Photon integrated interference imaging system baseline pairing optimization method and device based on genetic algorithm

Abstract

The invention discloses a photon integrated interference imaging system baseline pairing optimization method and device based on a genetic algorithm, and belongs to the technical field of photon integrated interference imaging. The method comprises the following steps: giving a micro-lens array arrangement mode of the photon integrated interference imaging system; initializing an interference baseline pairing mode of the microlens array according to a limiting condition; performing frequency spectrum sampling on the target by using the paired micro lenses to obtain a target mutual intensity spectrum; inverse Fourier transform is carried out on the target mutual intensity to obtain an airspace reconstruction image; obtaining a PSNR value of the spatial domain reconstruction image, and constructing a target function of an imaging system; the objective function is used as an optimization index, and a genetic algorithm is used to optimize the microlens interference baseline pairing mode; and taking the interference baseline pairing mode corresponding to the maximum value of the target function as the optimal baseline pairing mode of the photon integrated interference imaging system. According to the method, the genetic algorithm is utilized, the baseline pairing mode can be quickly optimized, and the imaging quality of the system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of photon integrated interference imaging, and particularly relates to a method and device for optimizing baseline pairing of a photon integrated interference imaging system based on a genetic algorithm. Background Art

[0002] High-resolution imaging technology has an urgent need in many fields such as military reconnaissance, resource exploration, and environmental monitoring. According to the Rayleigh resolution criterion, (where is the angular resolution of the camera, is the incident wavelength, is the camera aperture), increasing the system aperture can effectively improve the resolution. However, limited by factors such as materials and processes, it is difficult to machine a single mirror with an ultra-large aperture, the support structure is complex, and the load volume and mass of a large-aperture system increase, which brings difficulties to the launch of a space-based optical system. To solve these problems, the prior art has proposed a new photon integrated interference imaging technology, which combines the synthetic aperture imaging technology and the photon integrated circuit technology. The target light information is collected through a large-scale microlens array, and phase adjustment, beam interference, signal detection, etc. are realized in the photon integrated circuit. By analyzing the amplitude and phase of the interference image and through image reconstruction, a high-resolution image can be obtained, which can greatly reduce the size, mass, power consumption (by 10 to 100 times) and development cycle of the optical system. The arrangement method and baseline pairing method of the microlens array at the front end of the system directly affect the UV spectrum coverage of the system, and thus affect the imaging quality. At present, most of the research mainly focuses on the optimization of the microlens arrangement method, and there is less research on the baseline pairing method. Summary of the Invention

[0003] To solve the above technical problems, the present invention adopts the following technical solutions:

[0004] A method for optimizing baseline pairing of a photon integrated interference imaging system based on a genetic algorithm, comprising the following steps:

[0005] S1: Given the arrangement method of the microlens array of the photon integrated interference imaging system;

[0006] S2: Initialize the interference baseline pairing method of the microlens array according to the constraint conditions;

[0007] S3: Use pairwise paired microlenses to sample the spectrum of the target to obtain the mutual intensity spectrum of the target;

[0008] S4: Perform an inverse Fourier transform on the mutual coherence intensity of the target to obtain a spatial domain reconstructed image;

[0009] S5: Calculate the peak signal-to-noise ratio of the spatial domain reconstructed image and construct the objective function of the photon integrated interference imaging system;

[0010] S6: Take the objective function obtained in step S5 as the optimization index, and use the genetic algorithm to optimize the interference baseline pairing method of the microlens.

[0011] S7: Take the interference baseline pairing method corresponding to the maximum value of the objective function as the optimal baseline pairing method of the photon integrated interference imaging system.

[0012] A device for optimizing the baseline pairing of a photon integrated interference imaging system based on the genetic algorithm, comprising:

[0013] A microlens array arrangement method given module for giving the microlens array arrangement method of the photon integrated interference imaging system;

[0014] An initialization module for initializing the interference baseline pairing method of the microlens array according to the constraint conditions;

[0015] A target mutual intensity spectrum acquisition module for performing spectral sampling on the target using pairwise paired microlenses to obtain the target mutual intensity spectrum;

[0016] An airspace reconstruction image acquisition module for performing an inverse Fourier transform on the mutual coherence intensity of the target to obtain an airspace reconstruction image;

[0017] A target function construction module for calculating the peak signal-to-noise ratio of the airspace reconstruction image and constructing the target function of the photon integrated interference imaging system;

[0018] An optimization module for taking the objective function obtained by the target function construction module as the optimization index and using the genetic algorithm to optimize the interference baseline pairing method of the microlens;

[0019] An optimal baseline pairing method acquisition module for taking the interference baseline pairing method corresponding to the maximum value of the objective function as the optimal baseline pairing method of the photon integrated interference imaging system.

[0020] An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for optimizing the baseline pairing of a photon integrated interference imaging system based on the genetic algorithm are implemented.

[0021] A non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method for optimizing the baseline pairing of a photon integrated interference imaging system based on the genetic algorithm are implemented.

[0022] The present invention has the following beneficial effects:

[0023] The present invention can optimize the baseline pairing method according to the target, achieve precise UV spectrum coverage, and effectively improve the imaging quality of the system. By using the PSNR of the reconstructed image as the evaluation index of the objective function, the present invention quickly optimizes the baseline pairing method of the system's microlens array according to the characteristics of the target image, realizing the improvement of the system's imaging quality without increasing the manufacturing difficulty, cost, and volume of the system, avoiding the problem of excessive time caused by manually searching for the baseline pairing method, and providing effective technical guidance for the further development of the photon integrated interference imaging system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic flow chart of the baseline pairing optimization method for the photon integrated interference imaging system based on the genetic algorithm of the present invention;

[0025] Figure 2 It is a schematic diagram of the arrangement form of the wavy microlens array according to an embodiment of the present invention;

[0026] Figure 3 It is a schematic flow chart of the genetic algorithm according to an embodiment of the present invention;

[0027] Figure 4 It is a UV spectrum sampling diagram obtained by initializing the uniform baseline pairing method of the microlens array according to an embodiment of the present invention;

[0028] Figure 5 It is a UV spectrum sampling diagram obtained after optimizing the baseline pairing method by the genetic algorithm according to an embodiment of the present invention;

[0029] Figure 6 It is a reconstructed image obtained by initializing the uniform baseline pairing method of the microlens array according to an embodiment of the present invention;

[0030] Figure 7 It is a reconstructed image obtained after optimizing the baseline pairing method by the genetic algorithm according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] As Figure 1 shown, it is the baseline pairing optimization method for the photon integrated interference imaging system based on the genetic algorithm of the present invention, which specifically includes the following steps:

[0033] S1: Given the arrangement mode of the microlens array of the photon integrated interference imaging system;

[0034] In step S1, for the wavy microlens array (the wavy microlens array is only an example, and other arranged microlens arrays can also be set), the horizontal and vertical coordinates of the center of the th microlens on the th interference arm are expressed as:

[0035] ;

[0036] Among them, is the horizontal coordinate of the center of the microlens, is the vertical coordinate of the center of the microlens, is the distance of the center point of the th lens on each interference arm relative to the origin of the photon integrated interference imaging system, is the th interference arm, and is the phase of the center of the

[0037] S2: Initialize the interference baseline pairing mode of the microlens array according to the constraint conditions;

[0038] Step S2 specifically includes:

[0039] S21: Set the constraint conditions as needed. The constraint conditions set in the present invention are as follows: The entire microlens array is composed of 37 (this number is only an example, and other numbers can also be used) identical interference arms around the same center. Each interference arm is composed of 100 (this number is only an example, and other numbers can also be used) microlenses. The pairing mode of the interference baselines is the same. Therefore, only the pairing mode of the microlenses on a single interference arm needs to be optimized, and each lens can only be paired once. The first microlens on the interference arm must be paired with the last microlens to ensure that the longest baseline length is the same in different baseline pairing modes;

[0040] S22: Initialize the interference baseline pairing mode of the microlens array according to the above constraint conditions.

[0041] S3: Use the pairwise paired microlenses to perform spectral sampling on the target to obtain the mutual intensity spectrum of the target;

[0042] Step S3 specifically includes:

[0043] S31: The pairwise paired microlenses on the same interference arm determine the distribution of the system spatial frequency points , which is expressed as:

[0044] ;

[0045] Among them, , is the The interference baseline formed by the th microlens on one interference arm and the th microlens on the th interference arm, is the jth imaging wavelength of the system, is the detection distance, is the horizontal coordinate of the center of the mth microlens on the jth interference arm, is the horizontal coordinate of the center of the nth microlens on the jth interference arm, is the vertical coordinate of the center of the mth microlens on the jth interference arm, is the vertical coordinate of the center of the nth microlens on the jth interference arm.

[0046] S32: Use the system spatial frequency points obtained in the above step S31 as the ideal mutual intensity spectrum sample to obtain the actually detected mutual intensity spectrum. The mutual coherence intensity of the target is:

[0047] ;

[0048] where, is the mutual coherence intensity of the target, is the light intensity of the target.

[0049] S4: Perform an inverse Fourier transform on the mutual coherence intensity of the target to obtain the spatial domain reconstructed image;

[0050] In step S4, the calculation formula for the spatial domain reconstructed image is:

[0051] ;

[0052] where, is the actually obtained mutual coherence intensity spectrum, is the expression symbol of the inverse Fourier transform.

[0053] S5: Calculate the peak signal-to-noise ratio (PSNR) value of the obtained spatial domain reconstructed image and construct the objective function of the photon integrated interference imaging system;

[0054] In step S5, the expression of the objective function is:

[0055] ;

[0056] where, is the peak signal-to-noise ratio, is the maximum pixel value of the reconstructed image, is an intermediate quantity, is the spatial domain reconstructed image, and For reconstructing the height and width of the image.

[0057] S6: Taking the objective function obtained in step S5 as the optimization index, optimize the pairing method of the micro-lens interference baselines by using the genetic algorithm;

[0058] In step S6, the specific solution steps of the genetic algorithm include:

[0059] S61: Initialization of the population: Set the evolution generation counter t = 0, set the maximum number of evolution generations T, and randomly generate M individuals, X1, X2, …… X M , as the initial population P(0).

[0060] S62: Calculate the fitness function: Use the objective function in step S5 as the fitness function, and calculate the fitness function of each individual in the population P(t) . After all the fitness functions are completed, calculate the probability of the fitness values of all individuals:

[0061] ; ( represents the i-th individual).

[0062] S63: Selection operation: According to the probabilities of the fitness values calculated in step S62, accumulate them into a probability table for constructing a "probability roulette wheel"; generate a random number for each parent position, and determine the selected individual according to the probability interval where the random number falls, and form the parent population with them.

[0063] S64: Crossover operation: Under the condition of satisfying the constraints of S21, determine whether to perform crossover on the parent individuals in the population with a certain crossover probability (the crossover probability can usually be selected between 0.8 and 0.99). If crossover is performed, randomly select a crossover point between the genes, and segmentally crossover the genes of the two parents , before and after the crossover point to generate two offspring , .

[0064] S65: Mutation operation: Calculate the fitness function of all new individuals, and combine all the newly generated individuals and the original population P(t) to form a new population , and select individuals with smaller fitness function values for mutation with a certain mutation probability (usually a probability less than 0.4) can be selected. In the present invention, the method of swap mutation is adopted, randomly select two gene positions, and then swap their gene values to obtain a new population , and calculate their fitness values.

[0065] S66: Select M larger individuals as the new population according to the fitness function values in and determine whether the genetic algebra is reached and output the optimal individual. If not, return to execute step S62 and subsequent steps.

[0066] The flowchart of the genetic algorithm is as shown in Figure 3 Using this algorithm, the baseline pairing method of the microlens array can be optimized, and then the UV spectrum sampling can be optimized. The UV spectrum sampling diagram obtained after optimization by the genetic algorithm is as shown in Figure 5

[0067] S7: Use the interference baseline pairing method corresponding to the maximum value of the objective function as the optimal baseline pairing method for the photon integrated interference imaging system.

[0068] Figure 2 shows the layout diagram of a given wavy microlens array. The wavy microlens array is composed of a total of 37 interference arms surrounding a center point, and 100 microlenses are arranged on each interference arm according to a certain rule.

[0069] Figure 4 shows the UV spectrum sampling diagram obtained by initializing the uniform baseline pairing method of the microlens array.

[0070] Figure 6 and Figure 7 are the reconstructed images obtained by initializing the uniform baseline pairing method of the microlens array and the reconstructed images obtained after optimizing the baseline pairing method by the genetic algorithm respectively. By comparing the two figures, it can be clearly seen that after optimizing the baseline pairing method by the genetic algorithm, the imaging quality of the system has been greatly improved, which proves the feasibility of the method for optimizing the baseline pairing of the photon integrated interference imaging system based on the genetic algorithm of the present invention.

[0071] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0072] The present invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block of the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing apparatus create means for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more boxes or blocks.

[0073] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more boxes or blocks.

[0074] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in one or more boxes or blocks.

[0075] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the present invention.

[0076] 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 claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A baseline pairing optimization method for a photon integrated interference imaging system based on a genetic algorithm, characterized in that It includes the following steps: S1: Given the arrangement mode of the microlens array of the photon integrated interference imaging system; S2: Initialize the interference baseline pairing mode of the microlens array according to the constraint conditions; S3: Use pairwise paired microlenses to perform spectral sampling on the target to obtain the mutual intensity spectrum of the target; S4: Perform inverse Fourier transform on the mutual coherence intensity of the target to obtain the spatial domain reconstructed image; S5: Calculate the peak signal-to-noise ratio value of the spatial domain reconstructed image and construct the objective function of the photon integrated interference imaging system; S6: Take the objective function obtained in step S5 as the optimization index and use the genetic algorithm to optimize the interference baseline pairing mode of the microlenses; S7: Take the interference baseline pairing mode corresponding to the maximum value of the objective function as the optimal baseline pairing mode of the photon integrated interference imaging system.

2. The baseline pairing optimization method for a photon integrated interference imaging system based on a genetic algorithm according to claim 1, wherein In S1, the microlens array is set as a wavy microlens array, and the horizontal and vertical coordinates of the center of the th microlens on the th interference arm are expressed as: ； Among them, is the horizontal coordinate of the center of the microlens, is the vertical coordinate of the center of the microlens, is the distance from the center point of the th lens on each interference arm to the origin of the photon integrated interference imaging system, is the th phase of the center of the microlens on the interference arm relative to the center of the innermost microlens.

3. The baseline pairing optimization method for a photon integrated interference imaging system based on a genetic algorithm according to claim 1, characterized in that, In S2, the constraint conditions are as follows: The entire microlens array is composed of several identical interference arms around the same center of a circle. Each interference arm is composed of several microlenses. The pairing mode of the interference baselines is the same. Only the baseline pairing mode of the microlenses on a single interference arm needs to be optimized, and each lens can only be paired once. The first microlens on the interference arm must be paired with the last microlens.

4. The baseline pairing optimization method for a photon integrated interference imaging system based on a genetic algorithm according to claim 1, characterized in that S3 specifically includes: S31: The distribution of the spatial frequency points of the system is determined by the pairwise-matched microlenses on the same interference arm, expressed as: ​ ； Among them, , is the th interference baseline formed by the th microlens on the th interference arm and the th microlens on the is the jth imaging wavelength of the system, is the detection distance, is the horizontal coordinate of the center of the th microlens on the jth interference arm, is the vertical coordinate of the center of the th microlens on the jth interference arm; S32: Take the system spatial frequency points obtained in S31 as the ideal mutual intensity spectrum samples, obtain the actually detected mutual intensity spectrum, and the mutual coherence intensity of the target is: ； Among them, is the mutual coherence intensity of the target, is the light intensity of the target.

5. The baseline pairing optimization method of the photon integrated interference imaging system based on the genetic algorithm according to claim 1, wherein In S4, the calculation formula of the spatial domain reconstructed image is: ； Among them, is the obtained actual mutual coherence intensity spectrum, is the inverse Fourier transform.

6. The baseline pairing optimization method of the photon integrated interference imaging system based on the genetic algorithm according to claim 1, wherein In S5, the objective function has the following expression: ； Among them, is the peak signal-to-noise ratio, is the maximum pixel value of the reconstructed image, is an intermediate quantity, is the reconstructed image in the spatial domain, is the light intensity of the target, and are the height and width of the reconstructed image.

7. The method for optimizing baseline pairing of a photon integrated interference imaging system based on a genetic algorithm according to claim 1, characterized in that, In S6, the specific solution steps of the genetic algorithm include: S61: Initialization of the population: Set the evolution generation counter t = 0, set the maximum number of evolution generations T, and randomly generate M individuals, X1, X2, …… X M , as the initial population P(0); S62: Calculate the fitness function: Use the objective function in step S5 as the fitness function, and calculate each individual in the population P(t) for its fitness function, and calculate the probabilities of the fitness values of all individuals: ; ( representing the i-th individual); S63: Selection operation: According to the probability of the fitness values in S62, accumulate them into a probability table for constructing a probability roulette wheel; Generate a random number for each parent position, and determine the selected individual according to the probability interval where the random number falls, and form a parent population with them; S64: Crossover operation: Under the condition of satisfying the constraint conditions of S21, determine whether to perform crossover on the parent individuals in the population with a certain crossover probability; S65: Mutation operation: Calculate the fitness functions of all new individuals, and combine all the newly generated individuals and the original population P(t) to form a new population , and select individuals with relatively smaller fitness function values for mutation with a certain mutation probability; S66: Among , select M larger individuals as the new population according to the fitness function values , and determine whether the genetic algebra is reached and output the optimal individual. If not, return to execute step S62 and subsequent steps.

8. An apparatus for optimizing baseline pairing of a photon integrated interference imaging system based on a genetic algorithm, characterized in that It includes: Microlens array arrangement mode given module, which gives the arrangement mode of the microlens array of the photon integrated interference imaging system; Initialization module, which initializes the interference baseline pairing mode of the microlens array according to the constraint conditions; Target mutual intensity spectrum acquisition module, which uses pairwise paired microlenses to perform spectral sampling on the target to obtain the mutual intensity spectrum of the target; Spatial domain reconstructed image acquisition module, which performs inverse Fourier transform on the mutual coherence intensity of the target to obtain the spatial domain reconstructed image; Objective function construction module, which calculates the peak signal-to-noise ratio value of the spatial domain reconstructed image and constructs the objective function of the photon integrated interference imaging system; Optimization module, which takes the objective function obtained by the objective function construction module as the optimization index and uses the genetic algorithm to optimize the interference baseline pairing mode of the microlenses; Optimal baseline pairing mode acquisition module, which takes the interference baseline pairing mode corresponding to the maximum value of the objective function as the optimal baseline pairing mode of the photon integrated interference imaging system.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that When the processor executes the program, it realizes the steps of the method for optimizing the baseline pairing of the photon integrated interference imaging system based on the genetic algorithm as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it realizes the steps of the method for optimizing the baseline pairing of the photon integrated interference imaging system based on the genetic algorithm as described in any one of claims 1 to 7.

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