An image processing metasurface design method based on complex amplitude modulation

Abstract

The application belongs to the technical field of image processing, and provides a kind of image processing metasurface design method based on complex amplitude modulation, including a kind of dielectric metasurface, which is composed of silicon dioxide substrate and alpha-Si nanometer column on the substrate, dielectric nanometer column arrangement method based on geometric phase physical concept is adopted, so that the point spread function of the metasurface is equal to a specific convolution kernel, and image processing operation is carried out by using the principle that the response of image through the system corresponds to the convolution of image and system point spread function;The application adopts dielectric nanometer column arrangement method based on geometric phase physical concept, so that the point spread function of the metasurface is equal to a specific convolution kernel, and edge detection and second-order differential image processing operation are carried out by using the principle that the response of image through the system corresponds to the convolution of image and system point spread function, which greatly reduces the size of optical convolution layer and improves the integration and operation speed.

Description

Technical Field

[0001] The present invention belongs to the technical field of image processing, and in particular to a method for designing an image processing metasurface based on complex amplitude modulation. Background Art

[0002] Currently, in-depth research on deep convolutional neural networks (CNNs) has enabled the rapid development of artificial intelligence (AI) in academia and industry. Within each layer of a CNN, numerous kernels with specific functions are used to perform convolution operations to extract important features of an object for recognition. However, as the number of AI tasks increases, this approach remains extremely time-consuming. While advanced electronic devices such as graphics processing units, field-programmable gate arrays, and tensor processing units have been developed to accelerate computations to address these challenges, computational speed and energy consumption are still limited by the slower response of electronics, such as the charging and discharging of capacitors, electromagnetic radiation, and the heat generated by the movement of electrons in materials, due to the limitations of electrical devices.

[0003] Optical neural networks are considered key to breaking through bottlenecks in the next generation of artificial neural networks. Theoretically, photons, as massless bosons, can propagate losslessly and at high speed through large-bandgap transparent materials. Optical diffraction structures can also be used to quantitatively manipulate optical information, eliminating the need for electronic processing modules such as analog-to-digital and digital-to-analog converters, thereby enabling near-light-speed and low-loss computation. Currently, optical neural networks can be categorized into two main types: optoelectronic hybrid neural networks and all-optical neural networks. While optoelectronic hybrid neural networks can perform the functions of convolutional neural networks, the optical portion of the network is limited to convolution, with the electrical signal generated after optoelectronic conversion continuing to propagate within the electronic neural network. While all-optical neural networks do not require optoelectronic conversion, they cannot achieve convolution and can only perform the functions of fully connected layers. Based on the primary optical components used, all-optical neural networks can be further categorized into three types: photonic chips, passive diffraction optical elements, and scattering materials.

[0004] However, optoelectronic hybrid neural networks based on diffractive optical elements operate on a similar principle to spatial filtering using a "4f system" consisting of two convex lenses with a focal length of f. A phase plate is placed in the Fourier plane in the middle of the "4f system" to modulate the amplitude and phase of the incident light to achieve convolution. The result of the optical operation still contains a large amount of information. All-optical nanophotonic circuit neural networks are primarily based on Mach-Zehnder interferometers that modulate waveguide modes and phase. While the mathematical process is clearer than all other all-optical neural networks, it requires more components to participate in the operation, resulting in larger modules and hindering integration.

[0005] To this end, those skilled in the art have proposed an image processing metasurface design method based on complex amplitude modulation. Summary of the Invention

[0006] In order to solve the above technical problems, the present invention provides an image processing metasurface design method based on complex amplitude modulation to solve the problems mentioned in the background technology.

[0007] A method for designing an image processing metasurface based on complex amplitude modulation includes a dielectric metasurface composed of a silicon dioxide substrate and α-Si nanopillars on the substrate. A dielectric nanopillar arrangement method based on geometric phase physics is used to make the metasurface's point spread function equal to a specific convolution kernel. Image processing operations are performed based on the principle that the response of an image passing through a system corresponds to the convolution of the image and the system's point spread function.

[0008] By regulating the geometric phase and amplitude of the unit structure, the point spread function of the metasurface is made equivalent to the convolution kernel, and the image is convolved and processed.

[0009] The complex amplitude of vortex light with different orbital quantum numbers l and characteristic numbers p is used as the pupil function of the metasurface, and the pupil function of the metasurface, that is, the complex amplitude of the metasurface, is modulated in real space. Since the size and azimuth angle of the nanopillars can be arbitrarily controlled, the complex amplitude of the metasurface can be arbitrarily selected, and any image processing operation can be performed. Edge detection is used to convert the input Gaussian beam into vortex light.

[0010] Preferably, under monochromatic light illumination, the distribution of a certain object plane image can be decomposed into countless delta functions, that is, linear combinations of impulse functions, and each delta function can be used to calculate its corresponding point spread function. By introducing the pupil function P(x, y), the coherent point spread function of the imaging system is derived. The distances between the metasurface and the object plane and the image plane are l1 and l2, respectively. The position of a point source on the object plane is set to (x0, y0). The electric field distribution of the spherical wave emitted by it passing through the position l1 away from the point source is:

[0011]

[0012] Assuming that the complex pupil function of the metasurface is P(x1,y1), the distribution of the electric field after passing through the metasurface is expressed as:

[0013] u2(x1,y1)=u1(x1,y1)·P(x1,y1)

[0014] After Fresnel diffraction, the electric field distribution in the image plane at a distance of l2 from the metasurface is:

[0015]

[0016]

[0017] Preferably, an additional lens phase function is applied to the metasurface:

[0018]

[0019] Where f represents the focal length of the lens. According to the relationship between the focal length of the lens and the object distance and image distance: So that:

[0020]

[0021] make Then the integral term is equal to:

[0022] Where Φ(·) is the Fourier transform, then the electric field distribution u2′(x2,y2) on the image plane, i.e., the point spread function, is:

[0023]

[0024] After obtaining the point spread function, the image plane image is equal to the convolution of the original image and the point spread function, then the image plane field distribution is U(x2,y2)=U(x1,y1)*PSF∝U(x1,y1)*Φ[P(x1,y1)], where * is the convolution operation symbol.

[0025] Preferably, the Fourier transform form of the complex pupil function P(x, y) of the metasurface is made equivalent to a convolution kernel of a specific function, and the metasurface performs image processing and convolution operations. The metasurface performs filtering in the spatial frequency domain by regulating the complex amplitude of the metasurface real space.

[0026] Preferably, the device responds to circularly polarized light of 780 nm wavelength, and controls the length and width of nanorods made of α-Si and with a period of 400 nm, as well as the angle of the long axis relative to the x-axis, thereby controlling the conversion efficiency of the cross-circular polarization and the geometric phase in the cross-polarization term, thereby achieving simultaneous regulation of amplitude and phase.

[0027] The circularly polarized light carrying the image information is transmitted to the metasurface at point l1 in front of the metasurface, modulated by the metasurface, and finally forms a processed image at point l2 behind the metasurface. The cross-polarization component is detected by a half-wave plate and a polarizer to obtain the image information of the cross-circular polarization state.

[0028] Preferably, the edge detection image processing operation: using the electric field of the Laguerre-Gaussian beam as a reference for the complex pupil function of the metasurface to perform complex amplitude control, wherein the donut-shaped amplitude and vortex-shaped phase meet the conditions for performing a two-dimensional differential operation, thereby extracting edges in the x and y directions;

[0029] Gaussian filtering image processing operation: The metasurface complex pupil function is modulated in the form of a Gaussian function, so that the metasurface performs a function similar to a low-pass filter, filtering out noise mainly composed of high-frequency signals.

[0030] Preferably, it also includes using elliptical nanocolumns made of amorphous silicon as the backup unit structure of the metasurface, based on the principle of Fano resonance, using the phase and amplitude mutations brought about by the resonance to accurately control the amplitude and phase of the light field.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. By regulating the geometric phase and amplitude of the unit structure, the present invention can make the point spread function of the metasurface equivalent to the convolution kernel, thereby realizing the convolution and processing functions of the image, with a computing speed close to the speed of light, low loss, and no large amount of heat loss; the integration is higher, and the manufacturing size is limited to the micron level; the unit structure of the metasurface is in subwavelength size, which can provide ultra-high image edge extraction accuracy of about 2.6μm and an energy utilization rate of about 0.7, which can achieve more efficient edge detection.

[0033] 2. The present invention modulates the pupil function of the metasurface, i.e., the complex amplitude of the metasurface, in real space. Since the size and azimuth of the nanopillars can be arbitrarily controlled, the complex amplitude of the metasurface can also be arbitrarily selected, thereby realizing arbitrary image processing operations and meeting the requirements of convolutional neural networks for a variety of convolution kernels. At the same time, by utilizing the effect of edge detection, the input Gaussian light beam can be converted into vortex light, i.e., a donut-shaped intensity distribution and a vortex-shaped phase distribution, thereby realizing other functions in addition to image processing operations such as edge detection.

[0034] 3. The present invention uses vortex light complex amplitudes with different orbital quantum numbers l and characteristic numbers p as the pupil function of the metasurface to perform targeted information filtering on images containing different high-frequency information, so that the image only contains useful information. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Figure 1 is a diagram illustrating the working principle of the convolutional metasurface image processing of the present invention, (a) schematic diagram of the PSF calculation of the convolutional metasurface, where u1(x1, y1) and u2(x1, y1) represent the light fields before and after the metasurface, (b), (c) schematic diagrams of the metasurface used for edge detection (b) and Gaussian denoising (c) of the input image;

[0036] Figure 2 This is a schematic diagram of the unit structure for complex amplitude modulation of the present invention;

[0037] Figure 3Figure 2 shows the edge detection metasurface of the present invention. (a) and (c) are the amplitude and phase distributions of the metasurface under circularly polarized light illumination, respectively. The inset in (a) shows the discretized amplitude distribution. (b) is an SEM image of the fabricated metasurface. The diameter of the entire metasurface is 600 μm, and the scale bar is 2 μm. (d) is the measured intensity distribution of the metasurface. The insets show the simulated (curved) and measured (circled) intensity curves along the blue and orange dashed lines in (a) and (d), respectively.

[0038] Figure 4 Figure 1 shows the Gaussian filtered metasurface of the present invention. (a) and (c) are the amplitude and phase distributions of the metasurface under circularly polarized light illumination, respectively. The inset in (a) shows the discretized amplitude distribution. (b) is an SEM image of the fabricated metasurface. The diameter of the entire metasurface is 600 μm, and the scale bar is 2 μm. (d) is the measured intensity distribution of the metasurface. The insets show the simulated (curved) and measured (circled) intensity curves along the blue and orange dashed lines in (a) and (d), respectively.

[0039] Figure 5 The image of the metasurface interacting with the letter NJU and its tangent intensity distribution diagram obtained by MATLAB numerical simulation in the experimental example of the present invention;

[0040] Figure 6 The edge detection results and tangent intensity distribution diagram of the letter NJU obtained by simulation and experiment of the present invention;

[0041] Figure 7 These are the numerical simulation and experimental measurement results under different noises or patterns of the present invention, with a scale of 20 μm. DETAILED DESCRIPTION

[0042] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0043] Example 1: The present invention provides a method for designing an image processing metasurface based on complex amplitude modulation, including a dielectric metasurface composed of a silicon dioxide substrate and α-Si nanopillars on the substrate. A dielectric nanopillar arrangement method based on the concept of geometric phase physics is used to make the point spread function of the metasurface equal to a specific convolution kernel. Image processing operations are performed based on the principle that the response of an image passing through a system corresponds to the convolution of the image and the system's point spread function.

[0044] By regulating the geometric phase and amplitude of the unit structure, the point spread function of the metasurface is made equivalent to the convolution kernel, and the image is convolved and processed.

[0045] The complex amplitude of vortex light with different orbital quantum numbers l and characteristic numbers p is used as the pupil function of the metasurface, and the pupil function of the metasurface, that is, the complex amplitude of the metasurface, is modulated in real space. Since the size and azimuth angle of the nanopillars can be arbitrarily controlled, the complex amplitude of the metasurface can be arbitrarily selected, and any image processing operation can be performed. Edge detection is used to convert the input Gaussian beam into vortex light.

[0046] like Figure 1 As shown in the figure, under monochromatic light illumination, the distribution of a certain object plane image can be decomposed into countless delta functions, that is, linear combinations of impulse functions, and each delta function can be used to calculate its corresponding point spread function. The point spread function is the image plane light field distribution corresponding to a point light source on the object plane after passing through the system. Taking a traditional lens as an example, P(x, y) is 0 at the position greater than the aperture, and the function value is 1 at the position less than the aperture. The pupil function can be a complex-valued function of position that varies to indicate the absorption of the system, thereby controlling the changes in the transmittance, reflectivity, phase, polarization, etc. of the incident light. For the metasurface, its complex amplitude distribution is the pupil function. By introducing the pupil function P(x, y), the coherent point spread function of the imaging system is derived. The distances between the metasurface and the object plane and the image plane are l1 and l2, respectively. The position of a point source on the object plane is set to (x0, y0). The electric field distribution of the spherical wave emitted by it passing through the position l1 from the point source is:

[0047]

[0048] Assuming that the complex pupil function of the metasurface is P(x1,y1), the distribution of the electric field after passing through the metasurface is expressed as:

[0049] u2(x1,y1)=u1(x1,y1)·P(x1,y1)

[0050] After Fresnel diffraction, the electric field distribution in the image plane at a distance of l2 from the metasurface is:

[0051]

[0052] Apply an additional lens phase function to the metasurface:

[0053]

[0054] Where f represents the focal length of the lens. According to the relationship between the focal length of the lens and the object distance and image distance: So that:

[0055]

[0056]

[0057] make Then the integral term is equal to:

[0058] Where Φ(·) is the Fourier transform, then the electric field distribution u2′(x2,y2) on the image plane, i.e., the point spread function, is:

[0059]

[0060] After obtaining the point spread function, the image plane image is equal to the convolution of the original image and the point spread function, then the image plane field distribution is U(x2,y2)=U(x1,y1)*PSF∝U(x1,y1)*Φ[P(x1,y1)], where * is the convolution operation symbol.

[0061] By making the Fourier transform form of the complex pupil function P(x,y) of the metasurface equivalent to a convolution kernel with a specific function, the metasurface performs image processing and convolution operations. The metasurface performs filtering in the spatial frequency domain by regulating the complex amplitude of the metasurface real space, thereby removing unnecessary spatial frequencies and replacing the linear operation layer in the traditional convolutional neural network.

[0062] like Figure 2 As shown in the figure, to achieve a specific complex amplitude function for the metasurface, this structure responds to circularly polarized light with a wavelength of 780nm. By regulating the length and width of the nanopillars made of α-Si with a period of 400nm, as well as the angle between the long axis and the x-axis, the cross-circular polarization, that is, the conversion efficiency from left-circular to right-circular or right-circular to left-circular, and the geometric phase in the cross-polarization term, is controlled, achieving simultaneous regulation of amplitude and phase. Figure 2 The unit cell structure has a period of 400 nm, with its length and width denoted by L and W, respectively. The height is fixed at 500 nm, and θ is the orientation angle relative to the x-axis. The (L, W) and orientation angles in the xy plane independently control the amplitude and phase of the transmitted light.

[0063] The circularly polarized light carrying the image information is transmitted to the metasurface at l1 in front of the metasurface, and after being modulated by the metasurface, it finally forms a processed image at l2 behind the metasurface. l1 and l2 satisfy the relationship The cross-polarization components are detected by a half-wave plate and a polarizer to obtain image information of the cross-circular polarization state.

[0064] like Figure 1 As shown in (b) and (c), the edge detection image processing operation uses the electric field of the Laguerre-Gaussian beam as a reference for the complex pupil function of the metasurface to perform complex amplitude control. Its donut-shaped amplitude and vortex-shaped phase meet the conditions for performing two-dimensional differential operations, thereby extracting edges in the x and y directions;

[0065] Gaussian filtering image processing operation: The metasurface complex pupil function is modulated in the form of a Gaussian function, so that the metasurface performs a function similar to a low-pass filter, filtering out noise mainly composed of high-frequency signals.

[0066] The metasurfaces corresponding to the above two examples have been prepared by micro-nano processing and experimentally characterized; the complex amplitude modulation and other information used for edge detection and Gaussian filtering are respectively as follows: Figure 3 and Figure 4 shown.

[0067] Figure 3 This is an edge detection metasurface; (a) and (c) are the amplitude and phase distributions of the metasurface under circularly polarized light illumination, respectively. The inset in (a) shows the discretized amplitude distribution, (b) an SEM image of the fabricated metasurface, the diameter of the entire metasurface is 600 μm, and the scale bar is 2 μm, and (d) the measured metasurface intensity distribution. The insets show the simulated (curve) and measured (circle) intensity curves along the blue and orange dashed lines in (a) and (d), respectively.

[0068] Figure 4 The Gaussian filtered metasurface; (a) and (c) are the amplitude and phase distributions of the metasurface under circularly polarized light illumination, respectively. The inset in (a) shows the discretized amplitude distribution. (b) SEM image of the fabricated metasurface, with a diameter of 600 μm and a scale bar of 2 μm. (d) Measured metasurface intensity distribution. The insets show the simulated (curve) and measured (circle) intensity curves along the blue and orange dashed lines in (a) and (d), respectively.

[0069] Example 2: This example is basically the same as the previous example, except that it also includes elliptical nanocolumns made of amorphous silicon as the metasurface backup unit structure. Based on the principle of Fano resonance, the phase and amplitude mutations brought about by the resonance are used to precisely control the amplitude and phase of the light field.

[0070] Experimental example: Compared with existing electrical neural networks, the transmission speed of light is fast, and the optical loss is smaller than the electrical loss. Compared with optical convolutional neural networks, the overall optical computing amount and the number of modules required to be integrated in the system are reduced. Using a spatial light modulator to apply circularly polarized light carrying image information to a micron-sized metasurface device can modulate the amplitude and phase of the optical image, thereby realizing the convolution function and achieving higher integration.

[0071] At present, the edge detection accuracy of most optical convolutional neural networks is about 2-7μm. The edge intensity full width at half maximum obtained by numerical simulation through MATLAB is defined as the detection accuracy, which can reach 1.1μm, and the normalized edge intensity can reach 0.7 and above. Figure 5The edge detection accuracy obtained by simulation and experimental measurement is 2μm and 2.6μm respectively. Figure 6 Compared with the existing technology, a more accurate edge detection result can be obtained.

[0072] At the same time, in order to verify whether the present invention can be used for Gaussian filtering image processing operations, four images with different patterns or noises were selected in the experiment to evaluate the performance of the Gaussian filtering metasurface. Figure 7 The first and third columns from left to right show the input images for simulation and experiment, respectively. In these four images, salt and pepper noise is added to the letters "NJU," the handwritten digits "7," and "5," and Gaussian noise is added to the handwritten digit "7" to verify that this design is effective against various noises. Figure 7 The second and fourth columns from left to right are the denoised image results in simulation and experiment, respectively. Clearly, most of the noise is removed after passing through the metasurface. For quantitative analysis, the present invention introduces peak signal-to-noise ratio (PSNR) as a measure of image quality. The field of view of the present invention is approximately one-sixth of the diameter of the entire device, approximately 100 μm. The entire device has a diameter of 600 μm and a focal length of 2.5 mm. This allows it to be captured and converted into digital signals by a smaller CMOS sensor, making it more suitable for integration.

[0073] From the above, we can see that by purposefully selecting the size and rotation angle of the nanopillars, specific geometric phase and amplitude modulation can be applied to different positions on the incident circularly polarized light field. In principle, the point spread function of the metasurface can correspond to any commonly used neural network convolution kernel. Based on this principle, metasurfaces for arbitrary image operations can be designed. Therefore, they are very compatible with convolutional neural networks and can replace the linear operation layer in convolutional neural networks.

[0074] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (i.e., those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0075] It will be appreciated that in the development of any actual embodiment, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will, for those of ordinary skill having the benefit of this disclosure, be a routine undertaking of design, fabrication, and production without undue experimentation.

[0076] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for designing an image processing metasurface based on complex amplitude modulation, characterized in that: The invention comprises a dielectric metasurface composed of a silicon dioxide substrate and α-Si nanopillars on the substrate. The dielectric nanopillars are arranged in a manner based on the concept of geometric phase physics to make the point spread function of the metasurface equal to the convolution kernel corresponding to the target image processing operation. The image processing operation is performed based on the principle that the response of an image passing through a system corresponds to the convolution of the image and the system's point spread function. By regulating the geometric phase and amplitude of the unit structure, the point spread function of the metasurface is made equal to the convolution kernel, and the image is convolved and processed. Using different orbital quantum numbers and the number of features The complex amplitude of the vortex light is used as the pupil function of the metasurface, and the pupil function of the metasurface, that is, the complex amplitude of the metasurface, is modulated in real space. Since the size and azimuth angle of the nanopillars can be arbitrarily controlled, the complex amplitude of the metasurface can be arbitrarily selected, and any image processing operation can be performed. Edge detection is used to convert the input Gaussian beam into vortex light.

2. The method for designing an image processing metasurface based on complex amplitude modulation according to claim 1, characterized in that: Under monochromatic light illumination, the distribution of a certain object plane image can be decomposed into countless delta functions, that is, linear combinations of impulse functions, and each delta function can be used to calculate its corresponding point spread function. By introducing the complex pupil function P(x, y), the coherent point spread function of the imaging system is derived. The distances between the metasurface and the object plane and the image plane are respectively and , set the position of a point source on the object plane to (x0, y0), and the spherical wave it emits passes through the point source The electric field distribution at the location is: ； Assuming that the complex pupil function of the metasurface is P(x1, y1), the distribution of the electric field after passing through the metasurface is expressed as: ； After Fresnel diffraction, the distance from the metasurface The electric field distribution in the image plane at is: ； ； 。 3. The method for designing an image processing metasurface based on complex amplitude modulation according to claim 2, characterized in that: Apply an additional lens phase function to the metasurface: ； in, Indicates the focal length of the lens, according to the relationship between the focal length of the lens and the object distance and image distance: , such that: ； ； , then the integral term is equal to: ,in is the Fourier transform, then the electric field distribution on the image plane is That is, the point spread function is: ； After obtaining the point spread function, the image plane image is equal to the convolution of the original image and the point spread function, and the image plane field distribution is , where * is the convolution operation symbol.

4. The method for designing an image processing metasurface based on complex amplitude modulation according to claim 3, characterized in that: By making the Fourier transform form of the complex pupil function P(x, y) of the metasurface equivalent to a convolution kernel with a specific function, the metasurface performs image processing and convolution operations. The metasurface performs spatial frequency domain filtering by regulating the complex amplitude of the metasurface real space.

5. The method for designing an image processing metasurface based on complex amplitude modulation according to claim 4, characterized in that: Responding to circularly polarized light with a wavelength of 780 nm, the researchers manipulated the length and width of nanorods made of α-Si with a period of 400 nm, as well as the angle of their long axis relative to the x-axis, controlling the conversion efficiency of cross-circular polarization and the geometric phase in the cross-polarization term, achieving simultaneous control of both amplitude and phase. Circularly polarized light carrying image information passes in front of the metasurface is transferred to the metasurface, modulated by the metasurface, and finally The processed image is formed at and Satisfaction relationship The cross-polarization component is detected by a half-wave plate and a polarizer to obtain the image information of the cross-circular polarization state.

6. The method for designing an image processing metasurface based on complex amplitude modulation according to claim 5, characterized in that: Edge detection image processing: The electric field of the Laguerre-Gaussian beam is used as a reference for the metasurface's complex pupil function to perform complex amplitude control. The donut-shaped amplitude and vortex-shaped phase satisfy the conditions for two-dimensional differential operations, thereby extracting edges in the x and y directions. Gaussian filtering image processing operation: The metasurface complex pupil function is modulated in the form of a Gaussian function, so that the metasurface performs a function similar to a low-pass filter, filtering out noise mainly composed of high-frequency signals.

7. The method for designing an image processing metasurface based on complex amplitude modulation according to claim 1, wherein: It also includes the use of elliptical nanocolumns made of amorphous silicon as the backup unit structure of the metasurface. Based on the principle of Fano resonance, the phase and amplitude mutations brought about by resonance are used to precisely control the amplitude and phase of the light field.

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