- Filing Date
- 2026-04-02
- Publication Date
- 2026-06-02
Smart Images
Figure CN122131510A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of optical lens design and manufacturing technology, specifically a personalized wavefront compensation method, system, computer device, and storage medium based on the wearing geometry optical path. Background Technology
[0002] With the development of optometry technology, personalized lens design methods based on wavefront aberration theory have gradually become a research hotspot. These methods measure the wavefront aberration of the human eye and design lens shapes that can compensate for this aberration, aiming to achieve better visual correction. Current personalized lens designs are typically based on standardized wearing posture assumptions for optical modeling, meaning that the design process assumes the lens is in an ideal position relative to the human eye, without fully considering the geometric deviations that occur when the frame is actually worn.
[0003] However, in actual wear, due to individual differences in frame type, wearing habits, and facial anatomy, lenses exhibit variations in various geometric parameters such as vertex distance, tilt angle, wrap angle, and pupillary distance. The combined effect of these wearing geometric parameters leads to a complex distortion phase distribution of the actual wavefront entering the eye relative to the designed wavefront, resulting in a significant deviation between the lens's optical performance and the expected outcome of the prescription. This problem is particularly prominent in the design of planar microstructure lenses, because planar substrates cannot compensate for the changes in the optical path introduced by wearing geometric parameters through surface shape adjustments, as is possible with traditional curved lenses. This makes it difficult for existing design methods to achieve precise wavefront compensation matching the wearer's actual wearing condition on a two-dimensional plane. Summary of the Invention
[0004] Therefore, it is necessary to provide a personalized wavefront compensation method, system, computer device, and storage medium based on the wearing geometry optical path that can accurately match the actual wearing state to address the above-mentioned technical problems.
[0005] Firstly, a personalized wavefront compensation method based on the wearing geometric optical path is provided, the method comprising: The prescription parameters of the wearer's eyeball, the geometric parameters of the frame in the wearing state, and the individualized physiological parameters of the wearer's eyeball are obtained. The geometric parameters include vertex distance, anterior tilt angle, wrap angle, and pupillary distance deviation. The individualized physiological parameters include corneal anterior surface morphology data. Using the center of eye rotation as the origin of the coordinate system, a vector tracing model is constructed by combining the corneal anterior surface topography data. The vector tracing model includes the dynamic trajectory of the corneal vertex and the posterior surface of the lens. The geometric parameters are input into the vector tracing model for ray tracing to calculate the distortion phase distribution. The distortion phase distribution is caused by the combined effects of vertex distance, forward tilt angle, wrap angle and pupil distance deviation, and characterizes the deviation of the actual wavefront from the design wavefront. A personalized wavefront compensation term is generated based on the aforementioned distorted phase distribution; The personalized wavefront compensation term is fused with the basic phase field corresponding to the prescription parameters to obtain the fused phase field. The fused phase field is subjected to a conformal mapping transformation to map the fused phase field from a three-dimensional curved surface coordinate system to a two-dimensional planar coordinate system, resulting in a planarized customized phase distribution. The conformal mapping transformation is performed according to a predetermined conformal mapping relationship, which is determined by the planar geometric constraints of the lens substrate and the mapping function from the three-dimensional curved surface to the two-dimensional plane. Height field data is generated based on the planarized customized phase distribution, and the height field data is used to drive grayscale lithography or nanoimprint lithography processes.
[0006] In one embodiment, the conformal mapping transformation includes: Construct the three-dimensional surface parametric equations for the rear surface of the lens; Establish a mapping relationship between the parameters of the three-dimensional surface and the two-dimensional plane coordinates, wherein the mapping relationship is a conformal mapping that satisfies the Laplace equation; Based on the mapping relationship, the sampling points of the fused phase field on the three-dimensional curved surface are mapped to the corresponding points on the two-dimensional plane to obtain the planarized customized phase distribution.
[0007] In one embodiment, generating height field data based on the planarized customized phase distribution includes: Based on the material's refractive index and the design wavelength, the planarized customized phase distribution is converted into a continuous height field; The continuous height field is subjected to multi-order quantization to obtain a discretized height field; The boundary continuity of the discretized height field is checked to determine whether the height difference between adjacent microstructure units exceeds a preset gradient threshold. If the gradient threshold is exceeded, the discretized height field is locally smoothed until the height difference does not exceed the gradient threshold, thus obtaining the verified height field data.
[0008] In one embodiment, prior to generating the height field data, the method further includes: A two-dimensional Fourier transform is performed on the planarized customized phase distribution obtained based on the fused phase field to obtain the spatial spectrum; Based on the preset minimum linewidth constraint, the spatial spectrum is low-pass filtered to remove high-frequency components that exceed the manufacturing process limits. A two-dimensional inverse Fourier transform is performed on the filtered spectrum to obtain a manufacturability-optimized planar phase distribution, which is then used as a planarized customized phase distribution for generating the height field data.
[0009] In one embodiment, the individualized ocular physiological parameters further include intraocular media refractive index distribution data, which includes corneal refractive index, aqueous humor refractive index, lens equivalent refractive index, and vitreous refractive index. When calculating the distortion phase distribution, the vector tracing model uses the refractive index distribution data of the intraocular medium as the refractive index field constraint for light transmission between the cornea and retina, and calculates the actual optical path length based on the refractive index field constraint.
[0010] In one embodiment, the corneal anterior surface topography data includes the corneal vertex radius of curvature, the corneal aspheric coefficient, and the asymmetry parameters of the corneal anterior surface in the horizontal and vertical directions.
[0011] In one embodiment, the equivalent refractive index of the lens is determined by the combined curvature radius of the anterior surface of the lens, the curvature radius of the posterior surface of the lens, and the thickness at the center of the lens.
[0012] In one embodiment, generating a personalized wavefront compensation term based on the distorted phase distribution includes: The Zernike polynomial was used to fit the distortion phase distribution, and the coefficients of each order corresponding to defocus, astigmatism, coma and spherical aberration were extracted. Based on the extracted coefficients of each order, the sum of the products of the Zernik coefficients and the corresponding Zernik polynomials is calculated, and the negative of the sum is used as the personalized wavefront compensation term.
[0013] In one embodiment, fusing the personalized wavefront compensation term with the baseline phase field corresponding to the prescription parameters to obtain a fused phase field includes: The net phase distribution is obtained by vector superposition of the basic phase field and the personalized wavefront compensation term in the complex amplitude space. The net phase distribution is subjected to phase reset processing to compress its value range to a single phase period, and then the fused phase field is obtained.
[0014] Secondly, a personalized wavefront compensation system based on a wearable geometric optical path is provided, the system comprising: The parameter acquisition module is used to acquire the prescription parameters of the wearer's eyeball, the geometric parameters of the frame in the wearing state, and the wearer's individualized ocular physiological parameters. The geometric parameters include vertex distance, anterior tilt angle, wrap angle, and pupillary distance deviation. The individualized ocular physiological parameters include corneal anterior surface morphology data. The model building module is used to construct a vector tracing model with the eyeball rotation center as the coordinate origin and the corneal anterior surface topography data. The vector tracing model includes the dynamic trajectory of the corneal vertex and the posterior surface of the lens. The ray tracing calculation module is used to input the geometric parameters into the vector tracing model to perform ray tracing and calculate the distortion phase distribution. The distortion phase distribution is caused by the combined effects of vertex distance, forward tilt angle, wrap angle and pupil distance deviation, and characterizes the deviation of the actual wavefront from the design wavefront. The compensation term generation module is used to generate a personalized wavefront compensation term based on the distortion phase distribution. The fusion processing module is used to fuse the personalized wavefront compensation term with the basic phase field corresponding to the prescription parameters to obtain a fused phase field. The conformal mapping module is used to perform conformal mapping transformation on the fused phase field, mapping the fused phase field from a three-dimensional curved surface coordinate system to a two-dimensional planar coordinate system to obtain a planarized customized phase distribution. The conformal mapping transformation is performed according to a predetermined conformal mapping relationship, which is determined by the planar geometric constraints of the lens substrate and the mapping function from the three-dimensional curved surface to the two-dimensional plane. A height field generation module is used to generate height field data based on the planarized customized phase distribution, and the height field data is used to drive grayscale lithography or nanoimprint lithography processes.
[0015] Thirdly, a computer device is provided, including a memory and a processor, the memory being communicatively connected to the processor, and the memory storing a computer program executable on the processor, wherein the processor, when executing the computer program, implements the personalized wavefront compensation method based on the wearable geometric optical path as described above.
[0016] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the personalized wavefront compensation method based on the wearable geometric optical path as described above.
[0017] The aforementioned personalized wavefront compensation method, system, computer equipment, and storage medium based on wearing geometry optical path acquire the wearer's prescription parameters, wearing geometry parameters, and individualized ocular physiological parameters. It constructs a vector tracing model with the eye's rotation center as the origin for ray tracing, accurately quantifying the coupling effect of wearing geometry parameters on the wavefront. Based on this, it generates a personalized wavefront compensation term and fuses it with the basic phase field. Then, through conformal mapping transformation, it maps the fused phase field on the three-dimensional surface to a two-dimensional plane, ultimately generating height field data to drive micro / nano manufacturing processes. By incorporating wearing geometry parameters as key inputs into the compensation mechanism, it achieves targeted correction of the distorted phase caused by the combined effects of vertex distance, tilt angle, wrap angle, and pupillary distance deviations. This solves the technical challenge of reproducing precise optical functions under three-dimensional wearing conditions on planar substrates, ensuring that the manufactured planar microstructure lenses achieve wavefront compensation effects consistent with the design goals during actual wear. Attached Figure Description
[0018] Figure 1 This is an application environment diagram of a personalized wavefront compensation method based on the wearing geometric optical path in one embodiment; Figure 2 This is a flowchart illustrating a personalized wavefront compensation method based on the wearable geometric optical path in one embodiment. Figure 3 This is a structural block diagram of a personalized wavefront compensation system based on a wearable geometric optical path in one embodiment; Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation
[0019] To facilitate understanding of the technical solutions provided in the embodiments of this application, the background technology involved in the embodiments of this application will be described below.
[0020] In the field of optometry, personalized lens design is typically based on standardized wearing posture assumptions through optical modeling. This method first measures the aberration characteristics of the human eye's refractive system using equipment such as a wavefront aberrometer. Then, in the design software, the lens is positioned ideally relative to the eye, assuming the lens optical axis coincides with the eye's visual axis, the lens plane is perpendicular to the visual axis, and the posterior vertex of the lens maintains a standard distance from the corneal vertex. Based on this idealized model, designers compensate for the measured wavefront aberrations by optimizing the lens shape to achieve the desired corrective effect.
[0021] However, there are significant differences between lenses in actual wear and the ideal design model. Due to individual differences in frame type, wearing habits, and the wearer's facial anatomy, lenses will exhibit various geometric deviations relative to the human eye. Specifically, the actual distance (apex distance) between the posterior vertex of the lens and the apex of the cornea along the optical axis differs from the design standard value; there is an angle between the lens plane and the vertical plane (forward tilt angle); there is an angle between the lens plane and the sagittal plane (enclosure angle); and there is also a horizontal deviation between the optical centers of the left and right lenses and the pupil center (interpupillary distance deviation). These variations in wearing geometry parameters do not exist in isolation but collectively affect the light transmission path behind the lens, resulting in a complex distorted phase distribution of the wavefront actually entering the human eye relative to the designed wavefront.
[0022] This problem is particularly prominent in the design of planar microstructure lenses. Unlike traditional curved lenses, which can compensate for some wearing deviations by adjusting the base curve or surface shape, the optical function of planar microstructure lenses depends entirely on the precise arrangement of micro- and nanostructures on a two-dimensional plane. Their phase modulation capability is more sensitive to changes in the incident angle and position of light. Current design methods have not yet established an optical model that uses vertex distance, tilt angle, wrap angle, and pupillary distance deviation as key input variables. This makes it difficult to accurately compensate for the phase distortion caused by the combined effect of these wearing geometric parameters on a two-dimensional plane. Consequently, the manufactured lenses cannot achieve the optical performance expected by the optometry prescription under actual wearing conditions.
[0023] Therefore, this embodiment provides a personalized wavefront compensation method, system, computer device, and storage medium based on the wearing geometric optical path.
[0024] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0025] The personalized wavefront compensation method based on the optical geometry of the wearable lens provided in this application can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. Specifically, terminal 102 acquires the wearer's prescription parameters, the geometric parameters of the frame in the wearing state, and the wearer's individualized ocular physiological parameters, and sends these parameters to server 104 via the network. After receiving the parameters, server 104 constructs a vector tracing model using the eye's rotation center as the origin and combining it with corneal anterior surface morphology data. The geometric parameters are input into the vector tracing model to perform ray tracing calculations to obtain the distortion phase distribution. A personalized wavefront compensation term is generated based on the distortion phase distribution. The personalized wavefront compensation term is fused with the basic phase field to obtain a fused phase field. The fused phase field is then subjected to conformal mapping transformation to obtain a planarized customized phase distribution. Finally, height field data for driving grayscale lithography or nanoimprint lithography processes is generated based on the planarized customized phase distribution, and the generated height field data is returned to terminal 102 for output or storage. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, optometry equipment or portable wearable devices, and the server 104 can be implemented by a standalone server or a server cluster composed of multiple servers.
[0026] Firstly, to address the technical problem of discrepancies between the actual and designed wavefronts of lenses caused by neglecting frame wearing geometry parameters (vertex distance, tilt angle, wrap angle, and pupillary distance deviation), one embodiment provides a personalized wavefront compensation method based on the wearing geometry optical path. This method is applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps: Step S1: Obtain the prescription parameters of the wearer's eyeball, the geometric parameters of the frame in the wearing state, and the wearer's individualized ocular physiological parameters. The geometric parameters include vertex distance, anterior tilt angle, wrap angle, and pupillary distance deviation. The individualized ocular physiological parameters include corneal anterior surface morphology data.
[0027] In this step, the prescription parameters are the spherical power, cylindrical power, and axis data routinely obtained during ophthalmic refraction. Vertex distance is the distance between the posterior surface vertex of the lens and the corneal vertex along the optical axis, which can be measured using a corneal topography instrument or anterior OCT device. Anterior tilt angle is the angle between the lens plane and the vertical plane; envelope angle is the angle between the lens plane and the sagittal plane; and pupillary distance deviation is the horizontal deviation between the optical centers of the left and right lenses and the pupillary center. These angles and deviations can be measured using a 3D facial scanner or wearable eye-tracking device in the wearer's natural wearing state. Anterior corneal surface topography data can be measured using a corneal topography instrument, and its specific form can be a set of discrete point cloud data or a high-order aspherical function expression. It should be noted that all parameters should be acquired with the wearer's informed consent to ensure that data collection and use comply with relevant laws, regulations, and privacy policies.
[0028] Step S2: Using the center of eye rotation as the origin of the coordinate system, construct a vector tracing model by combining the anterior surface topography data of the cornea. The vector tracing model includes the dynamic trajectory of the corneal vertex and the posterior surface of the lens.
[0029] In this step, the eye rotation center is determined by measuring the wearer's eye position at different visual angles using an eye tracker and then determining it through geometric fitting. The dynamic trajectory of the corneal apex characterizes the positional change of the corneal apex in three-dimensional space during eye rotation. This trajectory can be calculated using rigid body kinematics based on the coordinates of the eye rotation center and the anterior corneal surface topography data. The posterior surface of the lens is constructed as a three-dimensional curved surface according to the lens design parameters. The core of this vector tracing model is to vectorize and parameterize the entire light path from an external object, through lens refraction, and then through the anterior corneal surface into the eye.
[0030] Step S3: Input the geometric parameters into the vector tracing model to perform ray tracing and calculate the distortion phase distribution. The distortion phase distribution is caused by the combined effects of vertex distance, forward tilt angle, wrap angle and pupil distance deviation, and represents the deviation of the actual wavefront from the design wavefront.
[0031] In this step, the vector tracing model adjusts the position and orientation of the lens's posterior surface relative to the eyeball based on these geometric parameters, and then tracks the light rays covering the entire pupillary area. During tracing, the complete path of each ray is calculated, starting from the object side, refracted by the lens's posterior surface, propagating through the air to the corneal apex, and then refracted by the corneal anterior surface into the eye. By comparing the actual optical path length under the current wearing geometry with the theoretical optical path length under the design reference pose (usually the standard vertex distance, 0 degrees of tilt angle, 0 degrees of envelope angle, and 0 mm pupillary distance deviation), the difference is converted into an optical path difference, thus obtaining the distortion phase distribution caused by the combined effects of vertex distance, tilt angle, envelope angle, and pupillary distance deviation.
[0032] Step S4: Generate a personalized wavefront compensation term based on the distorted phase distribution.
[0033] In this step, the purpose of generating a personalized wavefront compensation term is to counteract the aforementioned impact of phase distortion on image quality.
[0034] Step S5: The personalized wavefront compensation term is fused with the basic phase field corresponding to the prescription parameters to obtain the fused phase field.
[0035] In this step, the base phase field is an ideal phase distribution designed based on the prescription parameters (spherical, cylindrical, and axial), representing the standard refractive power that the lens should provide. Fusion processing adds compensation terms to the base phase field, ensuring that the final phase field meets both the prescription requirements and compensates for wavefront distortion caused by the wearing geometry.
[0036] Step S6: Perform conformal mapping transformation on the fused phase field to map the fused phase field from the three-dimensional curved surface coordinate system to the two-dimensional plane coordinate system to obtain a planarized customized phase distribution. The conformal mapping transformation is performed according to the predetermined conformal mapping relationship, which is determined by the planar geometric constraints of the lens substrate and the mapping function from the three-dimensional curved surface to the two-dimensional plane.
[0037] In this step, since the lens will ultimately be manufactured on a completely flat substrate, and the previously calculated fusion phase field is defined in a three-dimensional curved coordinate system (i.e., the back surface of the lens), a conformal mapping transformation of the fusion phase field is required. The core of conformal mapping is to keep the local angles unchanged before and after the mapping, thereby maximizing the fidelity of optical functions. In practical applications, a numerical solution based on the Cauchy-Riemann equations can be used to solve this mapping relationship.
[0038] Step S7: Generate height field data based on the planarized customized phase distribution. The height field data is used to drive grayscale lithography or nanoimprint lithography processes.
[0039] In this step, the generated height field data becomes the physical surface morphology data that can ultimately be used to manufacture planar microstructure lenses. This height field data is a key document for driving subsequent manufacturing processes (grayscale lithography or nanoimprint lithography), and can be directly used to control the exposure dose distribution of the grayscale lithography machine or the mold manufacturing of the nanoimprint lithography equipment.
[0040] Based on the above, this method incorporates wearing geometry parameters as key inputs into the compensation mechanism, accurately quantifies and compensates for the coupling effects of vertex distance, tilt angle, wrap angle and pupil distance deviation on the wavefront, solves the technical problem of it being difficult to reproduce the precise optical function under three-dimensional wearing conditions on planar substrates, and ensures that the manufactured planar microstructure lens can achieve the wavefront compensation effect consistent with the design goal when actually worn.
[0041] To ensure that phase information on a three-dimensional surface can be accurately transferred to a two-dimensional plane, in one embodiment, the conformal mapping transformation includes: Step S61: Construct the three-dimensional surface parametric equations for the rear surface of the lens.
[0042] In this step, the parametric equation is typically represented as a bivariate vector function, where the parameter domain coordinates are defined in a two-dimensional parameter domain. For example, for a rotationally symmetric aspherical lens, the parameters can represent radial distance and angle; for a freeform surface lens, the parameters can be normalized rectangular parameter domain coordinates. This parametric equation can be directly constructed based on the lens's design parameters (such as radius of curvature, aspheric coefficient, higher-order term coefficients, etc.).
[0043] Step S62: Establish the mapping relationship between the parameters of the three-dimensional surface and the coordinates of the two-dimensional plane. The mapping relationship is a conformal mapping that satisfies the Laplace equation.
[0044] In this step, the mathematical essence of conformal mapping is to find a pair of harmonic functions that satisfy the Laplace equation and the Cauchy-Riemann equation. In practical solutions, boundary conditions are usually required, such as mapping the boundary of a three-dimensional surface to a specific polygon (such as a rectangle or circle) on a two-dimensional plane. This mapping relationship can be solved using various numerical methods, such as a Laplace equation solver based on the finite element method, or a mesh parameterization algorithm from computational geometry. Specific algorithm implementations can utilize existing open-source libraries or mathematical modules in commercial software; this application does not limit this, as long as a conformal mapping relationship can be obtained.
[0045] Step S63: Based on the mapping relationship, the sampling points of the fused phase field on the three-dimensional curved surface are mapped to the corresponding points on the two-dimensional plane to obtain the planarized customized phase distribution.
[0046] In this step, for each grid point on the two-dimensional plane, its corresponding point on the three-dimensional surface parameter domain is found through the established mapping relationship, and then the phase value of that point is assigned to the two-dimensional plane grid point. By assigning values to all grid points, a complete planarized customized phase distribution can be obtained. If the mapping is not a one-to-one correspondence or there are missing sampling points, it can be supplemented by interpolation methods (such as bilinear interpolation or spline interpolation).
[0047] Based on the above, the phase field defined on a complex three-dimensional curved surface was accurately and conformally transferred to a two-dimensional plane, providing an accurate optical design basis for the subsequent fabrication of microstructures on planar substrates, thereby ensuring the optical performance of the final lens.
[0048] To transform pure phase design into physical surface morphologies suitable for micro / nano fabrication and optimize the fabrication adaptability of the morphology, in one embodiment, height field data is generated based on a planarized customized phase distribution, including: Step S71: Based on the material refractive index and the design wavelength, convert the planar customized phase distribution into a continuous height field.
[0049] In this step, the conversion is based on the fundamental principle of diffractive optics: for a transmission-type pure phase element, its local thickness variation is proportional to the introduced phase delay. Specifically, for a given design wavelength and material refractive index, the conversion relationship between the phase distribution and the surface physical height can be calculated using industry-standard formulas. Through this conversion, the phase distribution is linearly mapped to a surface profile with continuously varying height.
[0050] Step S72: Perform multi-order quantization on the continuous height field to obtain a discretized height field.
[0051] In this step, since manufacturing processes such as grayscale lithography or nanoimprint lithography can typically only handle discrete height levels, rather than infinitely continuous simulated heights, multi-order quantization of the continuous height field is required. The purpose of quantization is to approximate the continuous surface profile with a finite number of step heights. For example, when performing N-order quantization, the global maximum and minimum values of the continuous height field are first determined. Then, the entire height range is uniformly divided into N intervals, each interval corresponding to a quantized height value, usually the center value of that interval. For each coordinate point, its original continuous height value is replaced with the quantized height value corresponding to its interval, thus obtaining the discretized height field. The value of N can be an integer power of 2, such as 4, 8, 16, 32, etc., and the specific order depends on the process accuracy requirements and design complexity.
[0052] Step S73: Perform boundary continuity verification on the discretized height field to determine whether the height difference between adjacent microstructure units exceeds the preset gradient threshold.
[0053] In this step, boundary continuity verification is to ensure that the transition regions between microstructural units do not exhibit excessively steep gradients, thereby preventing defects in subsequent replication processes (such as imprinting). The verification method can be to traverse each grid point in a two-dimensional plane coordinate system and calculate the absolute values of the height differences between it and its adjacent points in the horizontal and vertical directions. The preset gradient threshold can be determined based on the limiting slope of the manufacturing process or the material flow characteristics.
[0054] Step S74: If the gradient threshold is exceeded, the discretized height field is locally smoothed until the height difference does not exceed the gradient threshold, and the verified height field data is obtained.
[0055] In this step, if a height difference exceeds a threshold, the region is deemed to fail to meet the boundary continuity requirement. In this case, local smoothing is performed on the affected region and its neighborhood. Various digital image processing techniques can be employed for smoothing, such as applying Gaussian filtering, mean filtering, or median filtering to regions exceeding the threshold to reduce local gradients. After smoothing, the affected region needs to be verified again, and the verification-smoothing iterative process is repeated until the height difference between all adjacent microstructure units in the entire discretized height field does not exceed the preset gradient threshold. The final height field data obtained through this step is the manufacturable data that meets both optical design requirements and manufacturing process continuity.
[0056] Based on the above, the abstract phase design was transformed into a concrete, manufacturable physical height field, and its process adaptability was optimized through quantization and continuity verification, thereby ensuring the yield and performance of the final product.
[0057] To improve design manufacturability from the outset, this involves pre-filtering out fine structures in a planarized custom phase distribution that are too high-frequency to be resolved by current manufacturing processes before generating height field data. In one embodiment, this pre-filtering process includes: Step S61': Perform a two-dimensional Fourier transform on the planarized customized phase distribution obtained based on the fused phase field to obtain the spatial spectrum.
[0058] This step is performed after obtaining the planarized customized phase distribution based on the fused phase field through conformal mapping transformation, and before generating height field data from this distribution. In this step, a two-dimensional Fourier transform converts the phase distribution in the spatial domain to the spatial frequency domain, obtaining its spatial spectrum. This spectrum reflects the amplitude of different frequency components in the phase distribution. The two-dimensional Fourier transform can be efficiently implemented using the Fast Fourier Transform algorithm, which has mature library functions available in digital signal processing and image processing.
[0059] Step S62': Based on the preset minimum linewidth constraint, perform low-pass filtering on the spatial spectrum to filter out high-frequency components that exceed the manufacturing process limits.
[0060] In this step, the minimum linewidth is the smallest feature size that the manufacturing process can reliably process. For example, for a certain type of grayscale lithography machine, it might be 200 nanometers; for nanoimprint lithography, it might be 50 nanometers. This is a process parameter determined by the specific equipment and process capabilities. Based on the minimum linewidth, the corresponding highest spatial frequency can be calculated. The goal of filtering is to retain all frequency components below this highest spatial frequency while suppressing or completely filtering out frequency components above it. In practical applications, a low-pass filter can be constructed based on actual needs. For example, an ideal cutoff filter can be used, allowing frequency components below the cutoff frequency to pass completely while completely filtering out frequency components above the cutoff frequency. Alternatively, to reduce ringing caused by truncation, filters with a smooth transition band, such as Butterworth filters or Gaussian filters, can be used. Multiplying the original spectrum by the filter point by point yields the filtered spectrum.
[0061] Step S63': Perform a two-dimensional inverse Fourier transform on the filtered spectrum to obtain a manufacturability-optimized planar phase distribution, and use the manufacturability-optimized planar phase distribution as the basis for generating height field data.
[0062] In this step, the two-dimensional inverse Fourier transform converts the filtered spatial spectrum back into the spatial domain, resulting in a manufacturability-optimized planar phase distribution. This optimized distribution, free of ultra-high frequency components, will be used as the basis for subsequent steps in generating height field data. This generated height field data will not contain any fine structures exceeding manufacturing limits, ensuring its successful fabrication using current processes and improving design success rate and product yield.
[0063] Based on the above, the limit constraints of the manufacturing process (minimum linewidth) are embedded into the phase design stage, so that the final generated planar customized phase distribution does not contain any high-frequency fine structures that exceed manufacturing capabilities. This allows the height field data obtained to be adapted to existing process conditions, avoiding the problem of being unable to process due to overly fine design. This improves the manufacturability of the design and the yield of the product, and realizes closed-loop optimization of design for manufacturing.
[0064] To address the issue that considering only the anterior corneal surface morphology cannot fully describe the light transmission path throughout the eye, one embodiment includes, in addition to anterior corneal surface morphology data, data on the refractive index distribution of intraocular media when acquiring individualized ocular physiological parameters. This data provides a detailed description of the refractive indices of each layer of optical media from the posterior corneal surface to the retina. Specifically, the intraocular media refractive index distribution data includes the corneal refractive index, aqueous humor refractive index, lens equivalent refractive index, and vitreous refractive index. These refractive index values are not fixed constants but can be individually obtained using existing ophthalmic measurement equipment. For example, the signal delay of different intraocular tissues can be measured using optical coherence tomography (OCT), and the refractive index of each medium can be calculated by inversion based on the geometric thickness of each tissue. The lens equivalent refractive index can be estimated based on the measured radius of curvature of the anterior and posterior surfaces of the lens and its central thickness, combined with existing eye models or optical simulation software.
[0065] Therefore, when calculating the distortion phase distribution, the vector tracing model uses the refractive index distribution data of the intraocular media as the refractive index field constraint for light propagation between the cornea and retina, and calculates the actual optical path length based on the refractive index field constraint. This means that when performing ray tracing to calculate the distortion phase distribution, the tracing process does not terminate at the corneal apex, but continues to propagate according to the actual layered structure of the intraocular media. The light successively passes through the cornea (thickness and refractive index known), aqueous humor, lens (with equivalent refractive index), and vitreous humor, until it finally reaches the image point on the retina. When calculating the actual optical path length, it is strictly based on the geometric path length of the light propagating in each layer of the medium and its corresponding refractive index, accumulated according to the industry-known optical path calculation formula. For example, the optical path length of the light in the cornea is the product of the corneal refractive index and the corneal thickness, the optical path length in the aqueous humor is the product of the aqueous humor refractive index and the aqueous humor path length, and so on. In this way, the calculated actual optical path length not only includes the influence of lens wearing geometry parameters, but also accurately includes the real optical path of light transmission in the individualized intraocular medium, thus making the final calculated distortion phase distribution closer to the optical condition of the real human eye.
[0066] Based on the above, by utilizing the refractive index distribution data of the intraocular medium, wavefront compensation is extended from the lens-air interface to the entire intraocular visual pathway, making the compensation more targeted and better able to match the differences in intraocular optical characteristics of different individuals, thereby further improving the accuracy of visual correction.
[0067] To provide more accurate corneal geometry input for the vector tracing model, thereby improving the calculation accuracy of the dynamic trajectory of the corneal vertex and the deflection of light rays on the corneal surface, in one embodiment, the anterior corneal surface topography data includes, but is not limited to, the following parameters: corneal vertex radius of curvature, corneal asphericity coefficient, and asymmetry parameters of the anterior corneal surface in the horizontal and vertical directions.
[0068] The corneal vertex curvature radius refers to the curvature radius value in the smallest neighborhood of the geometric center of the cornea, which determines the refractive power of the central corneal region. This parameter can be directly read by a corneal topography instrument.
[0069] The corneal aspheric coefficient describes the morphological changes of the cornea as it transitions from the center to the periphery. A value of 0 indicates a spherical surface, a negative value indicates a long ellipsoid (i.e., steep at the center and flat at the periphery), and a positive value indicates a flattened ellipsoid (i.e., flat at the center and steep at the periphery). Generally, the corneal aspheric coefficient of most normal adults is negative. This coefficient can be obtained by fitting an aspheric equation to measured corneal topography data.
[0070] Asymmetry parameters of the anterior corneal surface in the horizontal and vertical directions are used to describe the non-rotational symmetry of the cornea. The most common corneal asymmetry is regular astigmatism, where the cornea has different curvatures along two mutually perpendicular principal meridians. Relevant parameters can include the directions of the two principal meridians (i.e., the astigmatic axis) and the difference in the radii of curvature (or refractive power) along the two directions. These parameters can be directly extracted from the refractive power distribution map of corneal topography.
[0071] Based on the above, by constructing corneal anterior surface morphology data using the parameters mentioned above, the cornea can be modeled as an aspherical, non-rotationally symmetric optical surface that more closely resembles the actual anatomical structure. When calculating the refraction of light rays on the corneal anterior surface in the vector tracing model, these parameters are used to determine the surface normal vector at each incident point, and then the deflection direction of the light rays is accurately calculated according to Snell's law. This provides an accurate prerequisite for subsequently calculating the precise transmission path of light rays within the eye.
[0072] To clarify how to deduce the optical properties of the lens from measurable geometric parameters, and to incorporate the lens into the vector tracing model as an equivalent homogeneous medium, thereby simplifying the model complexity while maintaining computational accuracy, in one embodiment, the equivalent refractive index of the lens is jointly determined by the radius of curvature of the anterior surface, the radius of curvature of the posterior surface, and the thickness at the center of the lens.
[0073] In other words, the equivalent refractive index of the lens is not a physical quantity that can be directly measured, but rather an equivalent value calculated based on the lens's geometry and material properties. It can be determined using optical modeling and simulation techniques. A feasible method for determining this is as follows: First, obtain the anterior surface radius of curvature, posterior surface radius of curvature, and central thickness of the wearer's lens using ophthalmic measurement equipment (such as OCT or a Scheimpflug imaging system). Then, using a known basic refractive index distribution model of the lens material (e.g., assuming the lens has a gradient refractive index distribution, with its core and cortical refractive indices being known empirical values), build a lens model in optical simulation software that includes precise geometry and gradient refractive index. Next, construct a simplified uniform refractive index lens model whose geometric dimensions are completely consistent with the precise model. Using a ray tracing optimization algorithm, continuously adjust the refractive index value of the uniform model so that the optical power of the uniform model in a specific field of view (e.g., along the optical axis) is equal to that of the precise gradient refractive index model. When the difference in optical power between the two is less than a preset threshold, the refractive index value at this point is the equivalent refractive index of the wearer's lens. This optimization process can be automatically completed using optimization functions in optical design software.
[0074] Based on the above, the equivalent refractive index of the lens in this embodiment is an equivalent parameter that can represent the overall refractive power of the individual lens. In the vector tracing model, the lens is simplified as a uniform medium with this equivalent refractive index, and ray tracing is performed in conjunction with the radius of curvature and thickness of its anterior and posterior surfaces. This allows for a relatively accurate simulation of the effect of light passing through the individualized lens while ensuring computational efficiency.
[0075] To clarify how to generate a personalized wavefront compensation term based on the distortion phase distribution, in one embodiment, generating a personalized wavefront compensation term based on the distortion phase distribution includes: Step S41: Perform Zernike polynomial fitting on the distortion phase distribution and extract the coefficients of each order corresponding to defocus, astigmatism, coma, and spherical aberration.
[0076] In this step, the Zernike polynomials are a set of polynomials orthogonal on the unit circle. Their first few terms have a clear correspondence with Seidel aberrations; for example, some terms represent defocus, some astigmatism, some coma, and some spherical aberration. The fitting process represents the distortion phase distribution as a linear combination of a finite number of Zernike polynomials. The coefficients can be solved using the least squares method, that is, solving the linear equations to minimize the sum of squares of the fitting residuals, thus extracting the coefficients of each order corresponding to defocus, astigmatism, coma, and spherical aberration.
[0077] Step S42: Based on the extracted coefficients of each order, calculate the sum of the products of the Zernik coefficients and the corresponding Zernik polynomials, and use the negative of the sum as the personalized wavefront compensation term.
[0078] In this step, to counteract the aberrations caused by the wearing geometry, the constructed compensation phase should ideally be the opposite of the distortion phase. The compensation term constructed in this way is essentially a wavefront with the same mathematical form but opposite sign as the original distortion phase distribution. When it coexists with the distortion phase (i.e., superimposed on the base phase field), it can accurately cancel out major geometric aberrations such as defocus, astigmatism, coma, and spherical aberration, thus achieving the compensation purpose. Higher-order aberrations or irregularities represented by the fitting residuals can be ignored or smoothed to a certain extent through subsequent fusion and optimization steps.
[0079] Based on the above, the arbitrary distortion phase distribution, which is difficult to process directly, is transformed into a compensation term consisting of a few aberration coefficients with clear physical meaning. This makes the compensation process clearer and more controllable, and also facilitates integration with aberration analysis tools in existing optical design software.
[0080] To merge two phase fields carrying different optical functions into a unified, physically realizable phase distribution, in one embodiment, the personalized wavefront compensation term and the base phase field corresponding to the prescription parameters are fused to obtain a fused phase field, including: Step S51: Vector superposition of the basic phase field and the personalized wavefront compensation term in the complex amplitude space to obtain the net phase distribution.
[0081] In this step, based on the complex amplitude representation of light waves, the superposition of the fundamental phase field and the personalized wavefront compensation term is equivalent to multiplying their complex amplitudes. The resulting net phase distribution can be obtained by directly adding the two phase values. This addition is a mathematical addition, requiring the two phase fields to be added point-by-point at each corresponding coordinate point. This operation assumes that the fundamental phase field and the compensation term are defined on the same coordinate system and grid.
[0082] Step S52: Perform phase reset processing on the net phase distribution to compress its value range to a single phase period, and then obtain the fused phase field.
[0083] In this step, because the phase values have a periodicity of 2π and are usually truncated within the principal value interval of (-π, π] or [0, 2π), directly adding the phases of two arbitrary values will likely result in a value outside this principal value interval. For example, 1.5π + 1.5π = 3π, and 3π is numerically equivalent to π (because subtracting 2π gives π). Phase resetting, also known as the inverse process of phase wrapping or phase unwrapping, maps the phase of any real value back to a single 2π period through modulo operations. The distribution after phase resetting is the final fused phase field. This fused phase field includes both the corrective function of the basic prescription and personalized compensation for the wearing geometry, and its value range is normalized to a phase period, laying the foundation for subsequent conformal mapping transformations and height field generation.
[0084] Based on the above, the basic phase field and the personalized wavefront compensation term are combined by superimposing complex amplitudes. Then, the superimposed phase value is normalized to a single period by phase reset, eliminating the ambiguity of multi-valued values caused by the phase exceeding the main value range. This makes the fused phase field a physically realizable continuous phase distribution, providing accurate and unified input data for subsequent conformal mapping transformation and height field generation, and ensuring the smooth connection of the entire wavefront compensation process.
[0085] It should be understood that, although Figure 2The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.
[0086] Secondly, this embodiment provides a personalized wavefront compensation system based on the wearable geometric optical path, such as... Figure 3 As shown, it includes a parameter acquisition module, a model building module, a tracing calculation module, a compensation term generation module, a fusion processing module, a conformal mapping module, and a height field generation module.
[0087] The parameter acquisition module is used to acquire the wearer's prescription parameters, the geometric parameters of the frame when worn, and the wearer's individualized ocular physiological parameters. Geometric parameters include vertex distance, anterior tilt angle, wrap angle, and pupillary distance deviation; individualized ocular physiological parameters include corneal anterior surface morphology data. This module can include various measurement devices and data interfaces. For example, prescription parameters can be acquired by connecting to a hospital's optometry system or a manual input terminal; geometric parameters can be acquired using a 3D facial scanner (such as a structured light scanner or laser scanner) while the wearer is naturally wearing the frame, or using a wearable eye-tracking device; corneal anterior surface morphology data can be measured using a corneal topography instrument (such as a Placido disc or Scheimpflug imaging corneal topography instrument). These measurement devices are typically equipped with corresponding data acquisition cards and communication interfaces, such as USB 3.0, GigE Vision, or Camera Link interfaces, enabling real-time transmission of raw measurement data to the central processing unit. The parameter acquisition module also includes a data preprocessing unit, which filters, denoises, and standardizes the format of the raw measurement data to ensure that the data received by subsequent modules is accurate and in a uniform format.
[0088] The model building module is used to construct a vector tracing model with the eye's rotation center as the coordinate origin, combined with corneal anterior surface topography data. The vector tracing model includes the dynamic trajectory of the corneal vertices and the posterior surface of the lens. This module typically runs on a high-performance computing workstation or server, and its core is optical modeling software (such as Zemax, Code V, or a custom C++ / Python optical engine). The model building module first fits the coordinates of the eye's rotation center based on data recorded by an eye tracker, then generates a 3D geometric model of the cornea using the anterior corneal topography data, and constructs the 3D curved surface of the posterior surface of the lens in conjunction with the lens's design parameters. This module generates the dynamic trajectory of the corneal vertices at different field of view using mathematical algorithms and integrates all the above geometric elements into a complete ray tracing model. The model building module and the parameter acquisition module are connected via a high-speed data bus (such as PCIe or Ethernet) to ensure rapid transmission of large amounts of point cloud data.
[0089] The ray tracing calculation module is used to input geometric parameters into the vector ray tracing model for ray tracing and calculate the distortion phase distribution. The distortion phase distribution is caused by the combined effects of vertex distance, tilt angle, envelope angle, and pupil distance deviation, and characterizes the deviation of the actual wavefront from the design wavefront. This module typically shares the same computing platform as the model building module, but can also be deployed independently on a dedicated GPU computing cluster to accelerate ray tracing. The ray tracing calculation module receives the vector ray tracing model from the model building module and the geometric parameters from the parameter acquisition module. It simulates the complete path of light rays from the object side through the lens, air gap, and cornea into the eye by calling ray tracing algorithms (such as Monte Carlo ray tracing or deterministic ray tracing). During the calculation, the module dynamically adjusts the spatial pose of the lens according to the geometric parameters and records the optical path of each ray. Finally, it obtains the distortion phase distribution by comparing the actual optical path with the theoretical optical path. The output of this module is a set of high-precision two-dimensional or three-dimensional phase data, usually stored in memory or hard disk in matrix form for subsequent modules to access.
[0090] The compensation term generation module is used to generate personalized wavefront compensation terms based on the distorted phase distribution. This module can use a dedicated digital signal processor or a general-purpose CPU / GPU to run the wavefront reconstruction algorithm. For example, this module can call the Zernike polynomial fitting library to decompose the input distorted phase distribution, extract the aberration coefficients of each order, and then construct the compensation phase factor according to preset rules (such as taking the opposite number). The compensation term generation module needs to have efficient floating-point arithmetic capabilities and be equipped with a large amount of memory to process high-resolution phase data. Data exchange between it and the tracing calculation module can be achieved through shared memory or a high-speed network (such as InfiniBand) to reduce latency.
[0091] The fusion processing module fuses the personalized wavefront compensation term with the base phase field corresponding to the prescription parameters to obtain a fused phase field. The base phase field can be pre-generated by optical design software and stored in a database based on the prescription parameters, or it can be calculated in real-time by the fusion processing module. This module is typically integrated into the same computing platform, using a complex amplitude superposition algorithm to add the two phase fields point-by-point, followed by phase reset processing (i.e., phase wrapping). The output of the fusion processing module is a phase distribution matrix normalized to a single period. The hardware implementation of this module can be a high-performance CPU or FPGA to ensure real-time processing capabilities.
[0092] The conformal mapping module performs a conformal mapping transformation on the fused phase field, mapping it from a 3D surface coordinate system to a 2D planar coordinate system, resulting in a planarized, customized phase distribution. The conformal mapping transformation is performed according to a predetermined conformal mapping relationship, determined by the planar geometric constraints of the lens substrate and the mapping function from the 3D surface to the 2D plane. This module typically runs on a powerful graphics workstation, utilizing mesh parametric algorithms or finite element solvers. The conformal mapping module can call mature mathematical libraries (such as CGAL, OpenMesh, or PETSc) for numerical solutions. Its inputs are the fused phase field and the 3D surface parameters of the lens's back surface; the output is a planarized phase distribution defined on a 2D rectangular mesh. To handle large-scale meshes, this module may require a large amount of memory and high-speed storage.
[0093] The height field generation module generates height field data based on a planarized custom phase distribution. This height field data drives grayscale lithography or nanoimprint lithography processes. This module receives the planarized phase distribution output from the conformal mapping module. First, it calculates the continuous height field using a phase-height conversion formula (based on the design wavelength and material refractive index). Then, it performs multi-order quantization processing and executes boundary continuity verification and local smoothing optimization. Finally, the height field generation module encapsulates the verified height field data in a standard file format (such as GDSII, BMP, or a custom grayscale image format) and transmits it to the manufacturing equipment via a data interface (such as Ethernet, USB, or a dedicated data cable). This module can include an industrial control computer equipped with a dedicated image processing card and I / O interfaces to ensure seamless integration with manufacturing equipment (such as grayscale lithography machines or nanoimprint lithography machines).
[0094] Specific limitations regarding the personalized wavefront compensation system based on wearable geometric optical paths can be found in the limitations of the personalized wavefront compensation method based on wearable geometric optical paths described above, and will not be repeated here. Each module in the aforementioned personalized wavefront compensation system based on wearable geometric optical paths can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in a computer device, or stored in software in the memory of a computer device, so that the processor can call and execute the corresponding operations of each module.
[0095] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores data from a personalized wavefront compensation system based on wearable optical geometry. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a personalized wavefront compensation method based on wearable optical geometry.
[0096] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0097] Thirdly, a computer device is provided, including a memory and a processor. The memory is communicatively connected to the processor, and the memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the personalized wavefront compensation method based on the wearable geometric optical path described above. Furthermore, the specific limitations of the computer device in implementing the personalized wavefront compensation method based on the wearable geometric optical path can be found in the limitations of the personalized wavefront compensation method based on the wearable geometric optical path described above, and will not be repeated here.
[0098] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the personalized wavefront compensation method based on the wearable geometric optical path described above. Furthermore, the specific limitations of the computer-readable storage medium in implementing the personalized wavefront compensation method based on the wearable geometric optical path can be found in the limitations of the personalized wavefront compensation method based on the wearable geometric optical path described above, and will not be repeated here.
[0099] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0100] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0101] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.
Claims
1. A personalized wavefront compensation method based on the wearing geometry optical path, characterized in that, The method includes: The prescription parameters of the wearer's eyeball, the geometric parameters of the frame in the wearing state, and the individualized physiological parameters of the wearer's eyeball are obtained. The geometric parameters include vertex distance, anterior tilt angle, wrap angle, and pupillary distance deviation. The individualized physiological parameters include corneal anterior surface morphology data. Using the center of eye rotation as the origin of the coordinate system, a vector tracing model is constructed by combining the corneal anterior surface topography data. The vector tracing model includes the dynamic trajectory of the corneal vertex and the posterior surface of the lens. The geometric parameters are input into the vector tracing model for ray tracing to calculate the distortion phase distribution. The distortion phase distribution is caused by the combined effects of vertex distance, forward tilt angle, wrap angle and pupil distance deviation, and characterizes the deviation of the actual wavefront from the design wavefront. A personalized wavefront compensation term is generated based on the aforementioned distorted phase distribution; The personalized wavefront compensation term is fused with the basic phase field corresponding to the prescription parameters to obtain the fused phase field. The fused phase field is subjected to a conformal mapping transformation to map the fused phase field from a three-dimensional curved surface coordinate system to a two-dimensional planar coordinate system, resulting in a planarized customized phase distribution. The conformal mapping transformation is performed according to a predetermined conformal mapping relationship, which is determined by the planar geometric constraints of the lens substrate and the mapping function from the three-dimensional curved surface to the two-dimensional plane. Height field data is generated based on the planarized customized phase distribution, and the height field data is used to drive grayscale lithography or nanoimprint lithography processes.
2. The method according to claim 1, characterized in that, The conformal mapping transformation includes: Construct the three-dimensional surface parametric equations for the rear surface of the lens; Establish a mapping relationship between the parameters of the three-dimensional surface and the two-dimensional plane coordinates, wherein the mapping relationship is a conformal mapping that satisfies the Laplace equation; Based on the mapping relationship, the sampling points of the fused phase field on the three-dimensional curved surface are mapped to the corresponding points on the two-dimensional plane to obtain the planarized customized phase distribution.
3. The method according to claim 1, characterized in that, The process of generating height field data based on the planarized customized phase distribution includes: Based on the material's refractive index and the design wavelength, the planarized customized phase distribution is converted into a continuous height field; The continuous height field is subjected to multi-order quantization to obtain a discretized height field; The boundary continuity of the discretized height field is checked to determine whether the height difference between adjacent microstructure units exceeds a preset gradient threshold. If the gradient threshold is exceeded, the discretized height field is locally smoothed until the height difference does not exceed the gradient threshold, thus obtaining the verified height field data.
4. The method according to claim 1 or 3, characterized in that, Before generating the height field data, the following steps are also included: A two-dimensional Fourier transform is performed on the planarized customized phase distribution obtained based on the fused phase field to obtain the spatial spectrum; Based on the preset minimum linewidth constraint, the spatial spectrum is low-pass filtered to remove high-frequency components that exceed the manufacturing process limits. A two-dimensional inverse Fourier transform is performed on the filtered spectrum to obtain a manufacturability-optimized planar phase distribution, which is then used as a planarized customized phase distribution for generating the height field data.
5. The method according to claim 1, characterized in that, The individualized ocular physiological parameters also include intraocular media refractive index distribution data, which includes corneal refractive index, aqueous humor refractive index, lens equivalent refractive index, and vitreous refractive index. When calculating the distortion phase distribution, the vector tracing model uses the refractive index distribution data of the intraocular medium as the refractive index field constraint for light transmission between the cornea and retina, and calculates the actual optical path length based on the refractive index field constraint.
6. The method according to claim 5, characterized in that, The corneal anterior surface morphology data includes the corneal vertex radius of curvature, corneal aspheric coefficient, and corneal anterior surface asymmetry parameters in the horizontal and vertical directions.
7. The method according to claim 5, characterized in that, The equivalent refractive index of the lens is determined by the combined curvature radius of the anterior surface, the curvature radius of the posterior surface, and the thickness at the center of the lens.
8. The method according to claim 1, characterized in that, The step of generating a personalized wavefront compensation term based on the distorted phase distribution includes: The Zernike polynomial was used to fit the distortion phase distribution, and the coefficients of each order corresponding to defocus, astigmatism, coma and spherical aberration were extracted. Based on the extracted coefficients of each order, the sum of the products of the Zernik coefficients and the corresponding Zernik polynomials is calculated, and the negative of the sum is used as the personalized wavefront compensation term.
9. The method according to claim 1, characterized in that, The step of fusing the personalized wavefront compensation term with the base phase field corresponding to the prescription parameters to obtain the fused phase field includes: The net phase distribution is obtained by vector superposition of the basic phase field and the personalized wavefront compensation term in the complex amplitude space. The net phase distribution is subjected to phase reset processing to compress its value range to a single phase period, and then the fused phase field is obtained.
10. A personalized wavefront compensation system based on a wearable optical geometry path, characterized in that, The system includes: The parameter acquisition module is used to acquire the prescription parameters of the wearer's eyeball, the geometric parameters of the frame in the wearing state, and the wearer's individualized ocular physiological parameters. The geometric parameters include vertex distance, anterior tilt angle, wrap angle, and pupillary distance deviation. The individualized ocular physiological parameters include corneal anterior surface morphology data. The model building module is used to construct a vector tracing model with the eyeball rotation center as the coordinate origin and the corneal anterior surface topography data. The vector tracing model includes the dynamic trajectory of the corneal vertex and the posterior surface of the lens. The ray tracing calculation module is used to input the geometric parameters into the vector tracing model to perform ray tracing and calculate the distortion phase distribution. The distortion phase distribution is caused by the combined effects of vertex distance, forward tilt angle, wrap angle and pupil distance deviation, and characterizes the deviation of the actual wavefront from the design wavefront. The compensation term generation module is used to generate a personalized wavefront compensation term based on the distortion phase distribution. The fusion processing module is used to fuse the personalized wavefront compensation term with the basic phase field corresponding to the prescription parameters to obtain a fused phase field. The conformal mapping module is used to perform conformal mapping transformation on the fused phase field, mapping the fused phase field from a three-dimensional curved surface coordinate system to a two-dimensional planar coordinate system to obtain a planarized customized phase distribution. The conformal mapping transformation is performed according to a predetermined conformal mapping relationship, which is determined by the planar geometric constraints of the lens substrate and the mapping function from the three-dimensional curved surface to the two-dimensional plane. A height field generation module is used to generate height field data based on the planarized customized phase distribution, and the height field data is used to drive grayscale lithography or nanoimprint lithography processes.
11. A computer device comprising a memory and a processor, the memory being communicatively connected to the processor, and the memory storing a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the personalized wavefront compensation method based on the wearing geometric optical path as described in any one of claims 1 to 9.
12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the personalized wavefront compensation method based on the wearing geometric optical path as described in any one of claims 1 to 9.