21 results about "Phase retrieval" patented technology

The invention relates to methods and apparatuses for reconstructing phase information in a time series, the time series being derived from a time evolution of an input state acted on by a Hamiltonian, H. First, an input state, |ψ, a total time evolution time, T, and the Hamiltonian, H are received. Next a time evolution of the input state is enacted, using H to generate an absolute value of a first time series, |f1|. In addition at least one additional family of absolute values of time series is generated, each time series being a discrete or continuous function of time t, for t∈[0,T]. Finally, phase information is extracted for the time series of the input state from the absolute values of the first time series and the at least one additional family of absolute values of time series.

The invention relates to the technical field of underwater imaging, provides a Fourier lamination underwater imaging system and method based on adaptive phase retrieval, and effectively solves the problem of insufficient imaging resolution caused by a strong scattering effect of a water body and aperture limitation of an optical system in a traditional underwater imaging technology. According to the method, the Fourier lamination imaging technology is applied to the underwater environment for the first time, and the spatial resolution is improved by 2.24 times compared with that of a traditional method in combination with the self-adaptive phase retrieval algorithm. Further experiments show that even under the strong scattering condition, the scheme can still keep the resolution performance obviously superior to that of a traditional method. The invention provides a novel underwater high-resolution imaging technical scheme, the imaging performance of marine resource exploration and underwater engineering facility detection can be remarkably improved, and the method has important application value.

The application discloses a digital phase-shifting phase recovery method of ESPI fringe pattern based on distance mapping, which comprises the following steps: 1) extracting the direction of each pixel point of the fringe pattern, and then calculating the normal curve of the fringe according to the fringe direction to obtain the moving direction of the fringe; 2) extracting the center line of the dark fringe, calculating the width of the fringe according to the center line of the fringe, and obtaining the moving distance of the fringe through distance mapping; 3) comprehensively moving the direction and the distance, and performing digital phase-shifting on the initial fringe pattern point by point, and adopting the bilinear gray interpolation to obtain the fringe pattern after digital phase-shifting; 4) calculating the wrapped phase corresponding to the fringe pattern; and 5) performing unwrapping processing on the wrapped phase to recover the full-field phase of the fringe pattern. The application extracts the phase through the digital image processing technology on the single fringe pattern, avoids the problem of inaccurate phase-shifting existing in the traditional physical phase-shifting technology in dynamic measurement, and can effectively improve the accuracy of the phase recovery of the single fringe pattern.

This invention discloses a phase retrieval method for bright-field microscopy based on uniform light intensity, belonging to the technical field of phase retrieval in optical measurement. The method includes: acquiring focused light intensity images, positive defocus images, and negative defocus images along the optical axis; calculating the axial differential of light intensity using the finite difference method; simplifying the light intensity transmission equation to a Poisson equation and solving the Poisson equation to obtain the initial phase; constructing a positive higher-order error compensation model for the axial differential of light intensity and solving for the phase; and using a gradient acceleration strategy to iteratively calculate the phase to obtain the final phase result. This invention significantly improves the stability and accuracy of phase retrieval. Simultaneously, by combining angular spectrum theory to construct an axial differential higher-order error compensation model and introducing a gradient acceleration strategy, it effectively corrects defocus errors, greatly improves iterative convergence efficiency, and enhances the applicability of the method in practical microscopic imaging scenarios.

This invention discloses a single-frame coded phase retrieval system and parameter calibration method based on iterative filtering inversion, belonging to the field of lensless computational microscopy imaging technology. It solves the problems of mismatch between single-frame coded phase retrieval algorithms and complex coding scenarios, difficulty in balancing noise suppression and resolution, large system diffraction distance estimation errors, and inaccurate wavefront lateral offset calibration, leading to low imaging accuracy and poor stability. This invention constructs a system including a light source, replaceable amplitude / phase coding, CMOS imaging, one-dimensional electric displacement drive, and a built-in IrCPR algorithm control module, along with a process of "multi-distance calibration of coding functions → Z1 / Z2 calibration using ToG / SG according to coding board type → cross-correlation spectrum registration." This invention improves the accuracy of coding function calibration and diffraction distance estimation, achieves pixel-level alignment of the coded wavefront, and completes complex amplitude reconstruction with a single frame acquisition. The system has strong adaptability and stability, making it suitable for high-precision microscopy imaging scenarios.

A synthetic aperture quantitative phase imaging method based on a hybrid of digital holography and Fourier ptychography. A programmable LED array which is annularly arranged is mounted on an off-axis digital holographic system for providing oblique illumination at varying angles; accurate noise-containing low-frequency information of an object is obtained by means of digital holography and is used as initial estimation; and then, high-frequency information of the object is reconstructed by means of a Fourier ptychographic algorithm based on intensity measurement, so as to realize synthetic aperture quantitative phase imaging. Using the accurate low frequency provided by holography as initial estimation ensures the accuracy of phase retrieval and wavefront aberration reconstruction, without strictly meeting matching illumination conditions, and reduces the number of intensity graphs required by Fourier ptychography; and a non-interferometric phase retrieval method based on Fourier ptychography improves the imaging resolution to an incoherent diffraction limit, and also effectively solves the problem of inherent speckle noise in digital holography.

This invention discloses a method and system for integrated communication and sensing based on a large-scale intelligent reflector-assisted system. First, the invention characterizes the problems of channel estimation, beamforming design, and user location estimation during large-scale model training. Then, it designs a multi-task context learning mechanism, heterogeneous data reconstruction, and three network modules to organically incorporate three physically semantically distinct integrated communication and sensing tasks—channel estimation, beamforming design, and user location—into a unified model. Based on the uplink pilot signal sent by the user, the invention achieves the aforementioned three typical integrated communication and sensing tasks. Furthermore, this invention provides a differentiable reparameterized phase retrieval strategy for intelligent reflector phase shift, ensuring that the model output strictly meets hardware physical constraints. This overcomes the limitation of existing networks that can only handle single tasks, providing an efficient solution for large-scale intelligent reflector-assisted integrated communication and sensing.

This application belongs to the field of light field display technology, specifically disclosing a rigorous scalar light field calculation and solution method and system. It includes: obtaining the complex amplitude distribution on the source plane; and calculating the rigorous scalar light field distribution on the observation plane based on rigorous scalar diffraction theory and the complex amplitude distribution on the source plane. Based on scalar diffraction theory, this application constructs a light field propagation model for arbitrary propagation distances, avoids approximation errors in geometric correction methods through a rigorous scalar light field propagation method, overcomes the propagation distance constraints of the scalable angular spectrum propagation model, and achieves Abbe diffraction-limited resolution through a phase retrieval algorithm.

Herein is presented a method for the adaptive correction of images comprises the steps: (a) capturing a first image with an image capture device; (b) selecting within the first image at least one candidate point and at least two test points; (c) using an iterative phase retrieval algorithm to calculate for each of the at least one candidate points an initial aberration correction for the entire image as if each of said at least one candidate points were guiding stars; (d) comparing the aberrations of each of the at least two test points in each of the initial aberrations corrections; (e) selecting the one candidate point whose initial aberration correction yields suitably similar aberrations for each of the at least two test points and designating said candidate point as a virtual guiding star; and (f) calculating phase corrections for the initial aberrations according to said virtual guiding star.

This application provides a dynamic multifunctional optical metasurface design method and system. The method includes: acquiring functional requirements under different application scenarios and setting the target reflection spectrum accordingly; inputting the target reflection spectrum into a reverse retrieval network, which is then compressed by an encoder and predicted by a decoder parameter to obtain the predicted design parameters of the meta-unit structure; inputting the predicted design parameters of the meta-unit structure into a forward prediction network, which is then calculated via forward propagation to obtain the predicted reflection spectrum; based on the degree of matching between the predicted reflection spectrum and the target reflection spectrum, a phase retrieval algorithm is used to establish a bidirectional connection between the design domain and the physical domain, and by continuously adjusting the predicted design parameters of the meta-unit structure, the predicted reflection spectrum gradually approaches the target reflection spectrum to obtain the ideal design parameters of the meta-unit structure; and arranging the meta-units in the operating space according to the ideal design parameters of the meta-unit structure to form a metasurface structure that can be dynamically and multifunctionally controlled.

The application provides a phase retrieval method, device, system and medium based on enhanced total variation regularization, and relates to the technical field of image processing. The method comprises the following steps: constructing a non-convex optimization model for phase retrieval based on an enhanced total variation regularization model and a phase retrieval problem model; converting the non-convex optimization model into a convex optimization model by using a convex function difference algorithm; obtaining an image to be recovered, inputting the image to be recovered into the convex optimization model, iteratively solving the convex optimization model by using an alternating direction multiplier method, and obtaining a recovered image. The application can improve the definition of the recovered image.

The application discloses an EUV-OCT phase recovery method based on deep learning U-Net, and comprises the following steps: acquiring reflectivity spectrum data of a multi-layer sample and preprocessing; constructing and training a physical driving phase recovery network based on U-Net, wherein a double-branch feature embedding module is used for simultaneously extracting local interference fringes and depth envelope features; a physical driving state space module regards one-dimensional spectrum features as continuous dynamics, and realizes feature transmission of a global receptive field through a discrete state space equation; gradient phase perception attention guided skip connection enhances phase mutation point features; a complex domain output module predicts phase sine / cosine components and restores continuous phase by using an inverse tangent operator; and the measured reflectivity spectrum is input into the trained network, and a phase spectrum with physical continuity is output. The application can adapt to different experimental bandwidths, fundamentally eliminates phase jump artifacts, and significantly improves the accuracy and robustness of phase recovery.

The application provides a signal reconstruction method, system, device and storage medium, which is used for reconstructing an original signal from a measurement signal containing only amplitude information, and comprises the following steps: obtaining the measurement signal containing only amplitude information by using a measurement device, and recording a measurement matrix corresponding to the measurement device; establishing a denoiser, and taking a function feature of the denoiser as denoising prior information; under the regular constraint based on the denoiser prior information, establishing a non-convex optimization inverse problem of signal reconstruction, and iteratively solving the problem by using a projection gradient method; and introducing the denoiser in the solving step, so that the convergence speed of the algorithm is improved. The application combines a solving algorithm of a traditional non-convex optimization problem with denoising prior, improves the reconstruction performance of a signal in a complex Gaussian random measurement matrix and coded diffraction imaging, guarantees convergence, reduces the necessary number of measurement signals, and meets the current demand for signal phase retrieval and reconstruction.

The application discloses a 3D multi-plane phase retrieval algorithm based on compressed support estimation, a medium and equipment, and comprises the following steps: firstly, a compressed support estimation (CSD) algorithm is used to adaptively estimate the region support of each plane from a single diffraction intensity, and prior knowledge is not required to be predefined; then, a CSD-MIPR-HIO algorithm introduces a HIO cycle as a restriction condition, and the performance of phase retrieval is improved by adjusting the constraint condition of the Pth plane; in the iteration process, the transmission function of each plane is respectively subjected to a modulus constraint in a Fourier domain and a support constraint of a target region, and finally converges to the real distribution of an object quickly. The method disclosed by the application breaks the limitation of prior conditions of a traditional 3D multi-plane phase retrieval, and shows high robustness in a noise environment. Numerical and optical experimental results show that the CSD-MIPR-HIO method is feasible, superior and robust to noise.

This invention discloses a fringe phase retrieval method based on untangling theory-driven deep learning, belonging to the field of optical detection. The method includes: generating absolute phase labels based on a random number sequence; obtaining the original speckle image, wrapped phase labels, and wrapped count labels based on the absolute phase labels; constructing training and validation datasets; constructing a dual-task coupled network model based on a convolutional neural network and a composite loss function; training the dual-task coupled network model using the training dataset, validation dataset, and composite loss function; inputting the original fringe image to be processed into the trained dual-task coupled network model, and outputting the absolute phase result after fringe phase retrieval. This invention achieves unified end-to-end processing of speckle removal, fringe analysis, phase unwrapping, and phase retrieval, significantly improving the accuracy, robustness, and interpretability of the phase retrieval results under scenarios with noise, uneven illumination, complex backgrounds, and varying fringe density.

Disclosed in the present invention is a single-frame real-time three-dimensional imaging method based on deep learning, comprising: constructing a lightweight phase retrieval network model based on a physical model; building a multi-vision structured light fringe projection system; constructing a training data set to complete training of the lightweight phase retrieval network model; and using TensorRT to deploy the lightweight phase retrieval network model. Three wrapped phase images are obtained in real time by means of parallel reasoning of three monochromatic view angles; wrapped phases are unwrapped into absolute phases by using a multi-view geometric constraint and three-dimensional phase matching algorithm; and a three-dimensional point cloud having color texture information is generated by means of phase-height mapping and a color image. In the present invention, deep learning technology is integrated with a conventional fringe projection physical model, such that rapid phase acquisition can be achieved using only a single image frame, thereby overcoming motion interference and enabling online, real-time, high-precision three-dimensional imaging in complex dynamic scenes.

A cross-correlation frequency resolved optical gating (X-FROG) system causes a reference beam and an unknown beam to interact within a nonlinear medium in a cross-correlation or multiplication to produce X-FROG spectra and an X-FROG spectrogram. A dedicated frequency resolved optical gating (FROG) system is included within the apparatus to characterize the reference beam and to provide that characterization information to the computer or other processor that performs phase retrieval on the X-FROG spectrogram. A single reference beam is directed into the system and is split three ways by a zero dispersion difference beamsplitter, with a portion of the reference beam directed into the FROG system and a portion of the reference beam directed into the X-FROG system. The apparatus includes a trigger for initiating the reference beam characterization.

The application provides an optimization algorithm of a multi-focus diffractive lens, which comprises the following steps: determining the number of focal points, the diffraction order of each focal point and the target diffraction efficiency of each focal point according to actual application requirements; randomly assigning an initial phase to each focal point and calculating the complex amplitude of light waves; cyclically modulating the complex amplitude of light waves and the diffraction efficiency of each focal point by using a phase retrieval method; and determining the change relationship between the complex amplitude of light waves after modulation and the radial distance of the wave front from the distance pupil center by using the modulation method. By the method of the application, a multi-focus diffractive lens with no sharp corner, higher diffraction efficiency and freely controllable diffraction efficiency of each focal point can be designed.

The invention provides a three-dimensional STOVs light field measuring device and characterization method based on spectral resolution, the device sequentially comprises a spectral filtering module, a phase modulation module, an imaging module and a data processing module along a light path, and STOVs light beams to be measured are dispersed according to wavelength space through the spectral filtering module; carrying out binary amplitude modulation on each wavelength light beam after dispersion at a dispersion plane through a phase modulation module; collecting a modulated multi-wavelength two-dimensional light intensity distribution image by using a phase recovery algorithm of an imaging module; based on the two-dimensional light intensity distribution image and modulation information of the modulation element, three-dimensional complex amplitude distribution of the STOVs light beam to be measured is rebuilt through the data processing module, through fusion of spectral dispersion and calculation imaging, the topological charge number, the phase singular point position and dynamic changes of the topological charge number, the phase singular point position along with wavelength / time are accurately measured, and the measurement accuracy is improved. High spatial resolution, high time resolution and high phase measurement precision can be realized at the same time, and high-precision dynamic representation of a full-aperture three-dimensional space-time vortex light field (STOVs) can be realized.

The present application relates to a phase retrieval wavefront detection method and system, in particular to a phase retrieval wavefront detection method and system based on a non-standard symmetric pupil, which solves the technical problem of poor precision and stability of the existing phase retrieval wavefront detection method using a standard symmetric circular pupil. The present application uses a non-standard symmetric pupil, so that the optical transfer function presents a distribution with obvious direction characteristics in the frequency domain, thereby enhancing the direction sensitivity of the imaging result to system aberration and misalignment parameters, and more abundant aberration information can be extracted from the imaging data to provide stronger constraint conditions for wavefront recovery, and high-precision and high-stability wavefront detection is realized under complex imaging environment. At the same time, imaging information with direction characteristics can be introduced into the imaging data, thereby realizing effective detection of the wavefront, so that images in different states do not need to be obtained by mechanically moving the focal plane, and the system structure is simplified.