Mask optimization design method and device, electronic equipment and storage medium

Abstract

The application relates to a mask optimization design method and device, electronic equipment and a storage medium. The method comprises the following steps: based on an optical diffraction propagation model, simulating an optical field acquisition process of a to-be-designed mask, and obtaining a simulation result of a sampling matrix; performing performance evaluation on the simulation result according to a preset matrix evaluation strategy, obtaining a performance evaluation result of the sampling matrix, and determining a first optimal design mask arranged before and after a microlens array, including the microlens array and before an image sensor, and / or a second optimal design mask arranged before and after a main imaging system, including a main imaging lens and before the microlens array. Therefore, the problems of a large number of scanning times and low imaging efficiency when a scanning light field imaging increases a relative displacement between a camera lens and a microlens array to realize high-resolution light field acquisition and improve light field image quality and resolution are solved. Through the optimization strategy of the embodiment, the number of scanning times is reduced, and the system imaging reconstruction quality and stability are improved.

Description

Technical Field

[0001] This application relates to the field of computational imaging technology, and in particular to a mask optimization design method, apparatus, electronic device, and storage medium. Background Technology

[0002] In recent years, with the improvement of computing power, computational light field imaging technology has developed rapidly. Among related technologies, light field mainly focuses on the distribution function of light rays as position and angle. Benefiting from the space-viewpoint dimension assumption and the advancement of software and hardware technology, light field imaging can now be achieved by portable commercial devices, and can even be integrated into mobile phones.

[0003] The widespread use of light field cameras enables several new applications, including initial light field rendering based on realistic images and current computer vision applications utilizing light field encoded information, such as 3D reconstruction, segmentation, saliency detection, object detection and recognition, tracking, and video stabilization. Given the enormous potential of light field applications and the remaining technical challenges, light field technology has attracted widespread attention from research teams both domestically and internationally.

[0004] The acquisition of 4D light field information mainly involves encoding the 4D light field onto a 2D sensor plane by multiplexing the angular domain to the spatial (or frequency) domain. The light field acquisition device is called a "light field chip," which primarily uses microlens arrays or small lens arrays mounted on an image sensor. Light field cameras can acquire 4D light field information in both space and angle through a single exposure, but light field chips face an inherent contradiction between spatial and angular resolution. On the one hand, light field acquisition devices using the microlens array principle (such as Lytro Illume and Raytrix) acquire high angular resolution light field images by directly dispersing light rays from various angles onto the imaging unit. However, limited by the resolution of the imaging unit, their spatial resolution is often much smaller than that of commonly used imaging devices (SLR cameras, mobile phones, etc.). On the other hand, such as... Figure 1 As shown, while camera array systems can control the spatial resolution of the light field by changing the resolution of each camera, their angular resolution is far from meeting the requirements of real-time light field rendering due to limitations such as camera physical space, system complexity, and overall cost. Many people skilled in the art have focused on super-resolution light fields within the spatial / angular range, doing a great deal of work on light field reconstruction and providing a theoretical basis for light field information processing.

[0005] Scanning light field imaging achieves high-resolution light field acquisition by increasing the relative displacement between the camera lens and the microlens array, thereby improving the image quality and resolution of the light field. However, existing scanning imaging methods suffer from problems such as numerous scans, low imaging efficiency, and spectral aliasing during acquisition leading to information loss and degraded image quality. Summary of the Invention

[0006] This application provides a mask optimization design method, apparatus, electronic device, and storage medium to solve the problem of high scanning number and low imaging efficiency when increasing the relative displacement between the camera lens and the microlens array to achieve high-resolution light field acquisition in order to improve the quality and resolution of the light field image.

[0007] The first aspect of this application provides a mask optimization design method, including the following steps:

[0008] Based on the optical diffraction propagation model, the light field acquisition process of the mask to be designed is simulated, and the simulation results of the sampling matrix are obtained, wherein the sampling matrix is ​​obtained by simulating the mask to be designed;

[0009] The simulation results are evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation result of the sampling matrix; and

[0010] Based on the performance evaluation results of the sampling matrix, a first optimal design mask is determined to be placed before and after the microlens array, including on the microlens array and before the image sensor, and / or a second optimal design mask is determined to be placed before and after the main imaging system, including on the main imaging lens and before the microlens array.

[0011] According to one embodiment of this application, determining the first optimal design mask before and after the microlens array, including the mask on the microlens array and before the image sensor, and / or the second optimal design mask before and after the main imaging system, including the mask on the main imaging lens and before the microlens array, includes:

[0012] The mask to be designed is optimized based on a preset optimization algorithm;

[0013] The optimized mask is used as the mask to be designed until the target evaluation index is met;

[0014] The first optimal design mask, including the area before and after the microlens array and before the image sensor, and / or the second optimal design mask, including the area near the main imaging system and before the microlens array, are determined based on the design mask that meets the target evaluation index.

[0015] According to one embodiment of this application, the target evaluation index is that the condition number of the sampling matrix meets a preset requirement.

[0016] According to one embodiment of this application, the preset optimization algorithm includes at least one of a search optimization algorithm, a gradient descent optimization algorithm, an alternating optimization strategy, and an exhaustive search strategy.

[0017] According to one embodiment of this application, the mask to be designed is a binary mask or a grayscale transformation mask.

[0018] According to one embodiment of this application, the pattern of the binary mask and the pattern of the grayscale transformation mask are at least one of symmetrical and asymmetrical, circular, rectangular and various regular and irregular shapes.

[0019] According to one embodiment of this application, the binary mask has a value of 0 or 1, and the grayscale transformation mask has a grayscale value in the interval [0,1].

[0020] According to the mask optimization design method of this application embodiment, based on the optical diffraction propagation model, the light field acquisition process of the mask to be designed is simulated, and the simulation results of the sampling matrix are obtained. The simulation results are then evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation results of the sampling matrix. This determines the first optimal design mask placed before and after the microlens array (including on the microlens array and before the image sensor) and / or the second optimal design mask placed before and after the main imaging system (including on the main imaging lens and before the microlens array). This solves the problems of high scanning times and low imaging efficiency when increasing relative displacement between the camera lens and the microlens array to achieve high-resolution light field acquisition and improve the quality and resolution of the light field image in scanning light field imaging. By jointly optimizing the mask shapes between the microlens array and the main lens, and between the microlens array and the image sensor, the number of scans is reduced, and the imaging reconstruction quality and stability of the system are improved.

[0021] A second aspect of this application provides a mask optimization design apparatus, comprising:

[0022] The simulation module is used to simulate the light field acquisition process of the mask to be designed based on the optical diffraction propagation model, and to obtain the simulation result of the sampling matrix, wherein the sampling matrix is ​​obtained by simulating the mask to be designed;

[0023] The evaluation module is used to evaluate the performance of the simulation results according to a preset matrix evaluation strategy, and obtain the performance evaluation result of the sampling matrix; and

[0024] The determination module is used to determine, based on the performance evaluation results of the sampling matrix, a first optimal design mask set before and after the microlens array, including on the microlens array and in front of the image sensor, and / or a second optimal design mask near the main imaging system, including on the main imaging lens and in front of the microlens array.

[0025] According to one embodiment of this application, the determining module is specifically used for:

[0026] The mask to be designed is optimized based on a preset optimization algorithm;

[0027] The optimized mask is used as the mask to be designed until the target evaluation index is met;

[0028] The first optimal design mask, including the area before and after the microlens array and before the image sensor, and / or the second optimal design mask, including the area near the main imaging system and before the microlens array, are determined based on the design mask that meets the target evaluation index.

[0029] According to one embodiment of this application, the target evaluation index is that the condition number of the sampling matrix meets a preset requirement.

[0030] According to one embodiment of this application, the preset optimization algorithm includes at least one of a search optimization algorithm, a gradient descent optimization algorithm, an alternating optimization strategy, and an exhaustive search strategy.

[0031] According to one embodiment of this application, the mask to be designed is a binary mask or a grayscale transformation mask.

[0032] According to one embodiment of this application, the pattern of the binary mask and the pattern of the grayscale transformation mask are at least one of symmetrical and asymmetrical, circular, rectangular and various regular and irregular shapes.

[0033] According to one embodiment of this application, the binary mask has a value of 0 or 1, and the grayscale transformation mask has a grayscale value in the interval [0,1].

[0034] According to the mask optimization design apparatus of this application embodiment, based on an optical diffraction propagation model, the light field acquisition process of the mask to be designed is simulated, and the simulation results of the sampling matrix are obtained. The simulation results are then evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation results of the sampling matrix, thereby determining the first optimal design mask between the microlens array and the image sensor, and / or the second optimal design mask between the main lens and the microlens array. This solves the problems of high scanning count and low imaging efficiency when increasing relative displacement between the camera lens and the sensor to improve the quality and resolution of the light field image in scanning light field imaging. By jointly optimizing the mask shapes between the microlens array and the main lens, and between the microlens array and the image sensor, the number of scans is reduced, and the system imaging efficiency and stability are improved.

[0035] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the mask optimization design method as described in the above embodiments.

[0036] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the mask optimization design method as described in the above embodiments.

[0037] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0038] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0039] Figure 1 A schematic diagram of a camera array optical field mask system in related technologies;

[0040] Figure 2 This is a flowchart of a mask optimization design method provided according to an embodiment of this application;

[0041] Figure 3 This is an overall scheme for optimizing the design of a microlens array-optical lens combination mask according to an embodiment of this application;

[0042] Figure 4 This is an example diagram of a mask optimization design apparatus provided according to an embodiment of this application;

[0043] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0044] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0045] The mask optimization design method, apparatus, electronic device, and storage medium of this application are described below with reference to the accompanying drawings. Addressing the problem mentioned in the background art of scanning light field imaging systems where increasing relative displacement between the camera lens and sensor to achieve high-resolution light field acquisition and improve light field image quality and resolution results in numerous scans and low imaging efficiency, this application provides a mask optimization design method. In this method, based on an optical diffraction propagation model, the light field acquisition process of adding the mask to be designed is simulated, and the simulation results of the sampling matrix are obtained. The simulation results are then evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation results of the sampling matrix. This determines a first optimal design mask placed before and after the microlens array (including on the microlens array and before the image sensor) and / or a second optimal design mask placed before and after the main imaging system (including on the main imaging lens and before the microlens array). This solves the problems of high scanning number and low imaging efficiency when increasing the relative displacement between the camera lens and the sensor to achieve high-resolution light field acquisition and improve the quality and resolution of light field images. By jointly optimizing the mask shape between the microlens array and the main lens, as well as between the microlens array and the image sensor, the number of scanning is reduced and the imaging reconstruction quality and stability of the system are improved.

[0046] Specifically, Figure 2 This is a flowchart illustrating a mask optimization design method provided in an embodiment of this application.

[0047] like Figure 2 As shown, the mask optimization design method includes the following steps:

[0048] In step S201, based on the optical diffraction propagation model, the light field acquisition process of the mask to be designed is simulated, and the simulation result of the sampling matrix is ​​obtained, wherein the sampling matrix is ​​obtained by simulating the mask to be designed.

[0049] Specifically, based on the optical diffraction propagation model, the simulation of the light field acquisition process with the mask to be designed can be carried out in many ways. For example, the mask to be designed can be placed between the microlens array and the image sensor (such as a CMOS sensor); or the mask to be designed can be placed between the main lens and the microlens array, as well as between the microlens array and the image sensor, so as to obtain the simulation results of the sampling matrix.

[0050] Optionally, in some embodiments, the mask to be designed can be a binary mask or a grayscale transformation mask. The pattern of the binary mask and the pattern of the grayscale transformation mask are at least one of symmetrical and asymmetrical, circular, rectangular and various regular and irregular shapes. The value of the binary mask is 0 or 1, and the value of the grayscale transformation mask is a grayscale value in the interval [0,1].

[0051] It should be understood that the embodiments of this application can be designed according to actual needs, including the type, shape, pattern, and value of the mask to be designed. No specific limitations are made here. By setting the type of the mask to be designed and selecting the pattern, shape, and value of the mask to be designed, the clarity and reliability of the image can be effectively improved.

[0052] In step S202, the simulation results are evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation results of the sampling matrix.

[0053] In step S203, based on the performance evaluation results of the sampling matrix, a first optimal design mask is determined to be set before and after the microlens array, including on the microlens array and before the image sensor, and / or a second optimal design mask is determined before and after the main imaging system, including on the main imaging lens and before the microlens array.

[0054] Further, in some embodiments, determining a first optimal design mask disposed before and after the microlens array, including on the microlens array and before the image sensor, and / or a second optimal design mask disposed before and after the main imaging system, including on the main imaging lens and before the microlens array, includes: optimizing the mask to be designed based on a preset optimization algorithm; using the optimized mask as the mask to be designed until the target evaluation index is met; and determining the first optimal design mask before and after the microlens array, including on the microlens array and before the image sensor, and / or the second optimal design mask before and after the main imaging system, including on the main imaging lens and before the microlens array, based on the mask to be designed that meets the target evaluation index.

[0055] Furthermore, in some embodiments, the target evaluation metric is that the condition number of the sampling matrix meets a preset requirement.

[0056] Specifically, such as Figure 3 As shown, this embodiment of the application uses the simulation results of the obtained sampling matrix to perform performance evaluation on the simulation results to determine whether the sampling matrix meets the given evaluation index. The performance evaluation of the obtained sampling matrix can be performed by presetting the condition number of the sampling matrix or other evaluation strategies to assess the stability of the sampling matrix, thereby obtaining the evaluation result.

[0057] Furthermore, in this embodiment, based on the performance evaluation results of the sampling matrix described above, the mask can be optimized by employing at least one of the following preset optimization algorithms: search optimization algorithm, gradient descent optimization algorithm, alternating optimization strategy, and exhaustive search strategy. The optimized mask can then be used as the first optimal design mask and / or the second optimal design mask to obtain the optimal sampling strategy. This reduces sampling consumption, lowers the number of scans in the system while ensuring imaging quality, and improves the imaging efficiency and stability of the system.

[0058] It should be noted that if the performance of the sampling matrix fails to meet the given evaluation criteria (such as failing to meet the condition number of the sampling matrix) after the optimization process is completed, the optimization will continue until the target evaluation criteria are met.

[0059] According to the mask optimization design method of this application embodiment, based on the optical diffraction propagation model, the light field acquisition process of the mask to be designed is simulated, and the simulation results of the sampling matrix are obtained. The simulation results are then evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation results of the sampling matrix. This determines the first optimal design mask placed before and after the microlens array (including on the microlens array and before the image sensor) and / or the second optimal design mask placed before and after the main imaging system (including on the main imaging lens and before the microlens array). This solves the problems of high scanning times and low imaging efficiency when increasing relative displacement between the camera lens and sensor to achieve high-resolution light field acquisition and improve the quality and resolution of the light field image in scanning light field imaging. By jointly optimizing the mask shapes between the microlens array and the main lens, and between the microlens array and the image sensor, the number of scanning times is reduced, and the imaging reconstruction quality and stability of the system are improved.

[0060] Next, the mask optimization design apparatus proposed according to the embodiments of this application is described with reference to the accompanying drawings.

[0061] Figure 4 This is a block diagram of a mask optimization design device according to an embodiment of this application.

[0062] like Figure 4 As shown, the mask optimization design device 10 includes: a simulation module 100, an evaluation module 200, and a determination module.

[0063] The simulation module 100 is used to simulate the light field acquisition process of the mask to be designed based on the optical diffraction propagation model, and to obtain the simulation result of the sampling matrix, wherein the sampling matrix is ​​obtained by simulating the mask to be designed.

[0064] The evaluation module 200 is used to evaluate the performance of the simulation results according to a preset matrix evaluation strategy, and obtain the performance evaluation results of the sampling matrix; and

[0065] The determination module 300 is used to determine, based on the performance evaluation results of the sampling matrix, a first optimal design mask set before and after the microlens array, including on the microlens array and before the image sensor, and / or a second optimal design mask set before and after the main imaging system, including on the main imaging lens and before the microlens array.

[0066] Furthermore, in some embodiments, the determining module 300 is specifically used for:

[0067] The mask to be designed is optimized based on a preset optimization algorithm;

[0068] The optimized mask is used as the mask to be designed until the target evaluation index is met;

[0069] Based on the mask to be designed that meets the target evaluation index, determine the first optimal design mask before and after the microlens array, including the microlens array and before the image sensor, and / or the second optimal design mask before and after the main imaging system, including the main imaging lens and before the microlens array.

[0070] Furthermore, in some embodiments, the target evaluation metric is that the condition number of the sampling matrix meets a preset requirement.

[0071] Furthermore, in some embodiments, the preset optimization algorithm includes at least one of a search optimization algorithm, a gradient descent optimization algorithm, an alternating optimization strategy, and an exhaustive search strategy.

[0072] Furthermore, in some embodiments, the mask to be designed is a binary mask or a grayscale transformation mask.

[0073] Furthermore, in some embodiments, the patterns of the binary mask and the grayscale transformation mask are at least one of symmetrical and asymmetrical, circular, rectangular, and various regular and irregular shapes.

[0074] Furthermore, in some embodiments, the binary mask is 0 or 1, and the grayscale transformation mask is a grayscale value in the interval [0,1].

[0075] According to the mask optimization design apparatus of this application embodiment, based on an optical diffraction propagation model, the light field acquisition process of adding a mask to be designed is simulated, and the simulation results of the sampling matrix are obtained. The simulation results are then evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation results of the sampling matrix. This determines a first optimal design mask placed before and after the microlens array (including on the microlens array and before the image sensor) and / or a second optimal design mask placed before and after the main imaging system (including on the main imaging lens and before the microlens array). This solves the problems of high scanning times and low imaging efficiency when increasing relative displacement between the camera lens and sensor to achieve high-resolution light field acquisition and improve light field image quality and resolution in scanning light field imaging. By jointly optimizing the mask shapes between the microlens array and the main lens, and between the microlens array and the image sensor, the number of scanning times is reduced, and the system's imaging reconstruction quality and stability are improved.

[0076] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0077] The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0078] When the processor 502 executes the program, it implements the mask optimization design method provided in the above embodiments.

[0079] Furthermore, electronic devices also include:

[0080] Communication interface 503 is used for communication between memory 501 and processor 502.

[0081] The memory 501 is used to store computer programs that can run on the processor 502.

[0082] The memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0083] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0084] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0085] Processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0086] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the mask optimization design method described above.

[0087] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0088] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0089] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0090] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0091] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0092] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.

[0093] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0094] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A mask optimization design method, characterized in that, Includes the following steps: Based on the optical diffraction propagation model, the light field acquisition process of the mask to be designed is simulated, and the simulation results of the sampling matrix are obtained, wherein the sampling matrix is ​​obtained by simulating the mask to be designed; The simulation results are evaluated according to a preset matrix evaluation strategy to obtain the performance evaluation result of the sampling matrix; and Based on the performance evaluation results of the sampling matrix, a first optimal design mask is determined to be placed before and after the microlens array, including on the microlens array and before the image sensor, and / or a second optimal design mask is determined before and after the main imaging system, including on the main imaging lens and before the microlens array; the number of scans of the system is reduced while ensuring imaging quality. The determination of the first optimal design mask before and after the microlens array, including the mask on the microlens array and before the image sensor, and / or the second optimal design mask before and after the main imaging system, including the mask on the main imaging lens and before the microlens array, includes: The mask to be designed is optimized based on a preset optimization algorithm; the preset optimization algorithm includes at least one of a search optimization algorithm, a gradient descent optimization algorithm, an alternating optimization strategy, and an exhaustive search strategy. The optimized mask is used as the mask to be designed until the target evaluation index is met; Based on the mask to be designed that meets the target evaluation index, determine the first optimal design mask before and after the microlens array, including the microlens array and before the image sensor, and / or the second optimal design mask near the main imaging system, including the main imaging lens and before the microlens array; The target evaluation index is that the condition number of the sampling matrix meets the preset requirements.

2. The method according to claim 1, characterized in that, The mask to be designed is a binary mask or a grayscale transformation mask.

3. The method according to claim 2, characterized in that, The patterns of the binary mask and the grayscale transformation mask are at least one of symmetrical and asymmetrical, circular, rectangular, and various regular and irregular shapes.

4. The method according to claim 3, characterized in that, The binary mask has a value of 0 or 1, and the grayscale transformation mask has a grayscale value in the interval [0,1].

5. A mask optimization design device, characterized in that, include: The simulation module is used to simulate the light field acquisition process of the mask to be designed based on the optical diffraction propagation model, and to obtain the simulation result of the sampling matrix, wherein the sampling matrix is ​​obtained by simulating the mask to be designed; The evaluation module is used to evaluate the performance of the simulation results according to a preset matrix evaluation strategy, and obtain the performance evaluation result of the sampling matrix; and The determination module is used to determine, based on the performance evaluation results of the sampling matrix, a first optimal design mask placed before and after the microlens array, including on the microlens array and before the image sensor, and / or a second optimal design mask near the main imaging system, including on the main imaging lens and before the microlens array; to reduce the number of scans of the system while ensuring imaging quality. The determining module is specifically used for: The mask to be designed is optimized based on a preset optimization algorithm; the preset optimization algorithm includes at least one of a search optimization algorithm, a gradient descent optimization algorithm, an alternating optimization strategy, and an exhaustive search strategy. The optimized mask is used as the mask to be designed until the target evaluation index is met; Based on the mask to be designed that meets the target evaluation index, determine the first optimal design mask before and after the microlens array, including the microlens array and before the image sensor, and / or the second optimal design mask near the main imaging system, including the main imaging lens and before the microlens array; The target evaluation index is that the condition number of the sampling matrix meets the preset requirements.

6. The apparatus according to claim 5, characterized in that, The mask to be designed is a binary mask or a grayscale transformation mask.

7. The apparatus according to claim 6, characterized in that, The patterns of the binary mask and the grayscale transformation mask are at least one of symmetrical and asymmetrical, circular, rectangular, and various regular and irregular shapes.

8. The apparatus according to claim 7, characterized in that, The binary mask has a value of 0 or 1, and the grayscale transformation mask has a grayscale value in the interval [0,1].

9. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the mask optimization design method as described in any one of claims 1-4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the mask optimization design method as described in any one of claims 1-4.

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