A metasurface-based terahertz computational holographic image processing method and system

Abstract

The application discloses a kind of based on metasurface terahertz computational holographic image processing method and system, it is related to terahertz technical field, wherein, based on metasurface terahertz computational holographic image processing method, it includes the following steps: S1: based on vanadium dioxide and photosensitive silicon constructs terahertz reflection metasurface;S2: according to the imaging data required and the regulation characteristics of the terahertz wave of the terahertz reflection metasurface constructed hologram is calculated, and hologram is loaded to the terahertz reflection metasurface constructed, obtains reflected terahertz wave;S3: detection and collection reflected terahertz wave, reflected terahertz wave is handled, obtains reconstructed holographic image.The application is based on vanadium dioxide and photosensitive silicon design terahertz reflection metasurface, and based on classical theory calculation hologram, can realize terahertz wave high efficiency regulation, reduce algorithm complexity and improve calculation effect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of terahertz technology, and particularly relates to a processing method and system of a terahertz computational holographic image based on a metasurface. BACKGROUND

[0002] In the technical field of terahertz technology, the processing of a terahertz computational holographic image is of great significance for realizing high-resolution imaging, information storage and transmission and other applications. At present, the processing of a traditional terahertz computational holographic image faces many technical bottlenecks.

[0003] In the aspect of terahertz spatial light modulation, the traditional terahertz spatial light modulator has the problems of low modulation efficiency and insufficient resolution. Due to the limitations of its structure and material properties, it is difficult to flexibly and efficiently control the amplitude, phase and polarization state of a terahertz wave, resulting in an unsatisfactory imaging quality and failing to meet the application requirements of high-precision imaging.

[0004] In the aspect of holographic imaging algorithms, the existing holographic imaging algorithm relying on deep learning needs a large amount of data for training, which not only consumes a large amount of computing resources, increases the computing cost and time cost, but also has poor algorithm interpretability, making it difficult to clearly understand the physical mechanism in the imaging process and being not conducive to the optimization and improvement of the algorithm. SUMMARY

[0005] The purpose of the present application is to provide a processing method and system of a terahertz computational holographic image based on a metasurface, design a terahertz reflective metasurface based on vanadium dioxide and photosensitive silicon, and calculate a hologram based on a classical theory, which can realize efficient control of a terahertz wave, reduce the algorithm complexity and improve the calculation effect.

[0006] To achieve the above purpose, the present application provides a processing method of a terahertz computational holographic image based on a metasurface, comprising the following steps: S1: constructing a terahertz reflective metasurface based on vanadium dioxide and photosensitive silicon; S2: calculating a hologram according to the required imaging data and the control characteristics of a terahertz wave of the constructed terahertz reflective metasurface, and loading the hologram to the constructed terahertz reflective metasurface to obtain a reflected terahertz wave; S3: detecting and collecting the reflected terahertz wave, processing the reflected terahertz wave, and obtaining a reconstructed holographic image.

[0007] The above, wherein, based on vanadium dioxide and photosensitive silicon constructed terahertz reflection super surface sub-steps are as follows: S11: obtaining vanadium dioxide parameter dataset, using vanadium dioxide parameter dataset to construct vanadium dioxide dielectric constant model; S12: obtaining photosensitive silicon parameter dataset, using photosensitive silicon parameter dataset to construct photosensitive silicon conductivity and illumination parameter model; S13: obtaining design requirement data, wherein, the design requirement data at least includes: terahertz wave regulation target, external excitation condition, structure parameter value range and design target data; S14: using vanadium dioxide dielectric constant model, photosensitive silicon conductivity and illumination parameter model, and design requirement data to obtain multiple sets of simulation input data, wherein, each set of simulation input data at least includes: simulation material parameter and simulation structure parameter; S15: inputting each set of simulation input data into electromagnetic simulation software, obtaining multiple simulation results, each simulation result at least includes: terahertz wave reflection coefficient, transmission coefficient and phase change; S16: using design target data to analyze each simulation result, obtaining multiple comprehensive errors, using comprehensive error threshold to judge each comprehensive error, if there is a comprehensive error less than or equal to comprehensive error threshold, then the simulation input data corresponding to the comprehensive error less than or equal to comprehensive error threshold is taken as super surface unit structure parameter, and the terahertz reflection super surface is constructed according to the super surface unit structure parameter; if all comprehensive errors are greater than comprehensive error threshold, then the simulation input data is reacquired, and S15 is executed.

[0008] The above, wherein, the expression of comprehensive error is:

[0009] Wzh k = η1·|Sfs-Ffs k + η2·|Sts-Fts k + η3·|Sxw-Fxw k ; wherein, Wzh k is the comprehensive error between the kth simulation result and the design target data; η1 is the error weight of the reflection coefficient of the terahertz wave; Sfs is the reflection coefficient of the terahertz wave in the design target data; Ffs k is the reflection coefficient of the terahertz wave in the kth simulation result; η2 is the error weight of the transmission coefficient; Sts is the transmission coefficient in the design target data; Fts k is the transmission coefficient in the kth simulation result; η3 is the error weight of the phase; Sxw is the phase change in the design target data; Fxw k is the phase change in the kth simulation result; η1+η2+η3=1.

[0010] The above, wherein the sub-step of calculating the hologram according to the required imaging data and the regulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface is as follows: S21: processing the required imaging data to obtain a target complex amplitude distribution; S22: processing the target complex amplitude distribution according to the regulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface to obtain a light field complex amplitude distribution; S23: calculating the hologram according to the reference complex amplitude distribution and the light field complex amplitude distribution.

[0011] The above, wherein the expression of the hologram is as follows: I(x, y) = |U gc (x, y) + R(x, y)| 2 ; wherein I(x, y) is the light intensity distribution at point (x, y) of the hologram; U gc (x, y) is the light field complex amplitude distribution at point (x, y); and R(x, y) is the reference complex amplitude distribution at point (x, y).

[0012] The above, wherein the target complex amplitude distribution is obtained by processing the required imaging data by using the Fresnel diffraction theory.

[0013] The above, wherein the sub-step of processing the reflected terahertz wave to obtain the reconstructed holographic image is as follows: S31: filtering the reflected terahertz wave to obtain a filtered signal; S32: amplifying the filtered signal to obtain an amplified signal; and S33: processing the amplified signal to obtain the reconstructed holographic image.

[0014] The above, wherein the Fourier transform is used to process the amplified signal to obtain the reconstructed holographic image.

[0015] The above, wherein the sub-step of processing the amplified signal to obtain the reconstructed holographic image by using the Fourier transform is as follows: T1: performing discrete Fourier transform on the amplified signal to obtain a frequency domain signal; and T2: performing inverse Fourier transform on the frequency domain signal to obtain the reconstructed holographic image.

[0016] The application also provides a super-surface-based terahertz computational holographic image processing system, comprising a super-surface design module, a hologram calculation module, a super-surface loading and wave modulation module, and an imaging and image processing module; wherein the super-surface design module is used to construct a terahertz reflective super-surface based on vanadium dioxide and photosensitive silicon, determine the unit structure parameters of the terahertz reflective super-surface according to different functional requirements, and simulate and analyze the regulation and control performance of the terahertz reflective super-surface on terahertz waves; the hologram calculation module is used to calculate a hologram according to the required imaging data and the regulation and control characteristics of the terahertz waves of the constructed terahertz reflective super-surface; the super-surface loading and wave modulation module is used to load the hologram to the constructed terahertz reflective super-surface, obtain a reflected terahertz wave, and realize modulation on the incident terahertz wave; and the imaging and image processing module is used to detect and collect the reflected terahertz wave, process the reflected terahertz wave, and obtain a reconstructed holographic image.

[0017] The application achieves the following beneficial effects:

[0018] (1) The super-surface-based terahertz computational holographic image processing method and system can flexibly and efficiently regulate and control the amplitude, phase and polarization state of terahertz waves, and significantly improve the modulation effect and imaging resolution.

[0019] (2) The super-surface-based terahertz computational holographic image processing method and system calculate a hologram based on classical theory, avoid the complexity problem of deep learning algorithm, reduce the complexity of the algorithm, and improve the calculation efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0021] Figure 1 FIG. 1 is a structural schematic diagram of an embodiment of the super-surface-based terahertz computational holographic image processing system;

[0022] Figure 2 FIG. 2 is a flowchart of an embodiment of the super-surface-based terahertz computational holographic image processing method. DETAILED DESCRIPTION

[0023] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application are clearly and completely described. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0024] As shown in Figure 1 The present application provides a kind of based on super surface terahertz computing hologram image processing system, comprising: super surface design module 1, hologram calculation module 2, super surface loading and wave modulation module 3 and imaging and image processing module 4.

[0025] Wherein, super surface design module 1: for constructing terahertz reflective super surface based on vanadium dioxide and photosensitive silicon, the unit structure parameters of terahertz reflective super surface are determined according to different functional requirements, and the regulation and control performance of terahertz reflective super surface to terahertz wave is simulated and analyzed.

[0026] Specifically, different functional requirements include: hologram, vortex, abnormal reflection, absorption and focusing, but not limited to hologram, vortex, abnormal reflection, absorption and focusing. According to the functional requirements such as hologram, vortex, abnormal reflection, absorption and focusing, different characteristic super surface unit structures are combined and arranged, so that super surface with composite function can be obtained.

[0027] Hologram calculation module 2: for calculating hologram according to the required imaging data and the regulation and control characteristics of the terahertz wave of the constructed terahertz reflective super surface.

[0028] Super surface loading and wave modulation module 3: for loading hologram to the constructed terahertz reflective super surface, obtaining reflected terahertz wave, and realizing the modulation of incident terahertz wave.

[0029] Imaging and image processing module 4: detecting and collecting reflected terahertz wave, processing reflected terahertz wave, and obtaining reconstructed holographic image.

[0030] As shown in Figure 2 The present application provides a kind of based on super surface terahertz computing hologram image processing method, comprising the following steps:

[0031] S1: constructing terahertz reflective super surface based on vanadium dioxide (VO2) and photosensitive silicon.

[0032] Further, the sub-steps of constructing terahertz reflective super surface based on vanadium dioxide (VO2) and photosensitive silicon are as follows:

[0033] S11: obtain vanadium dioxide parameter data set, and construct vanadium dioxide dielectric constant model using vanadium dioxide parameter data set.

[0034] Specifically, the vanadium dioxide parameter dataset includes a plurality of vanadium dioxide (VO2) sample data, which are parameter data of vanadium dioxide at different temperatures and different terahertz frequency bands, such as medium constant, conductivity, angular frequency, and damping coefficient, obtained by measuring with a collection device (for example, a spectrometer or an impedance analyzer).

[0035] Further, the expression of the vanadium dioxide dielectric constant model is:

[0036]

[0037] wherein ε(T, ω) is the dielectric constant of vanadium dioxide (VO2) at temperature T and the angular frequency ω of the terahertz wave; ε ∞ is the dielectric constant at the high frequency limit; ω p is the plasma oscillation angular frequency; j is an imaginary number, j 2 = 1; γ is the damping coefficient; f i is the oscillator strength of the i-th oscillator; ω pi is the plasma oscillation angular frequency of the i-th oscillator; ω 0i is the intrinsic angular frequency of the i-th oscillator; γ i is the damping coefficient of the i-th oscillator; and β(T, ω) is the coupling effect function of temperature and frequency.

[0038] Specifically, the vanadium dioxide dielectric constant model of the present application can accurately calculate the dielectric constant of vanadium dioxide after considering the coupling effect of temperature and frequency, so as to more accurately predict the regulation performance of the metasurface on the terahertz wave, and further optimize the unit structure parameters of the terahertz reflection metasurface.

[0039] wherein the expression of the coupling effect function of temperature and frequency is:

[0040] β(T, ω) = A(T) · ω + B(T);

[0041] A(T) = a0 + a1T + a2T 2 ;

[0042] B(T) = b0 + b1T + b2T 2 ;

[0043] wherein A(T) is the change data of the influence degree of the angular frequency ω of the terahertz wave on the coupling effect of temperature and frequency with the change of temperature T; B(T) is the change data of the influence degree of temperature T on the coupling effect of temperature and frequency, except for the influence of the angular frequency ω of the terahertz wave; a0, a1, and a2 are the coefficient values of A(T); and b0, b1, and b2 are the coefficient values of B(T).

[0044] Specifically, A(T) and B(T) are fitted by using specific research objects and experimental data, for example: the research object is vanadium dioxide (VO2), and the experimental data includes the transmission and reflection data of vanadium dioxide (VO2) at different temperatures on terahertz waves measured by a terahertz time-domain spectroscopy technique, the dielectric constant data is obtained, and the dielectric constant data, the corresponding temperature and the terahertz wave angular frequency are fitted by using a fitting method to determine the coefficient values (a0, a1, a2 and b0, b1, b2), so as to obtain A(T) and B(T). Preferably, the fitting method is the least square method, but is not limited to the least square method.

[0045] S12: Obtain a photosensitive silicon parameter data set, and construct a conductivity and illumination parameter model of the photosensitive silicon by using the photosensitive silicon parameter data set.

[0046] Specifically, the photosensitive silicon parameter data set includes a plurality of photosensitive silicon sample data, and the plurality of photosensitive silicon sample data is the parameter data of the photosensitive silicon, such as the conductivity and the carrier concentration change, which is obtained by testing under different illumination intensities and illumination wavelengths.

[0047] Further, the expression of the conductivity and illumination parameter model of the photosensitive silicon is as follows:

[0048] σ Si (I, λ) = σ0 + Δσ(I, λ);

[0049] wherein, σ Si (I, λ) is the conductivity of the photosensitive silicon under the illumination intensity I and the illumination wavelength λ; σ0 is the initial conductivity of the photosensitive silicon, that is, the conductivity without illumination; and Δσ is the conductivity change amount caused by illumination.

[0050] S13: Obtain design requirement data, wherein the design requirement data at least includes a terahertz wave regulation target, an external excitation condition, a structure parameter value range and design target data.

[0051] Specifically, the terahertz wave regulation target is to realize the continuous adjustable reflection phase 0-2π in a preset frequency band or to realize a preset polarization conversion efficiency. The specific value of the preset frequency band is set according to the actual situation, and the application preferably is 0.1-1 THz. The specific value of the preset polarization conversion efficiency is set according to the actual situation, and the application preferably is greater than 80%.

[0052] The external excitation condition includes the working temperature range and the working angular frequency range of vanadium dioxide (VO2), the photosensitive silicon illumination intensity range and the illumination wavelength.

[0053] The specific content and specific values of the structure parameter value range are set according to process limitations, for example: the shape of the patch unit, the size range of the patch unit, the minimum line width range, and the minimum spacing range. For example, the shape of the patch unit is rectangular, and the size range of the patch includes: the length range of the patch unit, the width range of the patch unit, and the thickness range of the patch unit.

[0054] The feasible region of the parameter is limited by the external excitation condition and the process limitation to avoid the design from deviating from the actual application scenario.

[0055] The design target data is ideal data determined according to the terahertz wave regulation target, including: the reflection coefficient, the transmission coefficient, and the phase change of the terahertz wave.

[0056] S14: Obtain a plurality of sets of simulation input data using the vanadium dioxide dielectric constant model, the photosensitive silicon conductivity and the light parameter model, and the design requirement data, wherein each set of simulation input data at least includes: simulation material parameters and simulation structure parameters.

[0057] Further, the sub-steps of obtaining a plurality of sets of simulation input data using the vanadium dioxide dielectric constant model, the photosensitive silicon conductivity and the light parameter model, and the design requirement data are as follows:

[0058] S141: Construct a plurality of sets of vanadium dioxide input data according to the working temperature range and the working angular frequency range in the external excitation condition, and input each set of vanadium dioxide input data into the vanadium dioxide dielectric constant model to obtain a plurality of to-be-simulated dielectric constants; wherein each set of vanadium dioxide input data includes: a working temperature and a working angular frequency, the working temperature belongs to the working temperature range, and the working angular frequency belongs to the working angular frequency range.

[0059] S142: Construct a plurality of sets of photosensitive silicon input data according to the photosensitive silicon light intensity range and the light wavelength in the external excitation condition, and input each set of photosensitive silicon input data into the photosensitive silicon conductivity and the light parameter model to obtain a plurality of to-be-simulated conductivity values; wherein each set of photosensitive silicon input data includes: a photosensitive silicon light intensity and a light wavelength, and the photosensitive silicon light intensity belongs to the photosensitive silicon light intensity range.

[0060] S143: Construct a plurality of sets of to-be-simulated structure parameters according to the structure parameter value range, wherein each set of simulation structure parameters at least includes: the shape of the patch unit, the size of the patch unit, the minimum line width, and the minimum spacing; wherein the size of the patch unit belongs to the size range of the patch unit, the minimum line width belongs to the minimum line width range, and the minimum spacing belongs to the minimum spacing range.

[0061] Specifically, for example: the shape of the patch unit is rectangular, and each set of simulation structure parameters at least includes: minimum line width, minimum spacing, length of the patch unit, width of the patch unit and thickness of the patch unit, the minimum line width belongs to the minimum line width range, the minimum spacing belongs to the minimum spacing range, the length of the patch unit belongs to the length range of the patch unit, the width of the patch unit belongs to the width range of the patch unit, and the thickness of the patch unit belongs to the thickness range of the patch unit.

[0062] S144: Constructing a plurality of sets of simulation input data according to a plurality of to-be-simulated dielectric constants, a plurality of to-be-simulated conductivity values and a plurality of sets of to-be-simulated structure parameters; wherein each set of simulation input data includes: one to-be-simulated dielectric constant, one to-be-simulated conductivity value and one set of to-be-simulated structure parameters.

[0063] S15: Inputting each set of simulation input data into the electromagnetic simulation software to obtain a plurality of simulation results, each simulation result at least including: a reflection coefficient, a transmission coefficient and a phase change of the terahertz wave.

[0064] Further, the electromagnetic simulation software is CST (CST Microwave Studio) or HFSS (High-Frequency Structure Simulator), but is not limited to CST or HFSS, and can be other electromagnetic simulation software capable of achieving the required functions of the present application.

[0065] S16: Analyzing each simulation result using the design target data to obtain a plurality of comprehensive errors, and judging each comprehensive error using a comprehensive error threshold, if there is one comprehensive error less than or equal to the comprehensive error threshold, then the simulation input data corresponding to the comprehensive error less than or equal to the comprehensive error threshold is taken as the metasurface unit structure parameter, and a terahertz reflection metasurface is constructed according to the metasurface unit structure parameter; if all the comprehensive errors are greater than the comprehensive error threshold, then the simulation input data is reacquired, and S15 is executed.

[0066] Specifically, the simulation input data is reacquired by the existing optimization method, and the optimal solution is obtained by gradually adjusting the to-be-simulated structure parameters, wherein each time the to-be-simulated structure parameters are adjusted, the to-be-simulated dielectric constant and the to-be-simulated conductivity value need to be recalculated, which can ensure the accuracy of the simulation results. Wherein, the optimization method is genetic algorithm or particle swarm optimization algorithm, but is not limited to genetic algorithm or particle swarm optimization algorithm.

[0067] Further, the expression of the comprehensive error is:

[0068] Wzh k = η1·|Sfs-Ffs k + η2·|Sts-Fts k| + η3 · |Sxw - Fxw| k |

[0069] wherein Wzh k is the comprehensive error between the kth simulation result and the design target data; η1 is the error weight of the reflection coefficient of the terahertz wave; Sfs is the reflection coefficient of the terahertz wave in the design target data; Ffs k is the reflection coefficient of the terahertz wave in the kth simulation result; η2 is the error weight of the transmission coefficient; Sts is the transmission coefficient in the design target data; Fts k is the transmission coefficient in the kth simulation result; η3 is the error weight of the phase; Sxw is the phase change in the design target data; Fxw k is the phase change in the kth simulation result; η1 + η2 + η3 = 1.

[0070] S2: calculate the hologram according to the required imaging data and the modulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface, and load the hologram to the constructed terahertz reflective metasurface to obtain the reflected terahertz wave.

[0071] Further, the sub-step of calculating the hologram according to the required imaging data and the modulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface is as follows:

[0072] S21: process the required imaging data to obtain the target complex amplitude distribution.

[0073] Specifically, the required imaging data obtains the target complex amplitude distribution from the object plane to the hologram plane.

[0074] Further, the required imaging data is processed by using the Fresnel diffraction theory to obtain the target complex amplitude distribution, but it is not limited to the Fresnel diffraction theory.

[0075] S22: process the target complex amplitude distribution according to the modulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface to obtain the light field complex amplitude distribution.

[0076] Specifically, the terahertz reflective metasurface realizes the modulation of the terahertz wave by changing its amplitude and phase, and the modulation characteristics of the terahertz wave are related to the structural parameters and material characteristics. The light field complex amplitude distribution is obtained after the target complex amplitude distribution is modulated by the terahertz reflective metasurface.

[0077] Further, the expression of the light field complex amplitude distribution is as follows:

[0078] U gc (x, y) = U mb (x, y) · H(x, y);

[0079] wherein Ugc (x, y) is the light field complex amplitude distribution at point (x, y); U mb (x, y) is the target complex amplitude distribution at point (x, y); H(x, y) is the regulation characteristic of the terahertz wave of the constructed terahertz reflective metasurface, used to represent the complex transmittance of the terahertz reflective metasurface at point (x, y).

[0080] S23: Calculate the hologram according to the reference complex amplitude distribution and the light field complex amplitude distribution.

[0081] Further, the expression of the hologram is:

[0082] I(x, y) = |U gc (x, y) + R(x, y)| 2 ;

[0083] wherein I(x, y) is the light intensity distribution at point (x, y) of the hologram; U gc (x, y) is the light field complex amplitude distribution at point (x, y); R(x, y) is the reference complex amplitude distribution at point (x, y).

[0084] wherein R(x, y) can be determined according to experimental measurement method, theoretical calculation method, priori knowledge or empirical model method.

[0085] S3: Detect and collect the reflected terahertz wave, process the reflected terahertz wave, and obtain the reconstructed holographic image.

[0086] Specifically, the reflected terahertz wave is detected and collected by a collection device. The collection device is not limited to a terahertz detector.

[0087] Further, the processing of the reflected terahertz wave to obtain the sub-step of the reconstructed holographic image is as follows:

[0088] S31: Filter the reflected terahertz wave to obtain a filtered signal.

[0089] Further, a digital filter is used to filter the reflected terahertz wave to obtain a filtered signal, but it is not limited to a digital filter. The digital filter used in the present application can remove the noise and interference components doped in the signal and retain the effective signal related to the holographic image.

[0090] S32: Amplify the filtered signal to obtain an amplified signal.

[0091] Further, an amplifier is used to amplify the filtered signal to obtain an amplified signal, but it is not limited to an amplifier. The amplifier used in the present application can enhance the amplitude of the signal to facilitate subsequent analysis and processing and improve the signal-to-noise ratio of the signal.

[0092] S33: processing the amplified signal to obtain a reconstructed holographic image.

[0093] Further, the Fourier transform is used to process the amplified signal to obtain a reconstructed holographic image, but it is not limited to the Fourier transform, and the application preferably converts the amplified signal from the spatial domain to the frequency domain for processing through the Fourier transform to obtain a reconstructed holographic image.

[0094] Further, the Fourier transform is used to process the amplified signal to obtain a reconstructed holographic image, but it is not limited to the Fourier transform, and the application preferably converts the amplified signal from the spatial domain to the frequency domain for processing through the Fourier transform to obtain a reconstructed holographic image.

[0095] T1: performing discrete Fourier transform on the amplified signal to obtain a frequency domain signal.

[0096] T2: performing inverse Fourier transform on the frequency domain signal to obtain a reconstructed holographic image.

[0097] Further, the expression of the reconstructed holographic image is:

[0098]

[0099] wherein Jcg(x,y) is the reconstructed holographic image at point (x,y) of the hologram; IDFT2[] is a two-dimensional inverse discrete Fourier transform; z(n) is a time domain signal; N is the total number of sampling points of the signal, n is the index of the discrete time sequence, used to identify each sampling point in the time domain signal, n∈[0,N-1]; is a rotation factor for mapping the time domain signal to the frequency domain; j is an imaginary number, j 2 =1; e is the base of the exponential function; π is the circular constant; l is the discrete frequency index; is a frequency domain signal.

[0100] The application achieves the following beneficial effects:

[0101] (1) The super-surface-based terahertz computational holographic image processing method and system can flexibly and efficiently modulate the amplitude, phase and polarization state of terahertz waves based on vanadium dioxide (VO2) and photosensitive silicon to construct a terahertz reflective super-surface, significantly improving the modulation effect and imaging resolution.

[0102] (2) The super-surface-based terahertz computational holographic image processing method and system is based on classical theory to calculate the hologram, avoiding the complexity of deep learning algorithms, reducing the complexity of the algorithm, and improving the calculation efficiency.

[0103] While the preferred embodiments of the application have been described, additional variations and modifications can be made to these embodiments by those skilled in the art once they have the benefit of the foregoing description without departing from the spirit and scope of the application. Accordingly, it is intended that the scope of the application be governed solely by the appended claims and their equivalents. Obviously, many modifications and variations of this application are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for processing terahertz computational holographic images based on metasurfaces, characterized in that, Includes the following steps: S1: A terahertz reflective metasurface constructed based on vanadium dioxide and photosensitive silicon; S2: Calculate the hologram based on the required imaging data and the modulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface, and load the hologram onto the constructed terahertz reflective metasurface to obtain the reflected terahertz wave; S3: Detect and collect reflected terahertz waves, process the reflected terahertz waves, and obtain a reconstructed holographic image; The sub-steps for constructing a terahertz reflective metasurface based on vanadium dioxide and photosensitive silicon are as follows: S11: Obtain the vanadium dioxide parameter dataset and use the vanadium dioxide parameter dataset to construct a vanadium dioxide dielectric constant model; S12: Obtain the photosensitive silicon parameter dataset and use it to construct a model of the conductivity and illumination parameters of the photosensitive silicon. S13: Obtain design requirement data, which shall include at least: terahertz wave control target, external excitation conditions, structural parameter value range and design target data; S14: Using the vanadium dioxide dielectric constant model, the conductivity and illumination parameter models of photosensitive silicon, and design requirement data, multiple sets of simulation input data are obtained. Each set of simulation input data includes at least: simulation material parameters and simulation structural parameters. S15: Input each set of simulation input data into the electromagnetic simulation software to obtain multiple simulation results. Each simulation result shall include at least the reflection coefficient, transmission coefficient and phase change of the terahertz wave. S16: Analyze each simulation result using the design target data to obtain multiple comprehensive errors. Use the comprehensive error threshold to judge each comprehensive error. If there is a comprehensive error that is less than or equal to the comprehensive error threshold, then use the simulation input data corresponding to the comprehensive error that is less than or equal to the comprehensive error threshold as the metasurface unit structure parameter, and construct a terahertz reflecting metasurface based on the metasurface unit structure parameter. If all comprehensive errors are greater than the comprehensive error threshold, then re-acquire the simulation input data and execute S15.

2. The method for processing terahertz computational holographic images based on metasurfaces according to claim 1, characterized in that, The expression for the overall error is: Wzh k =η1·|Sfs-Ffs k |+η2·|Sts-Fts k |+η3·|Sxw-Fxw k |; Among them, Wzh k ηk represents the combined error between the k-th simulation result and the design target data; η1 represents the error weight of the terahertz wave reflection coefficient; Sfs represents the terahertz wave reflection coefficient in the design target data; Ffs represents the error weight of the reflection coefficient of the terahertz wave. k ηk is the reflection coefficient of the terahertz wave in the k-th simulation result; η2 is the error weight of the transmission coefficient; Sts is the transmission coefficient in the design target data; Fts k η is the transmission coefficient in the k-th simulation result; η3 is the phase error weight; Sxw is the phase change in the design target data; Fxw k Let η1 + η2 + η3 = 1, where η1 + η2 + η3 = 1.

3. The method for processing terahertz computational holographic images based on metasurfaces according to claim 1, characterized in that, The sub-steps for calculating the hologram based on the required imaging data and the terahertz wave modulation characteristics of the constructed terahertz reflective metasurface are as follows: S21: Process the required imaging data to obtain the target complex amplitude distribution; S22: The complex amplitude distribution of the target is processed according to the modulation characteristics of the terahertz wave of the constructed terahertz reflective metasurface to obtain the complex amplitude distribution of the optical field. S23: Calculate the hologram based on the reference complex amplitude distribution and the optical field complex amplitude distribution.

4. The method for processing terahertz computational holographic images based on metasurfaces according to claim 3, characterized in that, The expression for a hologram is: I(x,y)=|U gc (x,y)+R(x,y)| 2 ; Where I(x,y) represents the light intensity distribution at point (x,y) in the hologram; U gc (x,y) represents the complex amplitude distribution of the light field at point (x,y); R(x,y) represents the reference complex amplitude distribution at point (x,y).

5. The method for processing terahertz computational holographic images based on metasurfaces according to claim 3, characterized in that, The Fresnel diffraction theory is used to process the required imaging data to obtain the complex amplitude distribution of the target.

6. The method for processing terahertz computational holographic images based on metasurfaces according to claim 1, characterized in that, The sub-steps for processing the reflected terahertz wave to obtain the reconstructed holographic image are as follows: S31: Filter the reflected terahertz wave to obtain the filtered signal; S32: Amplify the filtered signal to obtain the amplified signal; S33: Process the amplified signal to obtain the reconstructed holographic image.

7. The method for processing terahertz computational holographic images based on metasurfaces according to claim 6, characterized in that, The amplified signal is processed using Fourier transform to obtain the reconstructed holographic image.

8. The method for processing terahertz computational holographic images based on metasurfaces according to claim 7, characterized in that, The sub-steps for processing the amplified signal using Fourier transform to obtain the reconstructed holographic image are as follows: T1: Perform a discrete Fourier transform on the amplified signal to obtain the frequency domain signal; T2: Perform inverse Fourier transform on the frequency domain signal to obtain the reconstructed holographic image.

9. A processing system for terahertz computational holographic images based on metasurfaces, characterized in that, include: Metasurface design module, hologram calculation module, metasurface loading and wave modulation module, and imaging and image processing module; Among them, the metasurface design module is used to construct terahertz reflective metasurfaces based on vanadium dioxide and photosensitive silicon, determine the unit structure parameters of the terahertz reflective metasurface according to different functional requirements, and simulate and analyze the modulation performance of the terahertz reflective metasurface on terahertz waves. Hologram Calculation Module: Used to calculate holograms based on the required imaging data and the modulation characteristics of terahertz waves of the constructed terahertz reflective metasurface; Metasurface loading and wave modulation module: used to load holograms onto the constructed terahertz reflective metasurface to obtain reflected terahertz waves and to modulate the incident terahertz waves; Imaging and image processing module: detects and acquires reflected terahertz waves, processes the reflected terahertz waves, and obtains reconstructed holographic images.

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