24 results about "Optical reconstruction" patented technology

The invention provides an interactive three-dimensional holographic display method for a smart farm, and relates to the technical field of smart agriculture and holographic visualization. Comprising the following steps: firstly, performing multi-angle aerial photography in different growth stages of a rice field through an unmanned aerial vehicle to collect image data; processing the data by using a three-dimensional reconstruction algorithm, and constructing a three-dimensional model library of the rice field; on the basis, a voice interaction module is integrated to a visual platform, so that a user can select and switch models and inquire growth information through voice control; further converting the selected three-dimensional model data into structured data suitable for holographic reconstruction, and generating a high-fidelity digital hologram by applying a complex-valued convolutional neural network point cloud gridding algorithm; and finally, performing optical reconstruction on the hologram by driving holographic display equipment. According to the method, the limitation of a traditional two-dimensional image in space and time sequence expression is overcome, dynamic visualization of the rice field growth process is achieved, and the monitoring and decision-making effects are improved.

The present disclosure provides a real-time holographic system and a real-time optical reconstruction method, which relate to the field of holographic technology. The system comprises: a first laser, adapted to generate nanosecond pulse light; a first beam splitter, adapted to split the nanosecond pulse light into reference light and detection light, the detection light being incident on an object to be measured and generating object light having information about the object to be measured; a reconstruction light timing module, adapted to generate reconstruction light having timed femtosecond pulse information; a dichroic mirror, adapted to generate combined light based on the incident reference light and reconstruction light; a holographic dry plate, adapted to receive the combined light and object light, so that the reference light and object light in the combined light interfere on the holographic dry plate to form a phase grating, thereby recording optical information; and a multi-frame imaging module, adapted to receive the reconstruction light and form a diffraction wave based on the phase grating, thereby reading the optical information with a time resolution of the order of picoseconds.

This invention discloses a high-precision liquid refractive index detection system and method, comprising a laser, a transparent substrate, a convex lens, a prism sample cell, and a spot detection unit. The laser emits visible light in parallel beams. The transparent substrate is used for photolithographic printing of a computational hologram, the original image of which is a pure black background containing a one-pixel-wide white vertical line. The convex lens images the object light wave reconstructed from the obtained computational hologram, resulting in a line spot optical reconstruction image. The prism sample cell holds the liquid to be tested. The spot detection unit is positioned on the image plane of the convex lens and is used to detect the pixel position at the center of the line spot reconstruction image. By analyzing the pixel position at the center of the line spot reconstruction image detected by the spot detection unit, the refractive index of the liquid to be tested in the prism sample cell can be measured. This application features a simple structure, convenient operation, low cost, and high detection sensitivity and accuracy.

The application relates to a three-dimensional optical reconstruction method based on a CT image, comprising the following steps: acquiring multi-angle CT projection signals and optical data of an object to be reconstructed by means of a coaxial scanning device; reconstructing the CT projection signals of all angles to obtain CT three-dimensional voxel data and extract CT surface voxel data of the CT three-dimensional voxel data; aligning and registering each pixel point in the optical data with a corresponding pixel point in the CT three-dimensional surface voxel data, and mapping the coordinates of the pixel point in the optical data to a CT image coordinate system of the CT three-dimensional surface voxel data to obtain a first optical data set with three-dimensional space coordinates in the CT image coordinate system under all angles; and splicing all the optical data in the data set to form information after three-dimensional optical reconstruction. The above method can provide accurate three-dimensional space information of an object for three-dimensional optical reconstruction by means of CT scanning, and can generate an accurate and comprehensive optical three-dimensional reconstructed object.

The application discloses a holographic image reconstruction method, device, equipment and program product. The method comprises the following steps: inputting object light of a three-dimensional object to be measured into a coaxial holographic imaging device, and outputting a coaxial holographic light field; performing double-optical-path distribution on the coaxial holographic light field to obtain a first optical path and a second optical path; inputting the coaxial holographic light field into a pre-constructed amplitude reconstruction optical path structure and a phase reconstruction optical path structure in parallel through the first optical path and the second optical path; performing full-optical reconstruction on amplitude information in the first optical path through the amplitude reconstruction optical path structure, and outputting an amplitude reconstruction image; and performing full-optical reconstruction on phase information in the second optical path through the phase reconstruction optical path structure, and outputting a phase reconstruction result. The embodiment of the application can improve the accuracy of the holographic image, and can be widely applied to the field of holographic imaging technology.

The invention discloses an image anti-counterfeiting method based on vector quantization and a phase mask, and the method comprises the steps: firstly, selecting a two-dimensional code which is simple in structure and only has transverse and longitudinal black and white change characteristics as an information medium, and simplifying a subsequent phase modulation structure while keeping the recognition characteristics clear; a vector quantization image compression technology is utilized to effectively code a high-definition image with rich content into a simplified graphic expression in which a two-dimensional code can be embedded, and effective mapping and compression from image complexity to a barcode structure are realized; and finally, a low-order pure-phase optical mask is generated based on the two-dimensional code, embedding and optical reconstruction of a high-definition image are realized under the condition that the phase quantization order is relatively low, and both the image identification degree and the mask preparation feasibility are considered. Therefore, the innovative image-level anti-counterfeiting coding method which integrates physical anti-counterfeiting and digital anti-counterfeiting advantages and has high information bearing capacity and strong physical anti-counterfeiting performance is constructed. The invention provides a feasible, efficient and low-cost new path for physical anti-counterfeiting of high-definition images.

The invention discloses a bagged water package intelligent detection system based on robot AI vision, and relates to the technical field of package detection and intelligent manufacturing. The system comprises an optical reconstruction control module, a geometric normalization processing module, a task enhancement construction module, a defect discrimination modeling module, a self-learning optimization module, a grade decision analysis module and a robot execution and tracing module, and all the modules sequentially realize optical imaging correction, feature enhancement, defect identification, self-learning optimization and grade determination. The robot is driven to complete sorting and tracing, and an intelligent detection and quality management integrated system of bagged water packages is constructed. Through collaborative design of optical self-consistent imaging, energy-driven multi-task self-learning detection and robot closed-loop tracing control, high-precision detection, intelligent sorting and full-process traceable automatic quality control of bagged water packages are realized.

The invention belongs to the technical field of optical reconstruction, and particularly provides a single-frame high-precision multi-view reconstruction system and method based on a curvature perception adaptive window, and the system comprises a multi-camera collection module which is used for collecting a single-frame image of a detected workpiece through a multi-view camera; the camera calibration module is used for carrying out distortion correction on the single-frame image; the multi-view matching module is used for obtaining a pixel-by-pixel hypothesis inclined plane of each single-frame image; the curvature sensing window size selection module is used for obtaining a comprehensive score of curvature sensing adaptive window size selection based on the local plane fitting error, the local hypothesis inclined plane normal vector consistency and the multi-view aggregation matching cost; and the multi-view reconstruction module is used for allocating the sizes of the matched windows based on the comprehensive score, and performing iteration of a multi-view three-dimensional pipeline algorithm by utilizing an allocation result of the sizes of the matched windows, so as to obtain a depth map and complete multi-view reconstruction. According to the technical scheme of the invention, single-frame high-precision and high-integrity measurement of the measured object is realized.

The invention provides an efficient and accurate integrated imaging light field three-dimensional salient target detection method. According to the method, feature extraction and fusion are carried out on four-dimensional light field data through a visual state space coding module, and three-dimensional saliency detection and optical reconstruction are achieved. Firstly, light field data of a three-dimensional scene are obtained through a lens array and recorded in a two-dimensional micro-image array. Then, the micro-image array is divided into sub-micro-image sequences, and the sub-micro-image sequences are input into a visual space state module for multi-scale feature coding and modeling; a salient region is modeled by a saliency-guided Mama module under a selective scanning mechanism, and the robustness and space consistency of features are enhanced through multi-path scanning. And after decoding by the hybrid attention module, the recovery and detail enhancement of the light field salient features are completed, and a high-quality salient micro-image array is generated. And finally, optical reconstruction is completed in combination with a lens array, a three-dimensional salient target with real depth features is obtained, and the balance between the detection precision and the calculation efficiency is realized.

The application discloses a hologram generation method based on deep learning and angular spectrum method, and belongs to the field of deep learning and digital holography.The application solves the problems of long time consumption, high cost, and difficulty in guaranteeing the quality of obtained data in the existing training data set acquisition method, and the problem of poor quality of a reconstructed image obtained by using a denoised hologram output based on the existing deep learning method.The application proposes an HG-Net network structure, uses multiple input intensity distributions and holograms obtained by ASM propagation as training data sets by randomly adjusting the density and size of the speckle, so as to improve the complexity of the training data set.The HG-Net network is trained by using the training data set, so as to improve the generalization of the model.The real part hologram and the imaginary part hologram output by the HG-Net network are combined to obtain a generated hologram, and numerical and optical reconstruction is carried out based on the generated hologram.The method can be applied to hologram generation.

Containers housed with random angular orientation of their thread in a first plurality of seats present circumferentially in a first rotatable carousel, caps are housed with random angular orientation of their thread in a second plurality of scats present circumferentially in a second rotatable carousel, ae current image is acquired of the thread of the container in transit through a first framing field and a current image of the thread of the cap in transit through a second framing field, a current value is calculated of the angular position of the thread of the cap in transit through the second framing field and a current value of the angular position of the thread of the container in transit through the first framing field by comparing their current image with an optical reconstruction thereof preliminarily learned, and the screwing operation is programmed with the calculated value of the current angular position.

Disclosed is an apparatus for measuring texture characteristics of a holographic image that is reconstructed optically by a holographic display device. Provided is an apparatus for measuring texture characteristics of a holographic image, which measures texture characteristics of a holographic image that is reconstructed optically by a holographic display device.

The application relates to the technical field of optical reconstruction, and discloses a multi-hologram-based optical reconstruction method, device and system, the method comprising the following steps: acquiring a target gray image set, converting each gray image in the gray image set into a holographic image to obtain a holographic image set; performing additional phase embedding on the light field of each holographic image in the holographic image set to obtain a composite holographic image; extracting a polarized light field distribution according to the light field phase distribution of the composite holographic image; and performing optical reconstruction on the composite holographic image according to the polarized light field distribution to obtain an actual light field distribution. Through the implementation of the application, the accurate extraction of a polarization state and the dynamic real-time regulation of the polarization state of a holographic light field can be realized, so that the accuracy of optical reconstruction in holographic imaging is improved.

The application discloses a cloud and fog sheltered area flood disaster image reconstruction method based on precipitation prior and SAR constraint, and relates to the technical field of remote sensing image processing. Firstly, permanent water body information is extracted by using pre-disaster cloud-free optical images, and daily flood state prior is constructed by combining multi-temporal SAR images, precipitation data and terrain hydrological information. Then, according to the cloud sheltered area, flood state category and background stability, a partitioned differentiated optical reconstruction prior is constructed. Finally, a conditional diffusion model is adopted to reconstruct the disaster image of the cloud and fog sheltered area under the guidance of SAR flood space constraint, precipitation driving weight and flood state prior, while the real observation information of the non-cloud visible area is reserved. The application can reduce the flood information missing problem caused by cloud sheltering of traditional optical images, improve the spectral texture recovery capability of the newly added expansion area, shallow stagnant water area and water recession transition area under the cloud, and improve the continuity and reliability of flood disaster remote sensing monitoring.

According to the invention, an amplification-free, high-sensitivity and high-specificity monomolecular biosensing platform is constructed. According to the single-molecule biosensing platform, the clickchemistry-based multi-fluorophore nucleic acid probe is designed and synthesized by taking DNA (Deoxyribose Nucleic Acid) of orientia tsutsugamushi as a model target. 5-ethynyl-2 '-deoxyuridine triphosphate is introduced into the probe through a polymerase chain reaction, so that the probe carries a plurality of alkynyl modification sites and is further connected with a large number of Cy5 fluorophores, signals are greatly enhanced, and the photobleaching problem is effectively relieved. Meanwhile, random optical reconstruction microscopy is introduced to serve as a detection reading mode, the random flicker characteristic of fluorescent molecules is utilized, tens of thousands of single molecule events are positioned and counted, and signals are further amplified. The application successfully develops a simple, rapid, high-sensitivity and high-specificity single-molecule detection platform, provides an effective tool for the detection of low-abundance biomarkers, and has wide application prospects in the fields of early diagnosis of diseases and the like.

This invention discloses an underwater 3D reconstruction method based on the fusion of a binocular camera and multibeam sonar, belonging to the field of underwater environment 3D reconstruction technology. The invention includes the following steps: Step 1, acquiring binocular optical images and multibeam acoustic images of an underwater target; Step 2, denoising and enhancing the binocular optical images, obtaining the underwater target's depth information through binocular correction and stereo matching, and calculating the underwater target's optical reconstruction point cloud; Step 3, denoising and enhancing the multibeam acoustic images, calculating the underwater target's acoustic reconstruction point cloud through feature point detection; Step 4, optimizing the sonar-camera coordinate transformation matrix based on feature points from the sonar and camera, and performing 3D reconstruction of the underwater target through depth information fusion. This invention can significantly improve the accuracy and coverage of the reconstructed point cloud, enabling the reconstructed point cloud to better restore the target object.

The invention relates to the technical field of optical reconstruction, and discloses an optical reconstruction method, device and system based on multiple holograms, and the method comprises the steps: obtaining a target grayscale image set, converting each grayscale image in the grayscale image set into a holographic image, and obtaining a holographic image set; carrying out additional phase embedding on the light field of each holographic image in the holographic image set to obtain a composite hologram; polarized light field distribution is extracted according to light field phase distribution of the composite hologram; and performing optical reconstruction on the composite hologram according to the polarized light field distribution to obtain actual light field distribution. Through the implementation of the invention, accurate extraction of the polarization state and dynamic real-time regulation and control of the holographic light field polarization state can be realized, so that the accuracy of optical reconstruction in holographic imaging is improved.

The utility model discloses a super-resolution imaging device of a super-resolution imaging probe, which belongs to the technical field of optical microscopic imaging and comprises an imaging structure for random optical reconstruction super-resolution imaging, an imaging structure for stimulated radiation loss super-resolution imaging and an imaging structure for ground state depletion super-resolution imaging. The device can be simultaneously suitable for random optical reconstruction super-resolution imaging detection, stimulated radiation loss super-resolution imaging and ground state depletion super-resolution imaging, is simple in structure and high in integration level, and can minimize the damage of a light source to cells and a probe and improve the imaging quality under the synergistic effect of low-power laser.

This invention proposes a fast hologram generation method based on high-frequency information extraction. The method includes the following three steps: First, preprocessing the object using a Gaussian filter to separate its high-frequency and low-frequency information, obtaining corresponding high-frequency and low-frequency images. Second, calculating the high-frequency image using a novel lookup table method to obtain the corresponding high-frequency hologram, and simultaneously calculating the low-frequency image using the angular spectrum method to obtain the corresponding low-frequency hologram. Third, superimposing the complex amplitude information of the high-frequency and low-frequency holograms to obtain the complex amplitude information of the final hologram, and extracting the phase information to obtain a pure phase hologram. The final pure phase hologram is then loaded onto a spatial light modulator for optical reconstruction. When coherent parallel light illuminates the spatial light modulator, the holographic image of the object is reconstructed. The method proposed in this invention reduces the number of object points involved in the calculation using the novel lookup table method, significantly improving the hologram calculation time.

The invention relates to a photon computing device for a Transform neural network, and the device comprises an optical coding module which is used for carrying out the word embedding coding of a plurality of input optical signals, and determining a coded optical signal corresponding to each input optical signal; the optical linear transformation module is used for performing multiple-input-multiple-output matrix operation on the coded optical signals corresponding to the multiple input optical signals according to preset parameters based on a multi-head attention model, and determining multiple modulated optical signals; the adjustable optical nonlinear module is used for carrying out feature dimension adjustment on the plurality of modulated optical signals according to a linear rectification activation function and determining an optical processing result; and the multi-path light output module is used for determining target output results corresponding to the plurality of input light signals according to the optical processing result. According to the invention, all-optical reconstruction of the Transform neural network can be realized, and the efficiency and accuracy of photon calculation are improved.

The application belongs to the technical field of optical reconstruction, and specifically provides a single-frame high-precision multi-view reconstruction system and method based on curvature-aware adaptive windowing, which comprises a multi-camera acquisition module, a camera calibration module, a multi-view matching module, a curvature-aware window size selection module and a multi-view reconstruction module; the multi-camera acquisition module is used for acquiring single-frame images of a measured workpiece by using a multi-view camera; the camera calibration module is used for correcting distortion of the single-frame images; the multi-view matching module is used for obtaining a pixel-by-pixel hypothesis slant plane of each single-frame image; the curvature-aware window size selection module is used for obtaining a comprehensive score of curvature-aware adaptive window size selection based on local plane fitting error, local hypothesis slant plane normal vector consistency and multi-view aggregated matching cost; and the multi-view reconstruction module is used for assigning a matching window size based on the comprehensive score, and iteratively performing a multi-view stereo pipeline algorithm by using the assignment result of the matching window size to obtain a depth map and complete multi-view reconstruction. The technical scheme of the application realizes single-frame high-precision and high-integrity measurement of a measured object.

The application discloses a kind of based on robot AI vision's bagged water packaging intelligent detection system, it is related to packaging detection and intelligent manufacturing technical field.The system includes: optical reconstruction control module, geometric normalization processing module, task enhancement construction module, defect discrimination modeling module, self-learning optimization module, grade decision analysis module and robot execution and traceability module, each module realizes optical imaging correction, feature enhancement, defect identification, self-learning optimization and grade determination in turn, drive robot to complete sorting and traceability, and construct the intelligent detection and quality management integrated system of bagged water packaging.Through the collaborative design of optical self-consistent imaging, energy-driven multi-task self-learning detection and robot closed-loop traceability control, high-precision detection, intelligent sorting and full-process traceable automatic quality control of bagged water packaging are realized.

The invention discloses a dynamic holographic generation method and system for a reconfigurable diffraction neural network, and relates to the technical field of optical calculation and optical information processing, and the method comprises the steps: S1, carrying out the amplitude coding of an input image, and then loading the input image to an input plane; s2, constructing a diffraction optical network comprising a plurality of passive diffraction layers and a plurality of reconfigurable diffraction layers; s3, the main light source irradiates the input plane through uniform plane waves, and an input light field sent into the passive diffraction layer is generated; s4, the liquid crystal spatial light modulator LC-SLM obtains key light under the irradiation of the auxiliary light source; s5, writing a diffraction modulation phase into each reconfigurable diffraction layer through the key light to perform modulation and decryption operation so as to dynamically generate a phase hologram in real time in a physical diffraction propagation process; and S6, the optical detector completes optical reconstruction of the target light field on the detection surface. The optical modulation reconfigurable diffraction layer is introduced for the first time, phase distribution is allowed to be adjusted in real time through an external secret key optical signal, and all-optical real-time holographic coding / decoding is achieved.

The application discloses a kind of dynamic holographic generation methods and systems of reconfigurable diffractive neural network, it is related to optical computing and optical information processing technical field, comprising: S1, input image is loaded to input plane using amplitude coding;S2, construct including multiple passive diffraction layers and multiple reconfigurable diffractive layers diffractive optical network;S3, main light source is irradiated input plane by uniform plane wave, generates input light field sent into passive diffraction layer;S4, liquid crystal spatial light modulator LC-SLM obtains key light under the irradiation of auxiliary light source;S5, by key light, write diffractive modulation phase into each reconfigurable diffractive layer and modulate, decryption operation, to generate phase hologram in real time dynamically in physical diffraction propagation process;S6, optical detector completes the optical reconstruction of target light field on detection surface.The application introduces light modulation reconfigurable diffractive layer for the first time, allows to adjust phase distribution in real time by external key light signal, realizes all-optical real-time holographic encoding / decoding.