Imaging data transmission method and system based on holographic image

Abstract

The invention discloses an imaging data transmission method and system based on a holographic image, and relates to the technical field of image data transmission, and the method comprises the steps: collecting object light, carrying out the plane conversion and frequency spectrum modulation, carrying out the polarization beam splitting and phase modulation of the object light through a geometric phase metal lens, aligning the polarization state of the polarization beam splitting through a polarization analyzer, and carrying out the imaging data transmission. Obtaining a preliminary intensity interferogram; in the phase modulation process, after a Perlin noise function is introduced and a modulation phase and a modulation factor are calculated, amplitude modulation and superposition are carried out, intensity values are obtained and combined, and a final intensity interferogram is formed; according to the method, the anti-noise capability and the interferogram reduction quality in the phase reconstruction process are enhanced, and the phase smooth value matrix and the amplitude matrix are optimized through the genetic algorithm, so that the phase consistency and the amplitude stability in the transmission process are effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of image data transmission, and in particular to a method and system for transmitting imaging data based on holographic images. Background Art

[0002] With the rapid development of holographic imaging, digital optics and efficient image coding technology, holographic images have shown broad application prospects in telemedicine, industrial inspection, digital twins, metaverse and high-precision sensing due to their ability to record and reconstruct real three-dimensional light fields. The development of holographic imaging technology has evolved from traditional dry plate holography to digital holography. Especially in recent years, the combination of computational optics, compressed sensing, phase recovery and spatial light modulator (SLM) technology has greatly improved the efficiency of holographic information acquisition and display. At the same time, with the gradual maturity of 5G and 6G wireless communications and MIMO parallel transmission architectures, remote transmission of holographic data and real-time three-dimensional reconstruction for mobile terminals have become key directions that urgently need breakthroughs.

[0003] However, existing imaging data transmission methods based on holographic images lack customized modulation strategies for the characteristics of holographic data, resulting in phase error accumulation, amplitude distortion and interference pattern degradation. On the other hand, they fail to effectively solve the problem that holographic data is susceptible to multipath interference, random noise and bandwidth limitations in wireless channels. Secondly, in the process of hologram phase reconstruction, existing phase unpacking and noise compensation algorithms mostly rely on iterative methods or optimization methods based on global minimization, which have high computational complexity and poor adaptability to complex backgrounds or strong noise environments. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a holographic imaging data transmission method and system to solve the problems of phase error accumulation, amplitude distortion and poor adaptability to strong noise environments in existing holographic imaging data transmission methods.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a method for transmitting imaging data based on holographic images, which comprises: The object light is collected for plane conversion and spectrum modulation. After polarization splitting and phase modulation of the object light using a geometric phase metal lens, the polarization states of the polarization split beams are aligned using an analyzer to obtain a preliminary intensity interference pattern. The polarization beam splitter includes a phase-modulated object wave and an unmodulated reference wave, and records the initial amplitudes of the two waves; In the phase modulation process, the Perlin noise function is introduced. After calculating the modulation phase and modulation factor, amplitude modulation and superposition are performed to obtain intensity values that are combined to form the final intensity interference pattern. The Hilbert transform method is used to extract the initial wrapping phase from the final intensity interferogram, and the complex wrapping field is constructed. The gradient modulus, perturbation term, and weight of the final intensity interferogram in the horizontal and vertical directions are calculated by the central difference method. A window is set with the spatial position in the final intensity interferogram as the center for traversal to obtain the spatial kernel. Combined with the weight, the phase smoothing value is calculated and combined to obtain the phase smoothing map. The spatial position refers to the spatial position of the pixel; Further, based on the final intensity interference pattern, the maximum amplitude combined with the phase smoothing value is obtained, the complex field complex amplitude is calculated and then propagated to obtain a propagation map, a matrix is constructed, and as an individual, a genetic algorithm is used for iterative optimization. During the iteration, after obtaining the power law value through power law distribution sampling, the mutation and crossover operations are adjusted to obtain the optimal phase smoothing and amplitude matrix. The matrix is transformed using DPAC coding to obtain a double real phase map. The double real phase image is transmitted via a MIMO wireless link, and the complex amplitude field is restored using a reconstruction formula for storage.

[0007] As a preferred solution of the imaging data transmission method based on holographic imaging of the present invention, wherein: the introduction of the Perlin noise function, after calculating the modulation phase and modulation factor, amplitude modulation and superposition are performed to obtain the intensity value, which refers to the use of the pnoise2(.) function to generate a preliminary intensity interference pattern. Perlin noise functions are used, and the amplitude attenuation coefficient and frequency scale of each Perlin noise function are set using empirical rules. Then, sparse noise is calculated, and the maximum modulation phase is set using geometric phase theory. Combined with the sparse noise, the modulation phase of each spatial position is calculated. Using a complex function and the modulation phase, the modulation factor of each spatial position in the preliminary intensity interferogram is calculated. The initial amplitude of the object wave carrying the phase modulation is modulated using the modulation factor. The modulated amplitude is superimposed with the initial amplitude of the reference wave to obtain the total amplitude, which is defined as the intensity value. Arrange the intensity values according to the two-dimensional pixel array to form the final intensity interference map .

[0008] As a preferred embodiment of the imaging data transmission method based on holographic imaging described in the present invention, the traversal of a window with the spatial position in the final intensity interference pattern as the center, obtaining a spatial kernel, and calculating a phase smoothing value in combination with a weight refers to extracting an initial wrapped phase from the final intensity interference pattern using a Hilbert transform method in combination with a forward and reverse tangent function, constructing a corresponding complex wrapped field using a modulation factor formula in combination with the initial wrapped phase, and taking the square of the modulus of the complex wrapped field to obtain a predicted intensity value; calculating the horizontal and vertical gradients of the final intensity interference pattern using a central difference method, and calculating the gradient modulus using a Euclidean norm formula in combination with the horizontal and vertical gradients, and then using an empirical rule to set a disturbance factor, and calculating the disturbance term in combination with the gradient modulus. According to the disturbance term and the intensity value, the error change is calculated. The mean square error formula is used to calculate the average of the sum of squares between the predicted intensity value and the intensity value, which is defined as the adjustment value. The exponential decay function is used to combine the adjustment value and the error change to calculate the weight of each spatial position. The spatial position As the center, and use the empirical rule to set the window, traverse all the neighborhood spatial positions in the window, calculate the position offset between the center and the neighborhood spatial position, and further combine the exponential decay function to calculate the spatial kernel of each neighborhood spatial position; The weight is multiplied by the spatial kernel and then summed to obtain the total weight, which is defined as the normalization factor. The initial wrapped phase, weight, and spatial kernel are then combined to calculate the phase smoothing value of each spatial position in the window. All phase smoothing values are combined to obtain the phase smoothing map.

[0009] As a preferred solution of the imaging data transmission method based on holographic imaging of the present invention, wherein: after obtaining the power-law value by power-law distribution sampling, adjusting the mutation and crossover operations to obtain the optimal phase smoothing and amplitude matrix refers to generating random numbers using a random number generator, sampling the generated random numbers using a power-law distribution sampling method, mapping the sampled random numbers using an inverse CDF method to obtain a power-law value group, and selecting the largest power-law value from the power-law value group using a maximization operation as the perturbation value; Calculate the objective function value and use it as the individual's fitness value. Arrange the individuals in ascending order according to their fitness values, and select the individual with the minimum fitness value as the current optimal individual. According to the optimal individual, the phase smoothing value contained in the optimal individual is disturbed by using the disturbance value to obtain the disturbance phase value, which is defined as the variation value. Repeat the operation to obtain The mutated individuals are trimmed using the trimming operation, and the fitness value is recalculated. The minimum fitness value is obtained using the minimization operation, which is defined as the optimal mutated individual. According to the variation value of the variant individual and the phase smoothing value of the current optimal individual, combined with the disturbance value, the judgment condition is set, and according to the judgment condition, the variation value or phase smoothing value is selected and defined as the crossover value; Repeat the operation to get Crossover individuals, recalculate After calculating the fitness values of the crossover individuals, the minimum fitness value is selected to compare with the fitness value of the current optimal individual. If the minimum fitness value is less than or equal to the fitness value of the current optimal individual, the optimal crossover individual corresponding to the minimum fitness value is replaced with the current optimal individual. Otherwise, the current optimal individual remains unchanged. During the iterative process, when the number of iterations reaches the maximum number, the final individual is output. The final individuals refer to the optimal phase smoothing value matrix and amplitude matrix.

[0010] As a preferred solution of the imaging data transmission method based on holographic imaging of the present invention, wherein: the transmitting of the dual real phase image through the MIMO wireless link and the restoration of the complex amplitude field using the reconstruction formula refers to transmitting the first real phase image and the second real phase image through the MIMO wireless link, and after the first and second real phase images are received by the mobile terminal, further using the complex function to reconstruct the complex amplitude of the complex field; The reconstructed complex field and complex amplitude are input into a spatial light modulator, and the spatial light modulator is irradiated with a laser to obtain a reconstructed 3D holographic image.

[0011] As a preferred solution of the imaging data transmission method based on holographic images described in the present invention, the storage refers to storing the first and second real phase images and the reconstructed complex field complex amplitude in a database, and after storage, adding a timestamp to each data, and then sorting the data with the timestamp through the database.

[0012] As a preferred solution of the imaging data transmission method based on holographic imaging of the present invention, wherein: the collecting object light for plane conversion and spectrum modulation, and the use of a geometric phase metal lens for polarization beam splitting and phase modulation of the object light refers to using a broadband white light LED to illuminate the target object and generating a quasi-parallel light beam through a collimating lens, which is defined as the object light; After the object light is converted to the Fourier plane through a Fourier lens, the spatial frequency mask technology is used for spectrum modulation. The modulated object light is polarization split and phase modulated using a geometric phase metal lens, and the polarization state of the polarization split is aligned using an analyzer to obtain a preliminary intensity interference pattern.

[0013] In a second aspect, the present invention provides an imaging data transmission system based on holographic images, comprising: The acquisition and alignment module is used to collect the object light for plane conversion, spectrum modulation, polarization beam splitting and phase modulation, as well as polarization state alignment to obtain a preliminary intensity interference pattern; The modulation module is used to introduce the Perlin noise function, calculate the modulation phase and modulation factor, perform amplitude modulation and superposition, obtain the intensity value and combine it to form the final intensity interference pattern; The extraction calculation module is used to extract the initial wrapped phase, construct the complex wrapped field, calculate the gradient modulus, disturbance term and weight, set the window for traversal, obtain the spatial kernel, combine the weights, calculate the phase smoothing value and combine them to obtain the phase smoothing map; The propagation module is used to obtain the maximum amplitude combined with the phase smoothing value, calculate the complex amplitude of the complex field, and then propagate it to obtain the propagation map, construct the matrix, and use it as an individual; The optimization coding module is used to obtain the power law value through power law distribution sampling in iteration, adjust the mutation and crossover operations to obtain the optimal phase smoothing and amplitude matrix, and use DPAC coding to transform the matrix to obtain a double real phase map; The transmission storage module is used to transmit the double real phase image through the MIMO wireless link and restore the complex amplitude field by using the reconstruction formula for storage.

[0014] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the imaging data transmission method based on holographic imaging as described in the first aspect of the present invention is implemented.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the imaging data transmission method based on holographic imaging as described in the first aspect of the present invention is implemented.

[0016] The beneficial effects of the present invention are as follows: the present invention introduces a multi-scale Perlin noise function, combines the amplitude attenuation coefficient and the frequency scale, effectively generates a sparse noise field, realizes phase modulation based on geometric phase theory, constructs the modulation factor using a complex function, completes high-robustness amplitude modulation, significantly improves the phase error accumulation and amplitude distortion phenomena, and improves the interference pattern quality from the source. In addition, through the combination of the Hilbert transform method, the central difference method and the weighted space kernel, as well as the extraction of phase wrapping and gradient information, combined with the local disturbance term and the exponential decay weight, high-precision phase smoothing value calculation is achieved, thereby enhancing the anti-noise ability and interference pattern restoration quality in the phase reconstruction process. Secondly, the phase smoothing value matrix and the amplitude matrix are optimized by the genetic algorithm, so that the phase consistency and amplitude stability in the transmission process are effectively guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 This is a flow chart of the imaging data transmission method based on holographic imaging in Example 1.

[0019] Figure 2 This is a structural diagram of the imaging data transmission system based on holographic imaging in Example 1.

[0020] Figure 3 This is a flow chart for obtaining a phase smoothing diagram in Example 1. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0022] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0024] Example 1, with reference to Figures 1-3 , which is the first embodiment of the present invention, provides an imaging data transmission method based on holographic images, comprising the following steps: S1. Collect object light for plane conversion and spectrum modulation, and use a geometric phase metal lens to perform polarization beam splitting and phase modulation on the object light. Then, use a polarization analyzer to align the polarization states of the polarization beam splits to obtain a preliminary intensity interferogram; the polarization beam splits contain a phase-modulated object wave and an unmodulated reference wave, and the initial amplitudes of the two waves are recorded; Specifically, the object light is collected for plane conversion and spectrum modulation, and the object light is polarized and phase modulated using a geometric phase metal lens. This refers to using a broadband white light LED to illuminate the target object and generating a quasi-parallel beam through a collimating lens, which is defined as the object light; After the object light is converted to the Fourier plane through a Fourier lens, the spatial frequency mask technology is used for spectrum modulation. The modulated object light is polarization split and phase modulated using a geometric phase metal lens, and the polarization state of the polarization split is aligned using an analyzer to obtain a preliminary intensity interference pattern.

[0025] Broadband white light sources have better coherence adjustment freedom and higher safety. When combined with a collimating lens, they can achieve highly uniform illumination of the target object. The mask can enhance edge features, and the low-pass mask helps smooth the background, thereby improving the feature contrast and compression robustness of the final interference pattern. The metal lens realizes ultra-fast and ultra-thin wavefront control functions based on the subwavelength structure, which not only improves the phase modulation accuracy, but also can realize full light field operation in a small size. The object light is split into left-handed and right-handed circularly polarized light waves (that is, a beam of object wave carrying phase modulation and a beam of unmodulated reference wave) through a geometric phase lens, and a polarizer is used to overlap the two beams in the same polarization direction. At this time, the light field can be superimposed in space to form an interference pattern. This intensity interference pattern not only carries the light field information of the original object, but also has embedded phase encoding features, providing a high-fidelity data source for subsequent image restoration and phase reconstruction.

[0026] S2. In the phase modulation process, the Perlin noise function is introduced. After the modulation phase and modulation factor are calculated, amplitude modulation and superposition are performed to obtain intensity values for combination to form the final intensity interference pattern. Specifically, the Perlin noise function is introduced, and after calculating the modulation phase and modulation factor, amplitude modulation and superposition are performed to obtain the intensity value. The pnoise2(.) function is used to generate the preliminary intensity interference pattern. Perlin noise functions are used, and the amplitude attenuation coefficient and frequency scale of each Perlin noise function are set using empirical rules to calculate the sparse noise. The formula is: Where, Represents the spatial position in the preliminary intensity interference pattern The sparse noise at represents the total number of Perlin noise functions, Indicates the The amplitude attenuation coefficient of the Perlin noise function, Indicates the The frequency scale of the Perlin noise function, represents the Perlin noise function, Represents the spatial position in the preliminary intensity interference pattern The scale position at The maximum modulation phase is set using geometric phase theory, and the modulation phase at each spatial position is calculated using sparse noise. The formula is: Where, Represents the spatial position in the preliminary intensity interference pattern The modulation phase at Indicates the maximum modulation phase; The modulation factor at each spatial position in the preliminary intensity interferogram is calculated using a complex function combined with the modulation phase, as follows: Where, Represents the spatial position in the preliminary intensity interference pattern The modulation factor at represents the base of natural logarithm, Represents a rotation operation; The initial amplitude of the phase modulated object wave is modulated using the modulation factor, which is: Where, represents the amplitude after modulation, represents the initial amplitude of the object wave carrying the phase modulation; The modulated amplitude is superimposed on the initial amplitude of the reference wave to obtain the total amplitude, which is defined as the intensity value. The formula is: Where, Indicates the intensity value, represents the modulus length of a complex number, represents the initial amplitude of the reference wave; Arrange the intensity values according to the two-dimensional pixel array to form the final intensity interference map .

[0027] The sparse disturbance field is generated by Perlin noise with multiple frequency scales and attenuation weights, which can effectively simulate the background noise, speckle, or diffraction artifacts in the spatial non-uniform interference system. This not only improves the local detail expression ability of the intensity interference pattern, but also reduces the structural repeatability in the modulation process and improves image differentiation. By setting the maximum geometric phase, the sparse noise is linearly mapped to the modulation phase space, thereby ensuring that the modulation phase is in the physically allowed range and avoiding periodic errors caused by phase crossing the boundary. This step ensures the physical consistency of the modulation phase and controls the maximum influence range of the phase disturbance, which is conducive to improving the robustness of the present invention. Rod property, and the modulated phase is embedded in the complex exponential function to form a modulation factor, which is then multiplied with the original object wave amplitude to achieve local phase perturbation rather than amplitude perturbation. This step keeps the amplitude unchanged, avoids destroying the original light field energy distribution, and enhances the detail complexity of the interference fringes, which is beneficial to optical encoding. Secondly, by superimposing the complex amplitude with the reference wave, the total field intensity distribution is obtained and output in a two-dimensional pixel array. This process retains the light field interference information after phase modulation, and this step provides a high-contrast interference pattern, which is convenient for the recognition of digital holography or deep learning, enhances the sensitivity of the interference pattern to structural changes, and improves the visibility of tiny features.

[0028] S3. Extracting the initial wrapped phase from the final intensity interferogram using the Hilbert transform method and constructing a complex wrapped field. Calculating the horizontal and vertical gradient moduli, perturbation terms, and weights of the final intensity interferogram using the central difference method. Traversing the final intensity interferogram using a window centered on the spatial position in the final intensity interferogram to obtain a spatial kernel, calculate the phase smoothing value based on the weights, and combine the values to obtain a phase smoothing map. The spatial position refers to the spatial position of the pixel point. Specifically, the Hilbert transform method is used to extract the initial wrapping phase from the final intensity interferogram, and the complex wrapping field is constructed by using the Hilbert transform method combined with the forward and reverse tangent functions to extract the initial wrapping phase from the final intensity interferogram. The formula is: Where, represents the initial wrapping phase, represents the inverse tangent function, represents the Hilbert transform operation, represents the final intensity interferogram; Using the formula of the modulation factor and the initial wrapping phase, the corresponding complex wrapping field is constructed, and the square of the modulus length of the complex wrapping field is taken to obtain the predicted intensity value; The phase field is constructed by performing local analytical operations through Hilbert transform, which has the advantages of strong immunity to noise and suitability for single-frame data extraction. This step can be implemented in the spatial domain, avoiding the sideband interference introduced in the frequency domain operation. Using the tangent function to extract the phase from the Hilbert can accurately restore the local phase distribution, avoiding the defect of ambiguity that the traditional inverse cosine function is prone to, which helps to construct a high-precision wrapped phase map and lay the foundation for subsequent complex field construction. The extracted wrapped phase is embedded in the complex exponential function to obtain a complex light field form with phase information. The complex wrapped field not only contains spatial phase change information, but also can be superimposed with an amplitude modulation factor for field encoding processing. By taking the square of the modulus length of the complex wrapped field, a predicted intensity value consistent with the actual interference pattern intensity distribution can be obtained. The predicted intensity value can be used for error calculation, constraint condition construction, or reverse correction of the modulation factor, which helps to improve the quality of holographic image restoration.

[0029] Furthermore, the gradient modulus, disturbance term and weight of the final intensity interference pattern in the horizontal and vertical directions are calculated, and a window is set with the spatial position in the final intensity interference pattern as the center for traversal to obtain the spatial kernel. Combined with the weight, the phase smoothing value is calculated and combined to obtain the phase smoothing map. The horizontal and vertical gradients of the final intensity interference pattern are calculated using the central difference method, and the gradient modulus is calculated by combining the horizontal and vertical gradients using the Euclidean norm formula. The disturbance factor is then set using the empirical rule, and the disturbance term is calculated by combining the gradient modulus. The formula is: Where, represents the perturbation term of the final intensity interferogram, represents the disturbance factor, represents the gradient modulus of the final intensity interferogram; According to the disturbance term and intensity value, the error change is calculated as follows: Where, represents the error variation of the final intensity interferogram, represents the square of a real number, represents the predicted strength value; Using the mean square error formula, the average of the sum of squares between the predicted intensity value and the intensity value is calculated, which is defined as the adjustment value. Then, using the exponential decay function, the weight of each spatial position is calculated by combining the adjustment value and the error change. The formula is: Where, Represents the spatial position of the final intensity interference pattern The weight of represents an exponential decay function, Indicates the adjustment value; The spatial position As the center, and use the empirical rule to set the window, traverse all the neighborhood spatial positions in the window, calculate the position offset between the center and the neighborhood spatial position, and further combine the exponential decay function to calculate the spatial kernel of each neighborhood spatial position. The formula is: Where, Represents the neighborhood spatial location The space core, Represents the spatial scale factor, which can be set through relevant domain knowledge or experiments. represents the square of Euclidean distance; The weight is multiplied by the spatial kernel and then summed to obtain the total weight, which is defined as the normalization factor. The initial wrapped phase, weight, and spatial kernel are then combined to calculate the phase smoothing value of each spatial position in the window. The formula is: Where, Represents the spatial position of the final intensity interference pattern The phase smoothing value of Indicates the window, represents the normalization factor; All phase smoothing values are combined to obtain a phase smoothing map.

[0030] The central difference method, as a difference method with high numerical stability and moderate accuracy, can effectively extract edge information in the horizontal and vertical directions of the image, improve the accuracy of gradient modulus calculation, and has lower discretization error than traditional forward or backward difference methods. The gradient modulus is used as a significance indicator of image structure change, and its product with the disturbance factor constitutes a disturbance term. This enables the present invention to give high gradient areas a stronger response ability in the error term construction, thereby enhancing the robustness to complex texture areas and suppressing the pseudo-error response of smooth areas. The construction of the error change is used to measure the degree of change between the predicted intensity and the target intensity before and after the introduction of the disturbance, which can be used to evaluate the optimization direction of the results after interference image reconstruction. The comparison of square differences helps to dynamically adjust the subsequent weight allocation strategy. By defining the adjustment value (i.e., the mean square error between the predicted intensity and the target intensity) and combining the error change, an exponential decay function is introduced as the basis for weight calculation, which can effectively control the impact of abnormal errors. response range, realizing adaptive information filtering and feature retention. Secondly, using a fixed window centered on the spatial position is helpful for integrating the local information of the image. The spatial kernel controls the influence of the neighborhood range through the spatial scale factor, enhancing the spatial consistency and noise resistance of the algorithm. The spatial kernel is multiplied and fused with the error weight to avoid numerical deviations caused by differences in the number or intensity of neighborhood pixels. This mechanism takes into account the dual regulation of structural correlation and dynamic response of error, and improves the stability and accuracy of phase estimation. By combining the phase values of each pixel point in the neighborhood in a weighted sum manner, a phase smoothing map is finally obtained, which effectively removes the phase jumps caused by optical system errors, sensor noise, etc. in the interference map.

[0031] S4. Further, based on the final intensity interference pattern, the maximum amplitude combined with the phase smoothing value is obtained, the complex field complex amplitude is calculated and propagated to obtain a propagation map, a matrix is constructed, and as an individual, a genetic algorithm is used for iterative optimization. During the iteration, after obtaining the power law value through power law distribution sampling, the mutation and crossover operations are adjusted to obtain the optimal phase smoothing and amplitude matrix, and the matrix is transformed using DPAC coding to obtain a double real phase map; Specifically, the maximum amplitude is obtained based on the final intensity interference pattern, combined with the phase smoothing value, and the complex amplitude of the complex field is calculated and propagated to obtain a propagation map. The matrix is constructed and used as an individual to perform iterative optimization using a genetic algorithm. The maximum modulation amplitude is obtained based on the final intensity interference pattern. The formula is: Where, Indicates the maximum modulation amplitude obtained, Indicates the maximum value operation; The complex function is further used to combine the phase smoothing value and the initial amplitude to calculate the complex amplitude of the complex field. The formula is: Where, represents the complex field complex amplitude; The complex field complex amplitude includes amplitude and phase; Use the angular spectrum propagation method to propagate the light field using the complex field complex amplitude, and obtain the complex amplitude of the light field on another plane. Then take the complex modulus square of the complex amplitude of the light field, which is defined as the intensity of the complex amplitude of the light field, and then combine them to obtain the propagation map; Use the mean and standard deviation formula to obtain the propagation map and phase smoothing map, their respective means and standard deviations, and combine them using the covariance formula based on their respective means to obtain the covariance; According to the phase smoothing map and the propagation map, the phase smoothing value matrix and the amplitude matrix are constructed respectively. The phase smoothing value matrix and the amplitude matrix are used as individuals in the genetic algorithm to randomly generate a population for initialization. Define the objective function and minimize the objective function value. The formula is: Where, represents the objective function value, and represents the mean and standard deviation of the phase smoothing plot, and represents the mean and standard deviation of the propagation map, represents the covariance between the means of the phase smoothing map and the propagation map; By extracting the maximum modulation amplitude in the final interference pattern and establishing the upper bound of amplitude recovery, it is convenient to modulate the reconstructed complex amplitude in a physically consistent manner, effectively avoiding abnormal gain or phase nonlinear expansion. The phase smoothing value can be fused with the initial amplitude, and the complex field complex amplitude is calculated using a complex function, thereby ensuring phase continuity and amplitude edge retention before the light field propagates, enhancing the spatial fidelity of subsequent propagation patterns, and using the angular spectrum propagation method to propagate the complex field complex amplitude to a new plane, which not only expands the information carrying dimension of the two-dimensional interference pattern, but also provides a real physical basis for multi-scale phase optimization, meeting the needs of three-dimensional information reconstruction, and combining the two The statistical fusion of images and the construction of collaborative optimization objectives can effectively suppress local optimality and enhance the coupling matching of phase and amplitude in the reconstruction process, reflecting the integrated fusion of statistical modeling and light field characteristics. The phase matrix and amplitude matrix are combined into individual structures, and the genetic algorithm is used for group evolution search, so that the search space has stronger expressiveness and fitness improvement capabilities within the light field propagation dimension. The constructed objective function integrates the mean difference, variance matching and covariance coupling between the two images, so that the optimization process takes into account both local brightness consistency and overall structural coordination, thereby improving the stability and accuracy of phase inversion and amplitude reconstruction.

[0032] Furthermore, after obtaining the power-law value through power-law distribution sampling, the mutation and crossover operations are adjusted to obtain the optimal phase smoothing and amplitude matrix, and the matrix is transformed using DPAC coding to obtain a double real phase map. A random number generator is used to generate random numbers, and the generated random numbers are sampled using the power-law distribution sampling method. The sampled random numbers are then mapped using the inverse CDF method to obtain a power-law value group, and the maximum power-law value is selected from the power-law value group as the perturbation value using a maximization operation. Calculate the objective function value and use it as the individual's fitness value. Arrange the individuals in ascending order according to their fitness values, and select the individual with the minimum fitness value as the current optimal individual. According to the optimal individual, the phase smoothing value contained in the optimal individual is disturbed by using the disturbance value to obtain the disturbance phase value, which is defined as the variation value. The formula is: Where, represents the variation value, represents the disturbance value, represents the phase smoothing value; Repeat the operation to get The mutated individuals are trimmed using the trimming operation, and the fitness value is recalculated. The minimum fitness value is obtained using the minimization operation, which is defined as the optimal mutated individual. According to the variation value of the variation individual and the phase smoothing value of the current optimal individual, combined with the disturbance value, the judgment condition is set, and according to the judgment condition, the variation value or phase smoothing value is selected, which is defined as the crossover value. The formula is: Where, represents the crossover value, Indicates otherwise; Repeat the operation to get Crossover individuals, recalculate After calculating the fitness values of the crossover individuals, the minimum fitness value is selected to compare with the fitness value of the current optimal individual. If the minimum fitness value is less than or equal to the fitness value of the current optimal individual, the optimal crossover individual corresponding to the minimum fitness value is replaced with the current optimal individual. Otherwise, the current optimal individual remains unchanged. During the iterative process, when the number of iterations reaches the maximum number, the final individual is output. The final individuals refer to the optimal phase smoothing value matrix and amplitude matrix; Get the amplitude value from the amplitude matrix, use DPAC encoding technology, combine the amplitude value, and calculate the phase encoding value. The formula is: Where, represents the phase encoding value, represents the inverse cosine function, represents the amplitude value obtained from the amplitude matrix; All phase encoding values are combined to obtain a first real phase map, and the optimal phase smoothing value matrix is reconstructed into an image as a second real phase map.

[0033] Through the non-uniform perturbation mechanism guided by the power-law distribution, individuals can not only achieve local high-precision fine-tuning in the search space, but also jump out of the local minimum area with a certain probability, thereby effectively preventing the optimization process from falling into the problem of premature convergence, significantly enhancing the global search capability and the diversity of solutions, and the long-tail characteristics of the power-law distribution allow large-amplitude perturbations and small-amplitude perturbations to be adaptively used alternately at different stages, so that the genetic algorithm of the present invention takes into account both exploration and convergence. Traditional Gaussian perturbations or uniform perturbations are prone to stagnation in low-gradient areas or out-of-control perturbations at strong edges. The present invention can maintain the stability of the perturbation while maintaining the stability of the perturbation based on power-law sampling. According to the characteristics of the local objective function, the disturbance amplitude is dynamically adjusted. By adjusting the power exponential parameter of the power law distribution and the disturbance intensity factor, the disturbance behavior can be flexibly controlled, so that the genetic algorithm in the present invention can show excellent robustness and adaptability. By synchronously optimizing the phase smoothing matrix and the amplitude matrix, the present invention can achieve coordinated control between amplitude modulation and phase continuity, effectively reducing the reconstruction error caused by phase mutation. The DPAC coding strategy is introduced to explicitly integrate the amplitude information into the phase expression during the coding process, which makes up for the problem that the traditional single-phase modulation is insufficient in expressing the light field transmission characteristics, and greatly improves the generation The expressive power, coherence consistency and optical feasibility of the phase image are enhanced, and DPAC coding has a strong energy concentration characteristic in the frequency domain, which helps to improve the anti-interference performance and image fidelity in holographic reconstruction. Secondly, in the generated double real phase image, one image carries the amplitude modulation information, and the other is used to express the phase smoothing value. The two work together to respectively realize the amplitude control and phase control of the light wave in practical applications. Through the dual-channel structure, the functions of modulation and reconstruction error compensation are effectively separated, so that the present invention still has a high imaging stability and error suppression capability under conditions of complex optical paths or large physical noise. Therefore, the dual-phase mechanism can significantly improve the overall performance and physical implementation capabilities of the present invention. In addition, a clipping operation is introduced during the evolutionary optimization process to perform bounded adjustments on the perturbation values in the mutated individuals that exceed the preset physical boundaries or violate numerical stability. This not only effectively limits the uncontrollability of the solution space expansion, but also prevents the generation of non-physical or invalid individuals. At the same time, it also increases the proportion of high-quality solutions in each round of iteration, thereby accelerating the overall optimization convergence process. In the context of the fitness evaluation criterion not having strong convexity or the solution space being nonlinear and complex, the clipping mechanism enables the present invention to maintain the overall stability of the algorithm while ensuring the rationality of the optimization.

[0034] S5. Transmitting the double real phase image via a MIMO wireless link and restoring the complex amplitude field using a reconstruction formula for storage; Specifically, the double real phase image is transmitted through the MIMO wireless link, and the complex amplitude field is restored using the reconstruction formula. The first real phase image and the second real phase image are transmitted through the MIMO wireless link, and after the first and second real phase images are received by the mobile terminal, the complex field complex amplitude is further reconstructed using a complex function. The formula is: Where, represents the complex amplitude of the reconstructed complex field, represents the cosine function, Indicates counterclockwise rotation operation. represents the second real phase diagram; The reconstructed complex field and complex amplitude are input into a spatial light modulator, and the spatial light modulator is irradiated with a laser to obtain a reconstructed 3D holographic image.

[0035] By decomposing the complex amplitude information into two real phase images, the data complexity and compression ratio can be significantly reduced, and it is compatible with current mainstream MIMO wireless communication protocols (such as 5G NR). Compared with directly transmitting complex data, the present invention significantly improves the real-time transmission efficiency. After the reconstructed complex amplitude field is loaded into the spatial light modulator (SLM), the real wavefront is reproduced through phase modulation. After laser irradiation, the interference wave identical to the original object is generated, forming a visual 3D image.

[0036] Furthermore, storing refers to storing the first and second real phase images and the reconstructed complex field complex amplitude in a database, and after storing, adding a timestamp to each data, and then sorting the timestamped data through the database.

[0037] By adding timestamps and sorting the stored data, a clear "data timeline" is formed, which supports subsequent comparative analysis between different versions of phase diagrams or complex amplitudes.

[0038] This embodiment also provides an imaging data transmission system based on holographic images, including: The acquisition and alignment module is used to collect the object light for plane conversion, spectrum modulation, polarization beam splitting and phase modulation, as well as polarization state alignment to obtain a preliminary intensity interference pattern; The modulation module is used to introduce the Perlin noise function, calculate the modulation phase and modulation factor, perform amplitude modulation and superposition, obtain the intensity value and combine it to form the final intensity interference pattern; The extraction calculation module is used to extract the initial wrapped phase, construct the complex wrapped field, calculate the gradient modulus, disturbance term and weight, set the window for traversal, obtain the spatial kernel, combine the weights, calculate the phase smoothing value and combine them to obtain the phase smoothing map; The propagation module is used to obtain the maximum amplitude combined with the phase smoothing value, calculate the complex amplitude of the complex field, and then propagate it to obtain the propagation map, construct the matrix, and use it as an individual; The optimization coding module is used to obtain the power law value through power law distribution sampling in iteration, adjust the mutation and crossover operations to obtain the optimal phase smoothing and amplitude matrix, and use DPAC coding to transform the matrix to obtain a double real phase map; The transmission storage module is used to transmit the double real phase image through the MIMO wireless link and restore the complex amplitude field by using the reconstruction formula for storage.

[0039] This embodiment also provides a computer device, which is suitable for the imaging data transmission method based on holographic images, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the imaging data transmission method based on holographic images proposed in the above embodiment. The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0040] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the imaging data transmission method based on holographic images proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0041] 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 holographic imaging data transmission method, characterized in that: include, The object light is collected for plane conversion and spectrum modulation. After polarization splitting and phase modulation of the object light using a geometric phase metal lens, the polarization states of the polarization split beams are aligned using an analyzer to obtain a preliminary intensity interference pattern. The polarization beam splitter includes a phase-modulated object wave and an unmodulated reference wave, and records the initial amplitudes of the two waves; In the phase modulation process, the Perlin noise function is introduced. After calculating the modulation phase and modulation factor, amplitude modulation and superposition are performed to obtain intensity values that are combined to form the final intensity interference pattern. The Hilbert transform method is used to extract the initial wrapping phase from the final intensity interferogram, and the complex wrapping field is constructed. The gradient modulus, perturbation term, and weight of the final intensity interferogram in the horizontal and vertical directions are calculated by the central difference method. A window is set with the spatial position in the final intensity interferogram as the center for traversal to obtain the spatial kernel. Combined with the weight, the phase smoothing value is calculated and combined to obtain the phase smoothing map. The spatial position refers to the spatial position of the pixel; Further, based on the final intensity interference pattern, the maximum amplitude combined with the phase smoothing value is obtained, the complex field complex amplitude is calculated and then propagated to obtain a propagation map, a matrix is constructed, and as an individual, a genetic algorithm is used for iterative optimization. During the iteration, after obtaining the power law value through power law distribution sampling, the mutation and crossover operations are adjusted to obtain the optimal phase smoothing and amplitude matrix. The matrix is transformed using DPAC coding to obtain a double real phase map. The double real phase image is transmitted via a MIMO wireless link, and the complex amplitude field is restored using a reconstruction formula for storage.

2. The holographic imaging data transmission method according to claim 1, wherein: The introduction of the Perlin noise function, calculation of the modulation phase and modulation factor, and then amplitude modulation and superposition to obtain the intensity value refers to using the pnoise2(.) function to generate Y Perlin noise functions for the preliminary intensity interference pattern, and using empirical rules to set the amplitude attenuation coefficient and frequency scale of each Perlin noise function, calculating the sparse noise, using the geometric phase theory to set the maximum modulation phase, and combining the sparse noise to calculate the modulation phase of each spatial position; Using a complex function and the modulation phase, the modulation factor of each spatial position in the preliminary intensity interferogram is calculated. The initial amplitude of the object wave carrying the phase modulation is modulated using the modulation factor. The modulated amplitude is superimposed with the initial amplitude of the reference wave to obtain the total amplitude, which is defined as the intensity value. The intensity values are arranged in a two-dimensional pixel array to form a final intensity interference map D.

3. The holographic imaging data transmission method according to claim 2, wherein: The traversal of the window set with the spatial position in the final intensity interferogram as the center, obtaining the spatial kernel, combining the weights, and calculating the phase smoothing value refers to extracting the initial wrapped phase from the final intensity interferogram using the Hilbert transform method in combination with the forward and reverse tangent functions, constructing the corresponding complex wrapped field using the formula of the modulation factor in combination with the initial wrapped phase, taking the square of the modulus of the complex wrapped field to obtain the predicted intensity value; using the central difference method to calculate the horizontal and vertical gradients of the final intensity interferogram, and using the Euclidean norm formula in combination with the horizontal and vertical gradients to calculate the gradient modulus, and then using the empirical rule to set the disturbance factor, and combining the gradient modulus to calculate the disturbance term; According to the disturbance term and the intensity value, the error change is calculated. The mean square error formula is used to calculate the average of the sum of squares between the predicted intensity value and the intensity value, which is defined as the adjustment value. The exponential decay function is used to combine the adjustment value and the error change to calculate the weight of each spatial position. The spatial position As the center, and use the empirical rule to set the window, traverse all the neighborhood spatial positions in the window, calculate the position offset between the center and the neighborhood spatial position, and further combine the exponential decay function to calculate the spatial kernel of each neighborhood spatial position; The weight is multiplied by the spatial kernel and then summed to obtain the total weight, which is defined as the normalization factor. The initial wrapped phase, weight, and spatial kernel are then combined to calculate the phase smoothing value of each spatial position in the window. All phase smoothing values are combined to obtain the phase smoothing map.

4. The holographic imaging data transmission method according to claim 3, wherein: After obtaining the power-law value through power-law distribution sampling, adjusting the mutation and crossover operations to obtain the optimal phase smoothing and amplitude matrix refers to using a random number generator to generate random numbers, and after sampling the generated random numbers using a power-law distribution sampling method, mapping the sampled random numbers using an inverse CDF method to obtain a power-law value group, and using a maximization operation to select the largest power-law value from the power-law value group as the perturbation value; Calculate the objective function value and use it as the individual's fitness value. Arrange the individuals in ascending order according to their fitness values, and select the individual with the minimum fitness value as the current optimal individual. According to the optimal individual, use the perturbation value to perturb the phase smoothing value contained in the optimal individual to obtain the perturbation phase value, which is defined as the mutation value. Repeat the operation to obtain m mutant individuals. Use the trimming operation to trim the mutation value in the mutant individual and recalculate the fitness value. Then use the minimization operation to obtain the minimum fitness value, which is defined as the optimal mutant individual. According to the variation value of the variant individual and the phase smoothing value of the current optimal individual, combined with the disturbance value, the judgment condition is set, and according to the judgment condition, the variation value or phase smoothing value is selected and defined as the crossover value; Repeat the operation to obtain u crossover individuals. After recalculating the fitness values of u crossover individuals, select the minimum fitness value and compare it with the fitness value of the current optimal individual. If the minimum fitness value is less than or equal to the fitness value of the current optimal individual, then replace the optimal crossover individual corresponding to the minimum fitness value with the current optimal individual. Otherwise, keep the current optimal individual unchanged. During the iterative process, when the number of iterations reaches the maximum number, output the final individual. The final individuals refer to the optimal phase smoothing value matrix and amplitude matrix.

5. The holographic imaging data transmission method according to claim 4, wherein: The transmitting of the double real phase image through the MIMO wireless link and restoring the complex amplitude field using the reconstruction formula refers to transmitting the first real phase image and the second real phase image through the MIMO wireless link, and after the first and second real phase images are received by the mobile terminal, further reconstructing the complex amplitude of the complex field using a complex function; The reconstructed complex field and complex amplitude are input into a spatial light modulator, and the spatial light modulator is irradiated with a laser to obtain a reconstructed 3D holographic image.

6. The method for transmitting imaging data based on holographic images according to claim 5, wherein: The storing refers to storing the first and second real phase images and the reconstructed complex field complex amplitude in a database, and after storing, adding a timestamp to each data, and then sorting the data with the timestamp through the database.

7. The method for transmitting imaging data based on holographic images according to claim 6, wherein: The object light is collected for plane conversion and spectrum modulation, and the object light is polarized and phase modulated by using a geometric phase metal lens. This refers to using a broadband white light LED to illuminate the target object and generating a quasi-parallel light beam through a collimating lens, which is defined as the object light; After the object light is converted to the Fourier plane through a Fourier lens, the spatial frequency mask technology is used for spectrum modulation. The modulated object light is polarization split and phase modulated using a geometric phase metal lens, and the polarization state of the polarization split is aligned using an analyzer to obtain a preliminary intensity interference pattern.

8. A holographic imaging data transmission system, based on the holographic imaging data transmission method according to any one of claims 1 to 7, characterized in that: include, The acquisition and alignment module is used to collect the object light for plane conversion, spectrum modulation, polarization beam splitting and phase modulation, as well as polarization state alignment to obtain a preliminary intensity interference pattern; The modulation module is used to introduce the Perlin noise function, calculate the modulation phase and modulation factor, perform amplitude modulation and superposition, obtain the intensity value and combine it to form the final intensity interference pattern; The extraction calculation module is used to extract the initial wrapped phase, construct the complex wrapped field, calculate the gradient modulus, disturbance term and weight, set the window for traversal, obtain the spatial kernel, combine the weights, calculate the phase smoothing value and combine them to obtain the phase smoothing map; The propagation module is used to obtain the maximum amplitude combined with the phase smoothing value, calculate the complex amplitude of the complex field, and then propagate it to obtain the propagation map, construct the matrix, and use it as an individual; The optimization coding module is used to obtain the power law value through power law distribution sampling in iteration, adjust the mutation and crossover operations to obtain the optimal phase smoothing and amplitude matrix, and use DPAC coding to transform the matrix to obtain a double real phase map; The transmission storage module is used to transmit the double real phase image through the MIMO wireless link and restore the complex amplitude field by using the reconstruction formula for storage.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the imaging data transmission method based on holographic imaging according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the imaging data transmission method based on holographic imaging according to any one of claims 1 to 7 are implemented.

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