Processing method and system for sparse compression reconstruction of LDI sub-pixel image and application

Abstract

The invention provides a processing method and system for reconstructing an LDI sub-pixel image through sparse compression and application, and the method comprises the steps: calculating a low-resolution to-be-exposed image corresponding to each phase structure in advance through a computer image compression algorithm; the low-resolution to-be-exposed images obtained through calculation are loaded to the digital micro-reflector according to the time sequence, and the display moment of each pattern is matched with the rotation position of the corresponding phase structure; coupling the pattern of the digital micro-mirror and the phase encoding mask in a frequency domain through a 4-f optical system, and reconstructing a high-resolution exposure pattern at a sub-pixel level by utilizing a diffraction effect; projecting a high-resolution light field of the reconstructed high-resolution exposure pattern to the surface of the photoresist, and forming a target circuit pattern by accumulating exposure dose; and the micro-nano structure with sub-pixel precision is obtained after development. The system comprises an image compression module, a pattern matching module and a pattern forming module. According to the invention, the manufacturing cost of the laser direct imaging equipment is reduced under the condition of the same precision.

Description

Technical Field

[0001] The present invention relates to the technical field of printed circuit board (PCB) exposure equipment, and in particular to a processing method, system and application of sparse compression reconstruction of LDI sub-pixel images. Background Art

[0002] Laser direct imaging (LDI) exposure systems are a new generation of printed circuit board (PCB) exposure equipment. They simplify the exposure process, eliminating the need for exposure masks and significantly outperforming traditional exposure systems that require mask production in terms of real-time performance. Their use of digital masks is driving the evolution of green, environmentally friendly, and refined electronics manufacturing, making them a core component of high-end PCB intelligent manufacturing. Their basic principle is to digitally control the laser beam to illuminate a photoresist (including photoresist) using a designed circuit pattern, thereby forming the desired circuit pattern on the photoresist. Implementation methods include direct control of the laser beam for rapid single-point scanning or simultaneous laser direct imaging of multiple pixels using a digital micromirror (DMD). Existing technology determines the resolution of LDI systems based on pixel size, and no comparable sub-pixel enhancement technology has been found for LDI. When using digital micromirrors as LDI systems, since they are digital mirrors rather than continuous imaging devices, the pixel size of the entire imaging system is fixed, and the resulting circuit board precision is therefore determined by this size.

[0003] Prior art 1, application number: CN202411785211.0 discloses a data processing method, system and related equipment in the process of laser direct imaging, which is used to achieve a balance between imaging accuracy and scanning efficiency in the process of laser scanning imaging. The method includes: obtaining each target area of the pixel row where the preset type of pixel points in the original dot matrix image are located; improving the resolution of the target area in the vertical direction of the laser scanning direction, and reducing the resolution of other areas outside the target area in the vertical direction of the laser scanning direction to obtain a corrected image for laser scanning imaging. Although the balance between imaging accuracy and scanning efficiency is achieved in the process of laser scanning imaging; however, a selective resolution adjustment strategy is adopted to improve the resolution in a specific target area at the expense of the accuracy of other areas. There are limitations in regional resolution adjustment, and the scanning direction is single.

[0004] Prior art 2, application number CN202510034829.1, discloses a method and system for quality inspection of perforated workpieces. The inspection method includes: a laser passes through a small hole in the workpiece to be inspected to form a diffraction image, the diffraction image appearing as multiple layers of circular bright rings; projecting the diffraction image onto an imaging unit; the imaging unit transmitting the diffraction image to a processing unit; the processing unit extracting the bright spot center area of the diffraction image, performing a polar coordinate transformation on the original diffraction image based on the sub-pixel points in the bright spot center area to obtain a horizontal stripe image; extracting the sub-pixel coordinates of the centerline of the horizontal stripe image; converting the extracted sub-pixel coordinates back to the original Cartesian image coordinates to obtain the trajectory centerline of each layer of circular rings; and calculating the actual center, actual roundness, and actual diameter of each layer of circular rings based on the trajectory centerline of each layer of circular rings; and an analysis unit analyzing the actual center, actual roundness, and actual diameter to obtain defect information of the workpiece to be inspected. Although it can efficiently and accurately detect small defects, sub-pixel defect detection achieved through post-processing is only applicable to the analysis of specific geometric features such as circular rings.

[0005] Prior art three, application number: CN202411675121.6, discloses a method for measuring whole-layer atmospheric turbulence based on centroid drift and light intensity scintillation, belonging to the field of satellite-to-ground laser communication technology. The atmospheric turbulence parameter measurement steps include: using a high-resolution imaging lens and a high-speed visible light camera as a receiving device to collect starlight spot images after atmospheric turbulence; then, edge detection of the star image is performed using the Zernike moment to accurately analyze and identify the shape features in the star image, achieving sub-pixel edge detection; on this basis, dynamic Lanczos interpolation is performed on the edge area of the star point to achieve resampling and retain star image details, and the normalized amplitude enhancement weighting method of the grayscale gradient is used to improve the accuracy of centroid positioning, improve anti-interference ability and achieve higher positioning accuracy; finally, by calculating the light intensity scintillation variance and the centroid drift variance, the whole-layer atmospheric turbulence intensity in the atmospheric channel transmission conditions during satellite-to-ground laser communication is obtained. Although the robustness, accuracy and convenience of whole-layer atmospheric turbulence measurement are improved, the hardware-level anti-interference ability is poor due to the reliance on algorithms to compensate for environmental disturbances.

[0006] Currently, existing technologies 1, 2, and 3 face significant limitations on image resolution due to the diffraction limit of the optical system and mechanical precision. They also rely on post-processing hardware-level anti-interference systems and struggle with lossless sub-pixel conversion from digital design to physical devices. Therefore, the present invention provides a method and system for sparse compression reconstruction of LDI sub-pixel images. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a processing method for sparse compression reconstruction of LDI sub-pixel images, comprising the following steps:

[0008] At least two phase structures are arranged in zones on at least one rotatable transparent glass slide, and the rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micro-mirror; a low-resolution image to be exposed corresponding to each phase structure is pre-calculated using a computer image compression algorithm;

[0009] The calculated low-resolution exposure image is loaded into the digital micromirror in a time-sequential manner, with the display moment of each pattern matching the rotational position of the corresponding phase structure. The digital micromirror pattern is coupled to the phase-encoding mask in the frequency domain through a 4-f optical system, and the diffraction effect is used to reconstruct the sub-pixel high-resolution exposure pattern.

[0010] The high-resolution light field of the reconstructed high-resolution exposure pattern is projected onto the photoresist surface, and the target circuit pattern is formed by accumulating the exposure dose; after development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical graphics.

[0011] Optionally, the process of precalculating a low-resolution image to be exposed corresponding to each phase structure includes the following steps:

[0012] The optical transfer characteristics of each phase structure on the rotating transparent glass slide are quantified, and a corresponding relationship model between it and spatial frequency is established. Each phase structure is regarded as a separate frequency domain filter, and its rotation position forms a fixed mapping with a specific frequency band component.

[0013] Based on the frequency domain characteristics of the phase structure, a set of overcomplete basis function libraries is generated. Each basis function corresponds to the modulation pattern of the phase structure on the incident light at a specific rotation angle. A sparse optimization algorithm is used to select the basis function combination that best represents the frequency domain characteristics of the target pattern.

[0014] The target high-resolution image is decomposed into multiple sub-band components in the frequency domain. Matching pursuit is performed based on the obtained basis function library, and the frequency domain components that best match the modulation characteristics of the current phase structure are preferentially extracted. The remaining residual image is transferred to the matching process of the next phase structure, and the cycle is repeated until all phase structures are matched or the residual is lower than the set threshold.

[0015] The decomposed frequency domain components are converted into low-resolution control instructions according to the following rules. Each component corresponds to a display frame of the digital micromirror. The frame display timing is strictly synchronized with the rotation phase of the phase structure. The frame content is converted into a realizable micromirror array state through deconvolution processing.

[0016] Optionally, the process of selecting the basis function combination that best represents the frequency domain characteristics of the target graph through a sparse optimization algorithm includes the following steps:

[0017] Using the established correspondence model, the optical transfer characteristics at each rotation angle are converted into an N-dimensional eigenvector, where each dimension of the vector corresponds to the energy coupling coefficient at a specific spatial frequency. The eigenvectors of all phase structures at all rotational positions constitute the original basis function space, whose dimensions are consistent with the frequency domain decomposition depth of the target image.

[0018] For the frequency domain subband components of the target image, the projection energy ratio of each basis function to the current subband component is calculated; a dynamic energy threshold function is set, whose independent variables include: the main frequency band weight of the correspondence model corresponding to the current rotation angle of the phase structure, and the cumulative frequency domain energy of the previous phase structure that has been matched. Only basis functions with a projection energy ratio exceeding the threshold are retained in the candidate set;

[0019] Set dual constraints of forward constraint and reverse constraint on the candidate basis functions: use the screened basis functions as the initial population, perform frequency domain topology adjustment: the output basis function combination satisfies, and the joint frequency domain coverage of the combination reaches more than a preset percentage of the total energy of the target image.

[0020] Optional, forward constraint, the main lobe direction of the basis function must be less than the set tolerance with the maximum modulation direction of the current phase structure; reverse constraint, the side lobe energy distribution of the basis function must not have more than 5% spectral overlap with the matched frequency domain component.

[0021] Optionally, the process of setting a dynamic energy threshold function includes the following steps:

[0022] Based on the established correspondence model, the main frequency band weight distribution under the current phase structure rotation angle is extracted to reflect the modulation efficiency advantage of a specific rotation angle on the target frequency band energy. The main frequency band weight is used as the basic adjustment factor of the threshold function, and the efficient basis function that best matches the current rotation angle is preferentially retained in the initial screening stage.

[0023] The cumulative frequency domain energy distribution of the matched previous phase structure is introduced as a dynamic correction term of the threshold function, and the energy proportion of the covered frequency domain sub-bands is updated in real time. As the optimization progresses, the threshold function automatically improves the screening sensitivity of the remaining unmatched high-frequency or low-energy sub-bands.

[0024] The projection energy ratio of the basis function and the current subband component is compared with the dynamic threshold. The main frequency band weight dominates the initial threshold value, and the basis function that is strongly correlated with the current rotation angle is given priority. The cumulative energy distribution dynamically lowers the threshold corresponding to the covered frequency band, forcing the algorithm to migrate to the unmatched frequency band. Only when the projection energy ratio of the basis function satisfies both constraints at the same time, it enters the candidate set.

[0025] Optionally, the process of reconstructing a sub-pixel high-resolution exposure pattern using the diffraction effect includes the following steps:

[0026] The synchronous frequency timing of phase structure rotation and micromirror refresh is obtained. Each phase structure activates the corresponding pre-calculated low-resolution image to be exposed at a specific rotation angle. The spatial distribution characteristics of the phase structure and the micromirror pattern are conjugated on the object plane of the 4-f system, forming a joint space-frequency modulation unit.

[0027] The modulated light field is decomposed into the frequency domain using the Fourier transform characteristics of the 4-f system. Each phase structure rotation position corresponds to a set of characteristic basis functions, whose main lobe direction is uniquely determined by the current rotation angle. The frequency domain components of the micromirror pattern are projected and matched with the phase structure basis functions, retaining only the basis function components whose projection energy exceeds the dynamic threshold.

[0028] The filtered frequency domain components are inversely transformed to the image plane through the 4-f system. The basis function groups activated at different rotation angles form multiple low-resolution light fields with sub-pixel phase differences on the image plane. They are incoherently superimposed through the diffraction effect within the exposure time. The superposition result is equivalent to the frequency domain interpolation reconstruction of the target high-resolution image.

[0029] Optionally, the discrete phase delay generated by the partitioned layout of the phase structure in the space-frequency joint modulation unit directionally diffracts the incident light field; the binary amplitude modulation of the micro-mirror pattern and the phase delay field realize complex multiplication coupling in the frequency domain.

[0030] Optionally, the process of projectively matching the frequency domain component of the micro-mirror pattern with the phase structure basis function includes the following steps:

[0031] The modulated light field is decomposed into the frequency domain. The phase structure rotation angle locks the main lobe direction characteristics of the basis function. The basis function corresponding to each rotation angle comes from the established space-frequency joint modulation unit and the spatial distribution of the phase structure is converted into a frequency domain eigenvector via a 4-f system.

[0032] The frequency domain components of the micro-mirror pattern are selected through dynamic energy gating. When the phase structure is rotated to a predetermined angle, the generated basis function main lobe scans the frequency domain components of the micro-mirror pattern like a probe. A projection energy threshold is used as the matching criterion: the basis function is activated only when the frequency domain energy covered by the basis function main lobe exceeds the set dynamic threshold.

[0033] The retained basis function components carry dual information, including both the rotation parameters of the phase structure and the local frequency domain characteristics of the micromirror pattern. During the inverse transformation, they spontaneously reconstruct a low-resolution light field with a specific phase difference.

[0034] The present invention provides a processing system for sparse compression reconstruction of LDI sub-pixel images, comprising:

[0035] An image compression module is responsible for arranging at least two phase structures on at least one rotatable transparent glass slide. The rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micro-mirror. A low-resolution image to be exposed corresponding to each phase structure is pre-calculated using a computer image compression algorithm.

[0036] The pattern matching module is responsible for loading the calculated low-resolution exposure image into the digital micromirror in a timed manner. The display moment of each pattern matches the rotational position of the corresponding phase structure. The digital micromirror pattern is coupled to the phase encoding mask in the frequency domain through a 4-f optical system, and the diffraction effect is used to reconstruct the sub-pixel high-resolution exposure pattern.

[0037] The graphics formation module is responsible for projecting the high-resolution light field of the reconstructed high-resolution exposure pattern onto the photoresist surface, forming the target circuit pattern by accumulating exposure doses; after development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical graphics.

[0038] The present invention provides an application of a processing method for sparse compression reconstruction of LDI sub-pixel images, which includes: a phase encoding design stage, a dynamic light field reconstruction stage, and a circuit pattern transfer stage.

[0039] This invention provides a processing method for achieving higher-resolution imaging in intelligent laser direct imaging devices. It primarily addresses the problem of enabling larger-pixel digital micromirrors in laser direct imaging devices to achieve sub-pixel imaging on printed circuit boards, thereby reducing the manufacturing cost of laser direct imaging devices while maintaining the same precision. The invention also provides a processing method for sparse compression reconstruction of LDI sub-pixel images, thus overcoming this size limitation. This method can be considered to improve manufacturing precision while maintaining existing equipment costs, or to reduce the cost of LDI devices while maintaining the same manufacturing precision.

[0040] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0041] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0043] Figure 1Flowchart of the processing method for sparse compression reconstruction of LDI sub-pixel images in Example 1 of the present invention;

[0044] Figure 2 A diagram showing a process of precalculating a low-resolution image to be exposed corresponding to each phase structure in embodiment 2 of the present invention;

[0045] Figure 3 This is a diagram showing the process of reconstructing a sub-pixel-level high-resolution exposure pattern using the diffraction effect in Example 5 of the present invention;

[0046] Figure 4 1 is a process diagram of forming a target circuit pattern by accumulating exposure doses in Example 8 of the present invention;

[0047] Figure 5 This is a block diagram of a processing system for sparse compression reconstruction of LDI sub-pixel images in Example 9 of the present invention;

[0048] Figure 6 Schematic diagram of uneven top-hat intensity of exposure lines in Example 9 of the present invention. DETAILED DESCRIPTION

[0049] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0050] The terms used in the embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present application. The singular forms "a", "the" and "the" used in the embodiments of the present application are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0051] When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0052] Example 1: Figure 1 As shown, an embodiment of the present invention provides a processing method for sparse compression reconstruction of LDI sub-pixel images, comprising the following steps:

[0053] S100: Arranging at least two phase structures in zones on at least one rotatable transparent glass slide, wherein the rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micro-mirror; pre-calculating a low-resolution image to be exposed corresponding to each phase structure using a computer image compression algorithm;

[0054] S200: The calculated low-resolution image to be exposed is loaded into the digital micro-mirror in a time sequence, with the display time of each pattern matching the rotation position of the corresponding phase structure; the pattern of the digital micro-mirror is coupled to the phase encoding mask in the frequency domain through a 4-f optical system, and the diffraction effect is used to reconstruct a sub-pixel high-resolution exposure pattern;

[0055] S300: The high-resolution light field of the reconstructed high-resolution exposure pattern is projected onto the photoresist surface, and the target circuit pattern is formed by accumulating the exposure dose; after development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical graphics.

[0056] The working principle and beneficial effects of the above technical solution are as follows: First, at least two phase structures are partitioned on at least one rotatable transparent glass slide, and the rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micromirror. A low-resolution image to be exposed corresponding to each phase structure is pre-calculated using a computer image compression algorithm. Secondly, the calculated low-resolution image to be exposed is loaded into the digital micromirror in a time sequence, with the display time of each pattern matching the rotation position of the corresponding phase structure. The digital micromirror pattern is coupled with the phase encoding mask in the frequency domain through a 4-f optical system, and a sub-pixel high-resolution exposure pattern is reconstructed using the diffraction effect. Finally, the high-resolution light field of the reconstructed high-resolution exposure pattern is projected onto the photoresist surface, and the target circuit pattern is formed by accumulating the exposure dose. After development, a micro-nanostructure with sub-pixel precision is obtained, completing the full process conversion from computational to physical pattern. The above solution achieves super-diffraction-limited lithographic pattern manufacturing through system-level collaboration of computational optics and dynamic light field modulation. By establishing synchronous control of phase structure rotation and DMD pattern refresh, a spatiotemporally modulated optical transfer function is constructed. The rotational modulation of the multi-phase structure forms an overcomplete basis in the frequency domain, breaking the Abbe diffraction limit through the diffraction effect. The lithography process compatibility is optimized using dose control using combined temporal and spatial modulation.

[0057] This embodiment achieves an increase in equivalent numerical aperture while maintaining the simplicity of the optical system through deep coupling of hardware (rotating phase plate + DMD + 4f system) and algorithm (compressed sensing reconstruction).

[0058] This embodiment provides a processing method for achieving higher-resolution imaging in intelligent laser direct imaging (LDI) devices. The primary problem addressed is enabling a larger-pixel digital micromirror (DMD) in a LDI device to achieve sub-pixel imaging onto a printed circuit board (PCB), thereby reducing the manufacturing cost of the LDI device while maintaining the same precision. The present invention provides a processing method for sparse compression reconstruction of LDI sub-pixel images, thus overcoming this size limitation. This method can be considered to improve manufacturing precision while maintaining existing device costs, or to reduce the cost of the LDI device while maintaining the same manufacturing precision.

[0059] Example 2: Figure 2 As shown, based on Example 1, the process of precalculating a low-resolution image to be exposed corresponding to each phase structure provided by the embodiment of the present invention includes the following steps:

[0060] S101: Quantify the optical transfer characteristics of each phase structure on the rotating transparent glass slide, establish a corresponding relationship model between the phase structure and the spatial frequency, and regard each phase structure as a separate frequency domain filter, whose rotation position forms a fixed mapping with a specific frequency band component;

[0061] S102: Based on the frequency domain characteristics of the phase structure, a set of overcomplete basis function libraries is generated. Each basis function corresponds to the modulation pattern of the phase structure on the incident light at a specific rotation angle. A sparse optimization algorithm is used to select the basis function combination that best represents the frequency domain characteristics of the target pattern.

[0062] S103: Decompose the target high-resolution image into multiple sub-band components in the frequency domain, perform matching pursuit based on the obtained basis function library, and preferentially extract the frequency domain components that best match the modulation characteristics of the current phase structure. The remaining residual image is transferred to the matching process of the next phase structure, and the cycle continues until all phase structures are matched or the residual is lower than the set threshold.

[0063] S104: The frequency domain components obtained by decomposition are converted into low-resolution control instructions according to the following rules. Each component corresponds to a display frame of the digital micromirror. The frame display timing is strictly synchronized with the rotation phase of the phase structure. The frame content is converted into an achievable micromirror array state through deconvolution processing.

[0064] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first quantifies the optical transfer characteristics of each phase structure on the rotating transparent glass slide, establishes a corresponding relationship model between the optical transfer characteristics and the spatial frequency, and regards each phase structure as a separate frequency domain filter, whose rotational position forms a fixed mapping with a specific frequency band component. Secondly, based on the frequency domain characteristics of the phase structure, a set of overcomplete basis function libraries is generated, each basis function corresponding to the modulation pattern of the phase structure on the incident light at a specific rotation angle. A sparse optimization algorithm is used to screen the basis function combination that best represents the frequency domain characteristics of the target image. Then, the target high-resolution image is decomposed into multiple sub-band components in the frequency domain. Matching pursuit is performed based on the obtained basis function library, and the frequency domain components that best match the modulation characteristics of the current phase structure are preferentially extracted. The remaining residual image is transferred to the matching process of the next phase structure, and the cycle is repeated until all phase structures are matched or the residual is lower than a set threshold. Finally, the decomposed frequency domain components are converted into low-resolution control instructions according to the following rules. Each component corresponds to a display frame of the digital micromirror. The frame display timing is strictly synchronized with the rotation phase of the phase structure. The frame content is converted into a realizable micromirror array state through deconvolution processing. The above scheme achieves computational optical compression and physical reconstruction of high-resolution lithographic patterns through the synergistic effects of phase structure optical property quantization, frequency-domain basis function library construction, target image sparse decomposition, and spatiotemporal encoding conversion. The dynamic modulation characteristics of the rotating phase structure are deeply coupled with the spatiotemporal encoding of the digital micromirrors. A fixed mapping between the phase structure's rotational position and spatial frequency ensures that each low-resolution control frame precisely matches the frequency-domain filtering characteristics of the current phase structure, thereby achieving sparse encoding of sub-pixel information in the optical frequency domain. Target image decomposition based on an overcomplete basis function library adaptively allocates high-frequency information to exposure sequences corresponding to different phase structures. A residual iteration mechanism ensures that all frequency band components are effectively captured, effectively constructing an inverse system of the time-varying optical transfer function. This allows the superposition of diffraction fields from multiple low-resolution frames to exceed the physical resolution limitations of the digital micromirrors. The phase structure's rotational synchronization and the digital micromirror's frame refresh form a closed-loop control. The decomposed frequency domain components are directly converted into exposure instructions that strictly match the hardware timing. This ensures that each computed low-resolution image meets the physical constraints of the subsequent 4-f system frequency-domain coupling, avoiding spectral aliasing in the reconstructed light field. The sparse optimization algorithm prioritizes frequency domain components with concentrated energy for encoding, significantly reducing the number of basis functions that need to be processed while ensuring reconstruction accuracy; combined with residual threshold control, a controllable trade-off between computational complexity and graphic fidelity is achieved, ensuring that the method is suitable for the rapid preparation of large-scale integrated circuit graphics.

[0065] In summary, this embodiment expands the effective degrees of freedom of the optical system through dynamic modulation of the rotating phase structure, transforms the resolution bottleneck of the traditional spatial light modulator into a time-frequency joint optimization problem, and ultimately achieves graphics generation capabilities on the photoresist surface that exceed hardware pixel limitations.

[0066] Example 3: Based on Example 2, the process provided by the embodiment of the present invention for selecting the basis function combination that best represents the frequency domain characteristics of the target graphic through a sparse optimization algorithm includes the following steps:

[0067] S1011: Using the established correspondence model, the optical transfer characteristics at each rotation angle are converted into an N-dimensional eigenvector, where each dimension of the vector corresponds to the energy coupling coefficient of a specific spatial frequency; the eigenvectors of all phase structures at all rotation positions constitute the original basis function space, whose dimension is consistent with the frequency domain decomposition depth of the target image;

[0068] S1012: For the frequency domain subband components of the target image, calculate the projection energy ratio of each basis function to the current subband component; set a dynamic energy threshold function, whose independent variables include: the main frequency band weight of the correspondence model corresponding to the current rotation angle of the phase structure, and the cumulative frequency domain energy of the previous phase structure that has been matched. Only basis functions whose projection energy ratio exceeds the threshold are retained in the candidate set;

[0069] S1013: Setting dual constraints of forward and reverse constraints on the candidate basis functions: using the screened basis functions as the initial population, performing frequency domain topology adjustment: the output basis function combination satisfies, and the combined joint frequency domain coverage reaches a preset percentage of the total energy of the target image;

[0070] For the forward constraint, the main lobe direction of the basis function must have an angle with the maximum modulation direction of the current phase structure that is less than the set tolerance; for the reverse constraint, the sidelobe energy distribution of the basis function must not have a spectrum overlap of more than 5% with the matched frequency domain component.

[0071] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first uses the established correspondence model to convert the optical transfer characteristics at each rotation angle into an N-dimensional feature vector, where each dimension of the vector corresponds to the energy coupling coefficient of a specific spatial frequency; the feature vectors of all phase structures at all rotation positions constitute the original basis function space, whose dimension is consistent with the frequency domain decomposition depth of the target image; secondly, for the frequency domain subband components of the target image, the projection energy ratio of each basis function to the current subband component is calculated; a dynamic energy threshold function is set, whose independent variables include: the main frequency band weight of the correspondence model corresponding to the current rotation angle of the phase structure The algorithm then applies dual forward and reverse constraints to the candidate basis functions, using the selected basis functions as the initial population and performing frequency domain topology adjustment. The output basis function combinations must meet the requirement that their combined frequency domain coverage exceeds a preset percentage of the target image's total energy. Under the forward constraint, the mainlobe direction of the basis function must be within a set tolerance of the maximum modulation direction of the current phase structure. Under the reverse constraint, the sidelobe energy distribution of the basis function must not overlap with the matched frequency domain components by more than 5%. Based on a model of the rotation angle-optical transfer characteristic correspondence, the proposed scheme quantifies the spatial modulation capability of the phase structure as a multidimensional frequency domain coupling coefficient, forming the original basis function space. Through dual screening using the projection energy ratio and a dynamic energy threshold, the algorithm prioritizes basis functions that are strongly correlated with the current subband energy distribution of the target image, achieving adaptive focusing of frequency domain energy. The dynamic threshold function uses mainband weights and cumulative energy feedback to ensure that the screening process consistently converges towards the high-energy region of the unmatched frequency domain components. The dual constraint mechanism ensures the physical feasibility of the basis function combination from the joint time-frequency dimension. The forward constraint forces the main lobe direction of the basis function to be aligned with the maximum modulation direction of the phase structure, avoiding the loss of actual system modulation efficiency due to rotation angle deviation; the reverse constraint eliminates the energy redundancy of the matched frequency domain components by suppressing the overlap of the sidelobe spectrum. The two work together to ensure that the final output basis function combination can meet the joint frequency domain coverage requirements with the minimum cardinality, achieving the essential goal of sparse optimization. The entire process embeds the physical constraints of the optical system (such as the rotational adjustable range and modulation directionality of the phase structure) into the mathematical optimization process. The spatial dimension of the original basis function is strictly consistent with the frequency domain decomposition depth of the target image, ensuring that the basis function combination output by the algorithm can directly drive the actual optical modulation device; the joint coverage characteristics of the basis functions output by the frequency domain topology adjustment essentially reflect the maximum achievable reconstruction fidelity of the optical system for the frequency domain characteristics of the target image.

[0072] In summary, this embodiment generates a basis function combination with high representation efficiency (low number of basis functions) and high reconstruction accuracy (frequency domain coverage meets the standard) through frequency domain energy-guided sparse screening and dual-constraint optimization, providing the optimal frequency domain operation basis for optical imaging or computational imaging tasks.

[0073] Example 4: Based on Example 3, the process of setting a dynamic energy threshold function provided in this embodiment of the present invention includes the following steps:

[0074] S10121: Based on the established correspondence model, the main frequency band weight distribution under the current phase structure rotation angle is extracted to reflect the modulation efficiency advantage of a specific rotation angle on the target frequency band energy. The main frequency band weight is used as the basic adjustment factor of the threshold function. In the initial screening stage, the efficient basis function that best matches the current rotation angle is preferentially retained.

[0075] S10122: Introduce the cumulative frequency domain energy distribution of the matched previous phase structure as a dynamic correction term for the threshold function, and update the energy proportion of the covered frequency domain subbands in real time. This allows the threshold function to automatically increase the screening sensitivity for the remaining unmatched high-frequency or low-energy subbands as the optimization progresses.

[0076] S10123: Compare the projection energy ratio of the basis function and the current subband component with the dynamic threshold. The main frequency band weight dominates the initial threshold value, and the basis function that is strongly correlated with the current rotation angle is given priority. The cumulative energy distribution dynamically lowers the threshold corresponding to the covered frequency band, forcing the algorithm to migrate to the unmatched frequency band. Only when the projection energy ratio of the basis function satisfies both constraints at the same time, it enters the candidate set.

[0077] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first extracts the main frequency band weight distribution under the current phase structure rotation angle based on the established correspondence model, reflecting the modulation efficiency advantage of the specific rotation angle on the target frequency band energy; the main frequency band weight is used as the basic adjustment factor of the threshold function, and the efficient basis function that best matches the current rotation angle is preferentially retained in the initial screening stage; secondly, the cumulative frequency domain energy distribution of the previous phase structure that has been matched is introduced as a dynamic correction term of the threshold function, and the energy proportion of the covered frequency domain sub-band is updated in real time, so that the threshold function automatically improves the screening sensitivity of the remaining unmatched high-frequency or low-energy sub-bands as the optimization process progresses; finally, the projected energy ratio of the basis function and the current sub-band component is compared with the dynamic threshold, the main frequency band weight dominates the initial threshold value, and the basis function that is strongly correlated with the current rotation angle is passed first; the cumulative energy distribution dynamically lowers the threshold corresponding to the covered frequency band, forcing the algorithm to migrate to the unmatched frequency band; only when the projected energy ratio of the basis function satisfies both constraints at the same time, it enters the candidate set. The design process of the dynamic energy threshold function in the above scheme achieves adaptive optimization of frequency domain energy screening through multi-step collaboration. Through the combined effect of the main frequency band weight distribution and the cumulative frequency domain energy feedback, the algorithm dynamically adjusts the screening direction according to the matched energy while retaining the basis function with the optimal modulation efficiency at the current rotation angle. This ensures that the basis function candidate set always contains the basis function with the greatest representation potential for the uncovered frequency band of the target image, avoiding the imbalance in frequency domain energy distribution caused by a fixed threshold. The dynamic threshold comparison of the projection energy ratio combines the local optimization characteristics of the main frequency band weight with the global convergence characteristics of the cumulative energy. The main frequency band weight ensures that the initial screening stage prioritizes the capture of high-energy basis functions that match the current physical state (rotation angle) of the phase structure. The cumulative energy distribution forces the algorithm to gradually shift to energy replenishment in low-frequency or high-resolution sub-bands by lowering the threshold of the saturated frequency band in real time. The two work together to drive the basis function candidate set to approach the complete frequency domain coverage requirement of the target image with the minimum number of iterations. The entire process is achieved through feedforward-feedback coupling of energy thresholds. The feedforward path uses the known correspondence between the rotation angle and the modulation efficiency to quickly narrow the search range; the feedback path (S10122) avoids repeated calculations of the optimized frequency bands through historical matching data; the final output candidate set not only meets the physical feasibility of real-time control of the optical system (guaranteed by the main frequency band weight), but also meets the integrity requirements of the frequency domain energy distribution (guided by the accumulated energy), providing a high-purity input population for subsequent dual-constraint optimization.

[0078] In summary, this embodiment realizes the dynamic adaptation of the basis function screening process, the physical properties of the optical system, and the frequency domain characteristics of the target image through the two-dimensional regulation of the rotation angle correlation and the historical energy distribution, significantly reducing the computational complexity while ensuring the accuracy of the frequency domain reconstruction.

[0079] Example 5: Figure 3As shown, based on Example 1, the process of reconstructing a sub-pixel-level high-resolution exposure pattern using the diffraction effect provided in the embodiment of the present invention includes the following steps:

[0080] S201: Acquire the synchronous frequency timing of phase structure rotation and micro-mirror refresh. Each phase structure activates the corresponding pre-calculated low-resolution image to be exposed at a specific rotation angle. The spatial distribution characteristics of the phase structure and the micro-mirror pattern are conjugated on the object plane of the 4-f system to form a space-frequency joint modulation unit.

[0081] The discrete phase delay generated by the phase structure partition layout directionally diffracts the incident light field; the binary amplitude modulation of the micro-mirror pattern and the phase delay field are coupled by complex multiplication in the frequency domain;

[0082] S202: Decomposing the modulated light field into the frequency domain using the Fourier transform characteristics of the 4-f system. Each phase structure rotation position corresponds to a set of characteristic basis functions, whose main lobe direction is uniquely determined by the current rotation angle. Projection matching is performed on the frequency domain components of the micro-mirror pattern and the phase structure basis functions, retaining only the basis function components whose projection energy exceeds the dynamic threshold.

[0083] S203: The filtered frequency domain components are inversely transformed to the image plane through the 4-f system. The activated basis function groups at different rotation angles form multiple low-resolution light fields with sub-pixel phase differences on the image plane. Incoherent superposition occurs through the diffraction effect within the exposure time. The superposition result is equivalent to the frequency domain interpolation reconstruction of the target high-resolution image.

[0084] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first obtains the synchronous frequency timing of the phase structure rotation and the micro-mirror refresh, and each phase structure activates the corresponding pre-calculated low-resolution image to be exposed at a specific rotation angle. The spatial distribution characteristics of the phase structure and the micro-mirror pattern are conjugated on the object plane of the 4-f system to form a space-frequency joint modulation unit; the discrete phase delay generated by the partition layout of the phase structure performs directionally diffracting on the incident light field; the binary amplitude modulation of the micro-mirror pattern and the phase delay field are coupled by complex multiplication in the frequency domain; secondly, through the Fourier transform characteristics of the 4-f system, The modulated light field is decomposed into the frequency domain. Each phase structure rotation position corresponds to a set of characteristic basis functions, whose main lobe direction is uniquely determined by the current rotation angle. The frequency domain components of the micromirror pattern are projected and matched with the phase structure basis functions, retaining only the basis function components whose projection energy exceeds the dynamic threshold. Finally, the filtered frequency domain components are inversely transformed to the image plane via a 4-f system. The activated basis function groups at different rotation angles form multiple low-resolution light fields with sub-pixel phase differences on the image plane. During the exposure time, they are incoherently superimposed through the diffraction effect. The superposition result is equivalent to the frequency domain interpolation reconstruction of the target high-resolution image. The above scheme realizes sub-pixel photolithography pattern reconstruction based on space-frequency joint modulation and dynamic diffraction synthesis through the synergistic effect of steps S201-S203. Through the precise synchronization of phase structure rotation and micromirror refresh, the pre-calculated low-resolution image sequence is converted into a time-varying diffraction modulation field. This process leverages the frequency-domain manipulation characteristics of the 4-f system. Within the physical resolution limitations of optical hardware, this breakthrough achieves light field reconstruction equivalent to high-frequency interpolation through frequency-domain screening and synthesis of multi-angle basis functions. Essentially, this method maps the frequency-domain optimization results of digital computations into actual light field distributions through the physical effects of diffraction. The combined effect of a phase structure partitioning layout and binary modulation of micromirrors concentrates the incident light energy on the diffraction orders corresponding to the target frequency band. Combined with dynamic threshold filtering to suppress energy in non-critical frequency bands, the system retains only the diffraction components effective for sub-pixel reconstruction. Ultimately, incoherent superposition is used at the image plane to generate exposure patterns that maximize energy efficiency, significantly reducing the energy loss caused by frequency-domain redundancy in traditional methods. The time-varying diffraction field generated by the rotating phase structure and the spatially distributed micromirror pattern together form a temporal-spatial dual encoding. During the frequency-domain decomposition stage, this system effectively suppresses static optical noise. During the image reconstruction stage, incoherent superposition of multiple frames further eliminates random phase errors, making the reconstruction process inherently robust to environmental perturbations and ensuring stable sub-pixel accuracy.

[0085] In summary, this embodiment unifies the forward prediction of computational optics and the reverse constraint of diffraction physics into a single optical path through the space-frequency synergy of programmable phase modulation and binary amplitude modulation, thereby achieving hardware-independent super-resolution exposure capabilities while maintaining the traditional projection lithography system architecture.

[0086] Example 6: Based on Example 5, the process of projecting matching the frequency domain components of the micro-mirror pattern and the phase structure basis function provided in the embodiment of the present invention includes the following steps:

[0087] S2021: Obtain the light field decomposed into the frequency domain, and the main lobe direction characteristics of the phase structure rotation angle locking basis function. The basis function corresponding to each rotation angle comes from the established space-frequency joint modulation unit and the spatial distribution of the phase structure and is converted into a frequency domain feature vector via a 4-f system;

[0088] S2022: The frequency domain components of the micro-mirror pattern are selected using a dynamic energy gate. When the phase structure is rotated to a predetermined angle, the generated basis function main lobe scans the frequency domain components of the micro-mirror pattern like a probe. A projection energy threshold is used as the matching criterion: the basis function is activated only when the frequency domain energy covered by the basis function main lobe exceeds the set dynamic threshold.

[0089] S2023: The retained basis function components carry dual information, including both the rotation parameters of the phase structure and the local frequency domain characteristics of the micro-mirror pattern. During the inverse transformation, they spontaneously reconstruct a low-resolution light field with a specific phase difference.

[0090] The working principle and beneficial effects of the above technical solution are as follows: First, in this embodiment, the phase structure rotation angle locks the main lobe directional characteristics of the basis function. The basis function corresponding to each rotation angle comes from the established space-frequency joint modulation unit and the spatial distribution of the phase structure and is converted into a frequency domain feature vector through a 4-f system; secondly, the frequency domain component of the micro-mirror pattern is feature selected through a dynamic energy gate. When the phase structure is rotated to a predetermined angle, the main lobe of the basis function generated by it will scan the frequency domain component of the micro-mirror pattern like a probe; the projection energy threshold is used as the matching criterion: the basis function will only be activated when the frequency domain energy covered by the main lobe of the basis function exceeds the set dynamic threshold; finally, the retained basis function component carries dual information, including both the rotation parameters of the phase structure and the local frequency domain characteristics of the micro-mirror pattern, and spontaneously reconstructs a low-resolution light field with a specific phase difference during inverse transformation. The projective matching process between the frequency-domain components of the micromirror pattern and the phase structure basis functions in this scheme achieves feature decoupling and reconstruction under joint spatial-frequency domain modulation through the synergistic effect of rotation-angle-constrained basis function mainlobe directional detection, dynamic energy threshold screening, and a dual information retention mechanism. The coordinated matching of the phase structure rotation angle and the frequency-domain components of the micromirror pattern ensures that the basis function mainlobe captures only frequency-domain components consistent with the current spatial modulation state, avoiding interference from irrelevant noise and improving feature extraction accuracy. The projected energy threshold serves as a matching criterion, automatically filtering out low-energy noise components and retaining only valid frequency-domain components, optimizing the signal-to-noise ratio (SNR) in the subsequent reconstruction process. Furthermore, this threshold mechanism is synchronized with the rotation angle, forming a closed-loop control mechanism that ensures that the frequency-domain feature selection strictly corresponds to the spatial modulation state. The activated basis function components simultaneously encode the phase structure rotation parameters and the local frequency-domain characteristics of the micromirror pattern. This allows, during the inverse transform stage, light field reconstruction to not only recover the original amplitude information but also maintain the precise phase difference distribution, thereby achieving sub-pixel resolution enhancement.

[0091] In summary, this embodiment, through the tight coupling of space-frequency joint modulation, dynamic energy screening and dual information retention, enables the system to efficiently extract key features in the frequency domain and accurately reconstruct in the spatial domain, ultimately achieving high-resolution light field synthesis under the diffraction effect.

[0092] Example 7: Based on Example 6, the process of decomposing the modulated light field into the frequency domain provided by the embodiment of the present invention includes the following steps:

[0093] S20211: After the spatial phase delay distribution corresponding to each rotation angle is transformed by the 4-f system front-end, a characteristic basis function cluster with a specific orientation is formed in the frequency domain. The main lobe direction of the basis function is controlled by the rotation angle, so that the frequency domain decomposition has a deterministic mapping relationship between angle and frequency.

[0094] S20212: The binary modulation information of the micro-mirrors is encoded into a frequency-domain energy distribution. When the composite light field output by the space-frequency joint modulation unit passes through the front lens of the 4-f system, its spatial distribution is converted into a frequency-domain characteristic spectrum. This spectrum contains two key components: the basis function framework generated by the phase structure, and the energy filling pattern of the micro-mirror pattern modulation, which together constitute the input conditions for subsequent projection matching.

[0095] S20213: The symmetric optical architecture of the 4-f system ensures a geometric correspondence between the spatial phase delay and the frequency domain basis function orientation, while the amplitude modulation information of the micromirror is losslessly converted to the frequency domain energy envelope.

[0096] The working principle and beneficial effects of the above technical solution are as follows: First, in this embodiment, the spatial phase delay distribution corresponding to each rotation angle is transformed by the front-end of the 4-f system, forming a characteristic basis function cluster with a specific orientation in the frequency domain. The main lobe direction of the basis function is controlled by the rotation angle, so that the frequency domain decomposition has a deterministic mapping relationship between angle and frequency; secondly, the binary modulation information of the micro-mirror is encoded into the frequency domain energy distribution. When the composite light field output by the space-frequency joint modulation unit passes through the front lens of the 4-f system, its spatial distribution is converted into a frequency domain characteristic spectrum, which contains two key components: the basis function framework generated by the phase structure, and the energy filling pattern of the micro-mirror pattern modulation, which together constitute the input conditions for subsequent projection matching; finally, the symmetric optical architecture of the 4-f system ensures that the spatial phase delay and the frequency domain basis function orientation meet the geometric correspondence, and at the same time, the amplitude modulation information of the micro-mirror is losslessly converted into the frequency domain energy envelope. The above scheme achieves precise conversion of spatial modulation information into frequency-domain features through the synergistic effect of rotation-angle-constrained basis function cluster generation, frequency-domain encoding of binary modulation information, and a fidelity-preserving transfer mechanism within the optical architecture. The strict correspondence between the phase structure rotation angle and the basis function mainlobe orientation ensures a predictable geometric correlation between the spatial modulation parameters and the frequency-domain decomposition results, providing a structured basis function framework for projection matching. The binary amplitude modulation of the micromirror and the spatial delay of the phase structure are characterized in the frequency domain as an energy-filling pattern and a basis function framework, respectively. This dual-channel encoding mechanism preserves the full dimensionality of the original modulation information, ensuring that the frequency-domain signature spectrum contains both amplitude and phase features. The symmetric architecture of the 4-f system maintains the strict geometric correspondence between the spatial-domain phase distribution and the frequency-domain basis function orientations, while also ensuring energy conservation during the space-to-frequency conversion of the amplitude modulation information, providing a distortion-free frequency-domain input for dynamic threshold screening.

[0097] In summary, this embodiment achieves the precise decomposition of the modulated light field into frequency domain features through the organic combination of angle-frequency mapping, dual-channel information encoding, and optical fidelity conversion. Its output has both a structured basis function framework and precise energy distribution characteristics, laying the foundation for frequency domain analysis for frequency domain screening and sub-pixel reconstruction.

[0098] Example 8: Figure 4 As shown, based on Example 1, the process of forming a target circuit pattern by accumulating exposure dose provided by the embodiment of the present invention includes the following steps:

[0099] S301: The reconstructed high-resolution light field forms a multi-frame low-dose exposure pattern with sub-pixel displacement characteristics on the image plane. The intensity distribution of each frame pattern is derived from the frequency domain coupling result of the corresponding phase structure and the micro-mirror pattern. The sub-pixel light field offset between each frame is controlled by the phase structure rotation timing, and the cumulative dose spatially covers all high-frequency details of the target pattern.

[0100] S302: The nonlinear response characteristics of the photoresist to the projected light field convert the continuous dose distribution into a binary pattern. When the exposure dose of a single frame is lower than the photoresist threshold, the superimposed dose of multiple frames reaches a critical value, triggering a photochemical reaction. This synergistically acts with the reconstructed sub-pixel light field spatial distribution, allowing the resolution of the final developed pattern to exceed the diffraction limit of the single-frame optical system.

[0101] S303: The redundant exposure introduced by the phase structure rotation compensates for the dose quantization error caused by the discrete refresh of the micro-mirror, while the light field reconstructed by frequency domain coupling suppresses the image distortion caused by the proximity effect by controlling the spatial gradient of the dose in each frame.

[0102] The working principle and beneficial effects of the above technical solution are as follows: first, the high-resolution light field reconstructed in this embodiment forms a multi-frame low-dose exposure pattern with sub-pixel displacement characteristics on the image plane, and the intensity distribution of each frame pattern comes from the frequency domain coupling result of the corresponding phase structure and the micro-mirror pattern; the sub-pixel light field offset between frames is controlled by the phase structure rotation timing, and the cumulative dose spatially covers all high-frequency details of the target pattern; secondly, the nonlinear response characteristics of the photoresist to the projected light field convert the continuous dose distribution into a binary pattern. When the single-frame exposure dose is lower than the photoresist threshold, when the multi-frame superimposed dose reaches the critical value, a photochemical reaction is triggered, which works synergistically with the reconstructed sub-pixel light field spatial distribution, so that the resolution of the final developed pattern exceeds the diffraction limit of the single-frame optical system; finally, the redundant exposure introduced by the phase structure rotation compensates for the dose quantization error of the micro-mirror discretization refresh, and the light field reconstructed by frequency domain coupling suppresses the pattern distortion caused by the proximity effect by controlling the spatial gradient of the dose of each frame. The above scheme achieves physical transfer of sub-pixel pattern precision through the process of cumulative exposure dose formation, manifesting as a synergistic effect of high-resolution light field modulation, nonlinear photochemical conversion, and dose error compensation mechanisms. Specifically, this involves complete reconstruction of high-frequency details. The intensity distribution generated by frequency-domain coupling of a sub-pixel shifted light field and micromirrors, controlled by the timing of phase structure rotation, is then combined with the spatial superposition of multiple low-dose exposure frames to form a continuous dose distribution, ensuring that the high-frequency components of the target pattern are fully preserved during the cumulative exposure process. Diffraction-limited imaging is achieved by utilizing the nonlinear response of the photoresist threshold characteristics to the sub-pixel light field, converting the sub-threshold dose of discrete frames into a binary edge of the developed pattern. The effective resolution is determined by the dose gradient of the multi-frame superposition, surpassing the spatial bandwidth limitations of single-frame optical systems. Image fidelity is enhanced. Exposure redundancy introduced by phase structure rotation eliminates dose step errors caused by micromirror refreshes. Simultaneously, the spatial gradient control of the frequency-domain reconstructed light field suppresses dose diffusion during the development process, jointly ensuring pattern edge positioning accuracy and linewidth consistency.

[0103] In summary, this embodiment converts the computationally generated sub-pixel light field information into a physical pattern that meets the requirements of nanoscale size control through the triple mechanisms of spatiotemporal dose modulation, threshold response conversion, and system error compensation. Its core lies in leveraging the synergistic effect of optical modulation and photochemical properties to achieve lossless transfer from digital calculations to physical structures.

[0104] Example 9: Figure 5 As shown, based on Examples 1 to 8, the processing system for sparse compression reconstruction of LDI sub-pixel images provided by the embodiment of the present invention includes:

[0105] An image compression module is responsible for arranging at least two phase structures on at least one rotatable transparent glass slide. The rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micro-mirror. A low-resolution image to be exposed corresponding to each phase structure is pre-calculated using a computer image compression algorithm.

[0106] The pattern matching module is responsible for loading the calculated low-resolution exposure image into the digital micromirror in a timed manner. The display moment of each pattern matches the rotational position of the corresponding phase structure. The digital micromirror pattern is coupled to the phase encoding mask in the frequency domain through a 4-f optical system, and the diffraction effect is used to reconstruct the sub-pixel high-resolution exposure pattern.

[0107] The graphics formation module is responsible for projecting the high-resolution light field of the reconstructed high-resolution exposure pattern onto the photoresist surface, forming the target circuit pattern by accumulating exposure doses; after development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical graphics.

[0108] The working principle and beneficial effects of the above technical solution are as follows: the image compression module of this embodiment partitions at least two phase structures on at least one rotatable transparent glass slide, and the rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micromirror; a low-resolution image to be exposed corresponding to each phase structure is pre-calculated through a computer image compression algorithm; the pattern matching module loads the calculated low-resolution image to be exposed to the digital micromirror in a time sequence, and the display time of each pattern matches the rotation position of the corresponding phase structure; the pattern of the digital micromirror and the phase encoding mask are coupled in the frequency domain through a 4-f optical system, and a sub-pixel high-resolution exposure pattern is reconstructed using the diffraction effect; the pattern formation module projects the high-resolution light field of the reconstructed high-resolution exposure pattern onto the photoresist surface, and forms the target circuit pattern by accumulating the exposure dose; after development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical pattern. The phase structure of the above scheme and the spatiotemporal synchronization mechanism of the digital micromirrors establish a strict mapping relationship between the physical code and the computed image. Phase-locked control of the rotation frequency and refresh rate ensures that each phase window precisely matches the corresponding compressed image. A computer pre-calculation algorithm converts the static mask used in traditional photolithography into a dynamically programmable spatiotemporal code sequence. The 4-f system couples the digital micromirror array and phase mask in the frequency domain, leveraging the diffraction effect to overcome the inherent resolution limitations of the optical system. Frequency-domain modulation reconstructs discrete low-resolution image sequences into continuous sub-pixel exposure patterns, achieving coordinated optimization of the spatial sampling rate and optical transfer function. The cumulative exposure mechanism converts multiple frames of low-dose exposure in time into spatially high-resolution patterns. The threshold response characteristics of the photoresist convert the sub-pixel light field distribution into the physical edge morphology after development. Computational optics enables pattern transfer beyond the hardware resolution, forming a closed-loop conversion chain from digital bitstream to physical device.

[0109] In summary, this embodiment constitutes a complete technology chain for computational optical lithography. Through spatiotemporal modulation, it transforms the spatial resolution constraint in traditional lithography into a computable temporal-spatial joint optimization problem, achieving super-resolution manufacturing under hardware limitations.

[0110] In this embodiment, if the phase structure used is a binary structure of 0 and π, which is easy to manufacture, then the flat top light intensity of the exposure line will have a non-uniformity of <1.5%, such as Figure 6 As shown in the figure, since the photosensitive resin has a photosensitivity threshold, its exposure accuracy is determined by the light / no light contrast. Therefore, in practical applications, this unevenness will not affect the accuracy of the circuit board and can be fully applied to LDI to achieve sub-pixel resolution enhancement.

[0111] Example 10: Based on Examples 1 to 8, an application of the processing method for sparse compression reconstruction of LDI sub-pixel images provided in an embodiment of the present invention includes:

[0112] During the phase encoding design phase, four sets of orthogonal phase structures were configured on a rotating glass slide based on the wiring characteristics of the target circuit board. The phase structure rotation period was synchronized with the digital micromirror refresh rate at 120Hz. A compressed sensing algorithm was used to decompose the original Gerber file into eight sets of low-resolution mask patterns.

[0113] During the dynamic light field reconstruction phase, a digital micromirror rotates the compressed mask pattern at a μs refresh rate. A 4-f optical system couples the rotating phase structure with the digital micromirror pattern in the frequency domain. Through the diffraction effect, a sub-pixel light field with an equivalent 0.5 μm step is reconstructed.

[0114] During the circuit pattern transfer stage, the reconstructed light field forms cumulative exposure on the dry film photoresist surface, and an equivalent line width of 5μm is achieved through 16 sub-pixel shift exposures. After development, a precision circuit with a minimum line width / line spacing of 10μm / 10μm is obtained.

[0115] The working principles and beneficial effects of this technical solution are as follows: A breakthrough process enables 10μm-level circuit processing, compared to the 25μm limit of traditional LDI; exposure efficiency is tripled (multiple patterns can be exposed in a single rotation); cost-effectiveness is achieved by using low-resolution DMD devices for high-precision exposure, reducing laser power requirements (50mW can achieve the equivalent of 100mW); and production line adaptability is achieved, making it compatible with existing PCB dry process production lines and a direct replacement for traditional LDI optical modules.

[0116] This embodiment can be applied in IC substrate manufacturing to achieve 40 μm pitch micro bump array processing, complete 10-layer arbitrary interconnected silicon interposer manufacturing, and pattern RDL layer of wafer-level packaging (WLP).

[0117] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention's equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for sparse compression reconstruction of LDI sub-pixel images, characterized in that: The following steps are involved: At least two phase structures are arranged in zones on at least one rotatable transparent glass slide, and the rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micro-mirror; a low-resolution image to be exposed corresponding to each phase structure is pre-calculated using a computer image compression algorithm; The calculated low-resolution exposure image is loaded into the digital micromirror in a time-sequential manner, with the display moment of each pattern matching the rotational position of the corresponding phase structure. The digital micromirror pattern is coupled to the phase-encoding mask in the frequency domain through a 4-f optical system, and the diffraction effect is used to reconstruct the sub-pixel high-resolution exposure pattern. Projecting the high-resolution light field of the reconstructed high-resolution exposure pattern onto the photoresist surface, and forming a target circuit pattern by accumulating exposure dose; After development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical graphics.

2. The method for reconstructing LDI sub-pixel images by sparse compression according to claim 1, wherein: The process of pre-calculating a low-resolution image to be exposed corresponding to each phase structure includes the following steps: The optical transfer characteristics of each phase structure on the rotating transparent glass slide are quantified, and a corresponding relationship model between it and spatial frequency is established. Each phase structure is regarded as a separate frequency domain filter, and its rotation position forms a fixed mapping with a specific frequency band component. Based on the frequency domain characteristics of the phase structure, a set of overcomplete basis function libraries is generated. Each basis function corresponds to the modulation pattern of the phase structure on the incident light at a specific rotation angle. A sparse optimization algorithm is used to select the basis function combination that best represents the frequency domain characteristics of the target pattern. The target high-resolution image is decomposed into multiple sub-band components in the frequency domain. Matching pursuit is performed based on the obtained basis function library, and the frequency domain components that best match the modulation characteristics of the current phase structure are preferentially extracted. The remaining residual image is transferred to the matching process of the next phase structure, and the cycle is repeated until all phase structures are matched or the residual is lower than the set threshold. The decomposed frequency domain components are converted into low-resolution control instructions according to the following rules. Each component corresponds to a display frame of the digital micromirror. The frame display timing is strictly synchronized with the rotation phase of the phase structure. The frame content is converted into a realizable micromirror array state through deconvolution processing.

3. The method for reconstructing LDI sub-pixel images by sparse compression according to claim 2, wherein: The process of selecting the basis function combination that best represents the frequency domain characteristics of the target graph through the sparse optimization algorithm includes the following steps: Using the established correspondence model, the optical transfer characteristics at each rotation angle are converted into an N-dimensional eigenvector, where each dimension of the vector corresponds to the energy coupling coefficient at a specific spatial frequency. The eigenvectors of all phase structures at all rotational positions constitute the original basis function space, whose dimensions are consistent with the frequency domain decomposition depth of the target image. For the frequency domain subband components of the target image, the projection energy ratio of each basis function to the current subband component is calculated; a dynamic energy threshold function is set, whose independent variables include: the main frequency band weight of the correspondence model corresponding to the current rotation angle of the phase structure, and the cumulative frequency domain energy of the previous phase structure that has been matched. Only basis functions with a projection energy ratio exceeding the threshold are retained in the candidate set; Set dual constraints of forward constraint and reverse constraint on the candidate basis functions: use the screened basis functions as the initial population, perform frequency domain topology adjustment: the output basis function combination satisfies, and the joint frequency domain coverage of the combination reaches more than a preset percentage of the total energy of the target image.

4. The method for reconstructing an LDI sub-pixel image by sparse compression according to claim 3, wherein: For the forward constraint, the main lobe direction of the basis function must have an angle with the maximum modulation direction of the current phase structure that is less than the set tolerance; for the reverse constraint, the sidelobe energy distribution of the basis function must not have a spectrum overlap of more than 5% with the matched frequency domain component.

5. The method for processing sparse compression and reconstruction of LDI sub-pixel images according to claim 3, characterized in that: The process of setting the dynamic energy threshold function includes the following steps: Based on the established correspondence model, the main frequency band weight distribution under the current phase structure rotation angle is extracted to reflect the modulation efficiency advantage of a specific rotation angle on the target frequency band energy. The main frequency band weight is used as the basic adjustment factor of the threshold function, and the efficient basis function that best matches the current rotation angle is preferentially retained in the initial screening stage. The cumulative frequency domain energy distribution of the matched previous phase structure is introduced as a dynamic correction term of the threshold function, and the energy proportion of the covered frequency domain sub-bands is updated in real time. As the optimization progresses, the threshold function automatically improves the screening sensitivity of the remaining unmatched high-frequency or low-energy sub-bands. The projection energy ratio of the basis function and the current subband component is compared with the dynamic threshold. The main frequency band weight dominates the initial threshold value, and the basis function that is strongly correlated with the current rotation angle is given priority. The cumulative energy distribution dynamically lowers the threshold corresponding to the covered frequency band, forcing the algorithm to migrate to the unmatched frequency band. Only when the projection energy ratio of the basis function satisfies both constraints at the same time, it enters the candidate set.

6. The method for reconstructing LDI sub-pixel images by sparse compression according to claim 1, wherein: The process of reconstructing a sub-pixel high-resolution exposure pattern using diffraction effects includes the following steps: The synchronous frequency timing of phase structure rotation and micromirror refresh is obtained. Each phase structure activates the corresponding pre-calculated low-resolution image to be exposed at a specific rotation angle. The spatial distribution characteristics of the phase structure and the micromirror pattern are conjugated on the object plane of the 4-f system, forming a joint space-frequency modulation unit. The modulated light field is decomposed into the frequency domain using the Fourier transform characteristics of the 4-f system. Each phase structure rotation position corresponds to a set of characteristic basis functions, whose main lobe direction is uniquely determined by the current rotation angle. The frequency domain components of the micromirror pattern are projected and matched with the phase structure basis functions, retaining only the basis function components whose projection energy exceeds the dynamic threshold. The filtered frequency domain components are inversely transformed to the image plane through the 4-f system. The basis function groups activated at different rotation angles form multiple low-resolution light fields with sub-pixel phase differences on the image plane. They are incoherently superimposed through the diffraction effect within the exposure time. The superposition result is equivalent to the frequency domain interpolation reconstruction of the target high-resolution image.

7. The method for reconstructing LDI sub-pixel images by sparse compression according to claim 6, wherein: The discrete phase delay generated by the partitioned layout of the phase structure in the space-frequency joint modulation unit directionally diffracts the incident light field; the binary amplitude modulation of the micro-mirror pattern and the phase delay field realize complex multiplication coupling in the frequency domain.

8. The method for reconstructing LDI sub-pixel images by sparse compression according to claim 1, wherein: The process of projecting the frequency domain components of the micro-mirror pattern with the phase structure basis function includes the following steps: The modulated light field is decomposed into the frequency domain. The phase structure rotation angle locks the main lobe direction characteristics of the basis function. The basis function corresponding to each rotation angle comes from the established space-frequency joint modulation unit and the spatial distribution of the phase structure is converted into a frequency domain eigenvector via a 4-f system. The frequency domain components of the micro-mirror pattern are selected through dynamic energy gating. When the phase structure is rotated to a predetermined angle, the generated basis function main lobe scans the frequency domain components of the micro-mirror pattern like a probe. A projection energy threshold is used as the matching criterion: the basis function is activated only when the frequency domain energy covered by the basis function main lobe exceeds the set dynamic threshold. The retained basis function components carry dual information, including both the rotation parameters of the phase structure and the local frequency domain characteristics of the micromirror pattern. During the inverse transformation, they spontaneously reconstruct a low-resolution light field with a specific phase difference.

9. A processing system for sparse compression reconstruction of LDI sub-pixel images, characterized in that: Include: An image compression module is responsible for setting at least two phase structures in partitions on at least one rotatable transparent glass slide, wherein the rotation frequency of the transparent glass slide is synchronized with the pattern refresh frequency of the digital micro-mirror; A low-resolution image to be exposed corresponding to each phase structure is pre-calculated by a computer image compression algorithm; The pattern matching module is responsible for loading the calculated low-resolution exposure image into the digital micromirror in a timed manner. The display moment of each pattern matches the rotational position of the corresponding phase structure. The digital micromirror pattern is coupled to the phase encoding mask in the frequency domain through a 4-f optical system, and the diffraction effect is used to reconstruct the sub-pixel high-resolution exposure pattern. The pattern formation module is responsible for projecting the high-resolution light field of the reconstructed high-resolution exposure pattern onto the photoresist surface and forming the target circuit pattern by accumulating the exposure dose; After development, a micro-nano structure with sub-pixel precision is obtained, completing the full process conversion from calculation to physical graphics.

10. An application of a processing method for sparse compression reconstruction of LDI sub-pixel images, characterized in that: It includes: phase encoding design stage, dynamic light field reconstruction stage and circuit pattern transfer stage.

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