36 results about "Coded aperture" patented technology

Described are embodiments of a multi-layer giga-pixel plenoptic camera that enable three-dimensional (3D) light-field imaging, high resolution and large field-of-view. In embodiments, the camera includes a radiation conversion array layer, an optics array layer, a complementary metal-oxide-semiconductor (CMOS) image sensor array layer, and a memory layer. Depending on the embodiment, the sequence of the radiation conversion array layer and the optics array layer may be reversed, and / or additional isolation layers may be provided between some of the layers. Applications can span the visible light spectrum, and can include ultraviolet (UV) and infrared (IR) spectra. In an embodiment, applications can span x-ray spectra and gamma ray spectra. Radiation converters in the radiation conversion array layer can be filters or scintillation converters. Optics in the optics array layer can be lenses or pinholes and / or coded apertures.

The application discloses a long-wave infrared dynamic space modulation device and method based on double coding apertures, and belongs to the technical field of optics. The application avoids the diffraction effect in the long-wave infrared space modulation process by selecting a large-size coding pixel coding aperture, adopts a double coding aperture space light modulation structure, separately performs space modulation on target light beams, and realizes coding effect superposition through beam combination, so that the space modulation resolution of the large-size coding pixel coding aperture is improved. On the premise of guaranteeing the space modulation resolution requirement and without increasing the coding aperture area, the diffraction effect in the long-wave infrared space modulation process is avoided by selecting the large-size coding pixel coding aperture. The application introduces the use of a displacement table, and the position of the moving coding template is transformed for multiple times within the single information acquisition time of the system, so that the effective coding area in the optical path is transformed, more coding superposition effects are generated, and the coding resolution and the coding gray scale are further improved.

The sensing system includes a focal plane array, a detector dual input circuit, a detector selector circuit, and a selection module. The focal plane array includes a plurality of detectors. The detector dual input circuit combines outputs from the detectors received on a first input channel without using outputs received on a second input channel. The detector selector circuit establishes a first signal path between the detectors and the first input channel and a second signal path between the detectors and the second input channel. The detector selector circuit includes a mask that maps the detectors to a first detector group or a second detector group. Based on the mask assignment, the selection module connects one or more of the detectors to the first signal path to establish the first detector group and connects one or more of the detectors to the second signal path to establish the second detector group.

This invention discloses an end-to-end spectral reconstruction method, comprising the following steps: S1, reconstructing a hyperspectral image; S2, using the obtained hyperspectral image as input to an optimized neural network, training the neural network parameters according to the end-to-end spectral reconstruction model, and calculating the loss function; S3, backpropagating errors to the coding template to be designed, changing the design parameters of the coding template, and continuing to train the model until a high-quality hyperspectral image is reconstructed. By employing the above technical solution, the design of the optical system is combined with the reconstruction method. Based on the coded aperture snapshot system, an adaptive coding template is added according to the end-to-end spectral reconstruction method, replacing the traditional random coding template, thereby improving the quality of spectral reconstruction.

A depth is estimated regardless of an imaging target and an imaging condition. An imaging device with a three-dimensional information measurement function includes: a pattern projection unit including a light source and a pattern forming unit that forms a projection pattern of a light beam; an imaging unit including a lens group including at least one lens, a coded aperture that limits external light passing through the lens group in a predetermined coded pattern, a shutter, and an image sensor; and a depth calculation unit configured to obtain, based on a pattern image imaged by the imaging unit and a known point spread function related to the coded pattern, a depth distribution of an image imaged by the imaging unit.

The invention discloses a hyperspectral compression imaging method and system, a terminal and a storage medium in the technical field of hyperspectral image processing, and aims to solve the problem of low reconstruction precision caused by loss of high-frequency details, weak spectral correlation and poor anti-noise capability in a compression imaging process in the prior art. The method comprises the following steps: acquiring compression measurement and a sensing mask of a coded aperture snapshot spectral imaging system, and acquiring an initial feature map according to the compression measurement and the sensing mask; inputting the initial feature map into a pre-constructed U-Net model to obtain a decoded feature map; performing convolutional mapping on the decoded feature map, and obtaining a reconstructed hyperspectral image in combination with the initial feature map; according to the method, long-sequence data are efficiently processed through the spectrum-space state synchronizer, local and global features of the image can be effectively captured through multi-scale decomposition of the wavelet variance modulation block, and the problem that reconstruction precision is not high due to loss of high-frequency details, weak spectrum correlation and poor anti-noise capacity in the traditional compression imaging process is solved.

A depth map generation system generates a depth map based on a plurality of captured images acquired by using an imaging device including a diaphragm unit in which a coded aperture is formed by a liquid crystal panel. The plurality of captured images including at least a first frame, a second frame acquired after acquisition of the first frame, and a third frame acquired after acquisition of the second frame. The depth map generation system includes: a combination unit configured to acquire a combined frame based on the first frame and the third frame; and a depth map generation unit configured to generate a depth map based on the combined frame and the second frame.

The invention discloses a perovskite imaging system and method based on high-brightness X-ray light source coupling. The system sequentially comprises a high-performance X-ray radiation source, an optical divergence element, a coding aperture, an object plane, a detector array based on a perovskite material and a processing unit according to a radiation propagation sequence, emitting X-ray radiation by an X-ray radiation source; intercepting X-ray radiation by using an optical diverging element, and generating a diverging beam emitted from the virtual focus; modulating the divergent beam through the coding aperture and irradiating the divergent beam to an object to be imaged; capturing radiation interacted with the object to be imaged by using a detector array to generate a measured value; the processing unit solves the inverse problem of reversely deducing real physical information of the to-be-imaged object from the coding measurement value according to a preset coding aperture pattern, a system forward model and the measurement value, and reconstructs a high-resolution and high-fidelity image of the to-be-imaged object; the imaging effects of high resolution, high sensitivity, low radiation dose and high fidelity can be realized.

Regarding tomography, more radiation is detected. To detect a large number of radiations and provide better resolution than that provided by a parallel hole collimator, the collimator is replaced by an attenuator having outer and inner edges. Instead of forcing directivity, large holes having different shapes are used to enable detection of more radiation. By operating the attenuator, differences in shadows on the sensor are used as time-coded apertures to reconstruct the radiation source with higher resolution and sensitivity than when a fixed parallel hole collimator is used.

The present invention addresses the problem of reducing the weight of a head-mounted display to lower its cost. A head-mounted display system (100) includes: a lens; a coded aperture that narrows external light passing through the lens, to a predetermined coded pattern through a liquid crystal panel; a camera (14) having an image sensor; a depth calculation unit (20) that obtains the depth distribution of an image, which is captured by the camera (14), from the image and a known blur function related to the coded pattern; a stereoscopic image generation unit (21) that generates, on the basis of the image and the depth distribution, an image for a right eye and an image for a left eye; and a stereoscopic display (13) that displays the image for the right eye and the image for the left eye such that the images correspond to the wearer's right and left eyes, respectively.

The application provides an image reconstruction method, system and medium of a compressive sensing lens based on a coded aperture, the method comprising: acquiring an original scene image, performing projection modulation to obtain an image received by a sensor; constructing a sensing matrix and a projection matrix, mapping a transfer function of a mask based on the sensing matrix, performing spatial coding sampling on the image received by the sensor through the projection matrix to obtain a compressed measurement result; constructing a deep learning reconstruction network, processing the compressed measurement result based on the deep learning reconstruction network to obtain a two-dimensional feature map; capturing different subspace information based on the two-dimensional feature map through a multi-head attention mechanism, restoring the image resolution based on the different subspace information, and outputting a reconstructed image; and using the mask to realize physical compression, greatly reducing the data acquisition amount, restoring information through the deep learning reconstruction network, improving the image reconstruction efficiency and sensing quality, and adapting to multiple scene environments.

The application discloses a hyperspectral compression imaging method, system, terminal and storage medium in the technical field of hyperspectral image processing, and aims to solve the problem of low reconstruction accuracy caused by high-frequency detail loss, weak spectral correlation and poor noise resistance in the compression imaging process in the prior art. It comprises obtaining the compression measurement and the perception mask of the coded aperture snapshot spectral imaging system, obtaining the initial feature map according to the compression measurement and the perception mask; inputting the initial feature map into the pre-constructed U-Net model to obtain the decoding feature map; and performing convolution mapping on the decoding feature map to obtain the reconstructed hyperspectral image in combination with the initial feature map; the spectral-space state synchronizer efficiently processes long sequence data, and the wavelet variance modulation block can effectively capture the local and global features of the image through multi-scale decomposition, thereby solving the problem of low reconstruction accuracy caused by high-frequency detail loss, weak spectral correlation and poor noise resistance in the traditional compression imaging process.

The application discloses a hyperspectral snapshot compressive imaging reconstruction and classification integrated method and system, which comprises a training stage and a test stage: in the training stage, a compressed measurement map is generated by using a hyperspectral image and coded aperture mask information, and a training sample composed of the compressed measurement map and a corresponding multi-label vector is constructed; the compressed measurement map is input into an end-to-end network composed of a shared feature encoder, an image reconstruction branch and a multi-scale fusion classification branch, and a joint loss function with dynamic weights is used to learn network parameters; in the test stage, the compressed measurement map collected by a snapshot compressive imaging system is input into the trained network, and a multi-label ground object classification result is directly output. Compared with a serial scheme of first reconstruction and then classification, the application reduces repeated calculation and parameter size, reduces inference delay, improves remote sensing interpretation efficiency, and is suitable for fast ground object identification scenes.

An imaging system module includes a first lens, a second lens disposed on an optical axis of the first lens, a liquid crystal panel disposed between the first lens and the second lens, and a cylindrical member having a cylindrical shape and supporting the first lens, the second lens, and the liquid crystal panel inside a cylinder. The liquid crystal panel is controlled externally to form an aperture having a designated pattern such as a coded aperture. A panel surface of the liquid crystal panel has an N-polygonal shape or a circular shape. Here, N is a natural number greater than four.

The present application relates to the technical field of nuclear power plant radiation monitoring, and particularly relates to a nuclear power plant radiation heat source three-dimensional visualization method, aiming at the problems of low positioning efficiency of radiation hot spots in complex scenes and high-precision scanning of laser radar in multi-modal data fusion in the prior art, the present application synchronously collects three-dimensional point cloud and radiation image data through laser radar and coded aperture gamma camera, realizes accurate alignment of cross-modal data by using a feature point coordinate system transformation algorithm, fuses optical images, radiation intensity and three-dimensional space depth information, and generates a three-dimensional visualized scene with color gradient. The method can present the position, distribution and environmental relationship of the radiation hot spot in real time, and the positioning accuracy reaches millimeter level, and is suitable for complex scenes such as dense pipelines. The present application solves the defects of high dependence on the precision of a single device and insufficient real-time performance of the traditional scheme, and provides efficient and intuitive technical support for safe operation of nuclear power.

The application discloses a kind of training-free snapshot photometric stereo vision methods based on spectral compression imaging, comprising: (1) setting multiple different wavelength monochromatic light sources to simultaneously irradiate object from different directions, form high-dimensional spectral-angle data cube;(2) the spectral-angle data cube is modulated in space by coded aperture, along the spectrum dimension is sheared translation by using optical dispersion element, finally integrates on single-channel image sensor, generates single two-dimensional gray compressed measurement image;(3) inverse problem model is constructed, and multiple illumination image sequence is decoupled and recovered from single two-dimensional gray compressed measurement image using iterative optimization algorithm based on physical drive;(4) the surface normal map of the measured object is predicted by inputting multiple illumination image sequence into pre-trained photometric stereo vision network module.The application can realize low-cost, high data efficiency and high physical fidelity three-dimensional reconstruction by single snapshot.

A multi-modality imaging system allows for selectable photoelectric effect and / or Compton effect detection. The camera or detector is a module with a catcher detector. Depending on the use or design, a scatter detector and / or a coded physical aperture are positioned in front of the catcher detector relative to the patient space. For low energies, emissions passing through the scatter detector continue through the coded aperture to be detected by the catcher detector using the photoelectric effect. Alternatively, the scatter detector is not provided. For higher energies, some emissions scatter at the scatter detector, and resulting emissions from the scattering pass by or through the coded aperture to be detected at the catcher detector for detection using the Compton effect. Alternatively, the coded aperture is not provided. The same module may be used to detect using both the photoelectric and Compton effects where both the scatter detector and coded aperture are provided with the catcher detector. Multiple modules may be positioned together to form a larger camera, or a module is used alone. By using modules, any number of modules may be used to fit with a multi-modality imaging system. One or more such modules may be added to another imaging system (e.g., CT or MR) for a multi-modality imaging system.

The invention relates to a crop classification method and system based on coded aperture snapshot calculation spectral imaging, and the method comprises the following steps: S1, capturing an agricultural scene through an optical encoder and an imaging element based on compressed sensing, and obtaining an output result of the optical encoder; s2, constructing a data set of an output result of the optical encoder and a real label of the crop variety, designing a deep learning decoder, constructing a deep learning framework, respectively carrying out training, testing and verification, and finally obtaining a weight file of the model through gradient descent; and S3, collecting compressed data through an optical encoder, and obtaining a crop classification result of an agricultural scene and a hyperspectral image of the corresponding scene in real time through network reasoning by using the obtained weight file. According to the crop classification method and system, an integrated method of optical hardware coding and decoding based on the deep learning network is used for crop classification, the classification speed is greatly improved, and the data storage cost is reduced.

The invention relates to a glow discharge optical emission spectroscopy (GDOES) apparatus that includes a spectral filter mask with a plurality of slits that are each operable to receive optical radiation emitted from a sample. The apparatus also includes a processor operable to analyze a sample's emitted optical radiation from the plurality of slits of the spectral filter mask. The invention also relates to methods of analyzing a sample by utilizing the aforementioned apparatus.

The invention discloses an out-of-focus coding snapshot type spectrum scattering imaging method based on deep learning, and belongs to the field of computational imaging. Comprising a projector, a collimating lens, a diaphragm, an imaging lens, a scattering medium, a liquid crystal lens and a monochromatic camera which are sequentially arranged in the direction of an optical axis. The axial dispersion characteristic of a liquid crystal lens is used as a physical coding mechanism, and a single-frame mixed speckle image is obtained; learning a mapping relation between speckle distribution and a specific wavelength image by constructing and training a U-Net neural network including wavelength indication channel input; the target image of each wavelength channel can be decoupled and recovered only by inputting the single-frame mixed speckle and the wavelength indication diagram into the network. According to the invention, a mechanical scanning device, an optical filter or a special coding aperture is not needed, the method has the advantages of simple optical path, low cost, high time resolution and the like, and high-quality snapshot spectral imaging penetrating through the scattering medium is realized.

A system and method for acquiring in vivo tomographic X-ray scatter data for tissue discrimination of breast tissue. The system includes a coded aperture for spatially encoding X-ray scatter originating from within a patient's breast. Detectors record the modulated scatter signal, which is used to reconstruct a spatially resolved estimate of the X-ray scatter spectra which can then be used to generate spatially resolved tissue type estimates for the user.

A system and method for in vivo tomographic tissue imaging using coded aperture X-ray scatter tomography are disclosed. The imaging system includes a coded aperture for spatially encoding X-ray scatter originating from within a patient. An X-ray detector array records the modulated scatter signal, which is analyzed and used to generate a spatially resolved X-ray scatter spectral reconstruction of the tissue and produce a spatially resolved scatter tissue image of the irradiated tissue.

The application discloses an optical imaging system and method integrating optical imaging and coding aperture technology, aiming to integrate the dispersed polarization components in the reflected light signal into hierarchical coded light field data by constructing a polarization coding modulation system, and highlight the coupling relationship between optical elements; adopt refocusing sequence and focal plane tomography technology to fully tap the spatial geometric information and light intensity distribution characteristics of different depth layers, and reveal the three-dimensional distribution law of the surface topography; introduce wavefront correction and deformable mirror control technology to adaptively adjust the imaging parameters of the optical system, and expand the application range of the measurement precision; combine light intensity modulation analysis and phase unwrapping window processing to depict the change trend of the surface curvature and grasp the key feature points of the topography measurement; finally, fuse the multi-dimensional and multi-level optical measurement information to form three-dimensional measurement output with rich content and reliable precision, and provide comprehensive and high-quality measurement technology resources for application scenarios such as precision optical detection and surface quality evaluation.

The application discloses a kind of compressed computing spectral imaging reconstruction method and system based on pulse weighted network, it is related to computing imaging technical field, it can be from compressed measurement value with low energy consumption and high quality Reconstruct HSI data, can greatly improve the energy efficiency ratio of reconstruction algorithm.The scheme is specifically as follows: using coded aperture snapshot spectral imager CASSI obtains the two-dimensional compressed measurement value of known target scene three-dimensional hyperspectral imaging technology HIS data cube.The two-dimensional compressed measurement value obtained is preprocessed, image features are extracted, and the initial value of the reconstruction result of the HSI cube of the known target scene is obtained.The initial value of the reconstruction result is spliced with the coded pattern of the compressed spectral imaging system, and is sent into the trained multi-time-step reconstruction network to obtain the output result of the network, i.e., the reconstruction result of the hyperspectral data of the target scene to be measured.

The invention relates to the technical field of instruments and meters, in particular to a small-sized double-focusing mass spectrum imaging system for space and a use method, the system comprises an ion source, a coding plate, an electrostatic analyzer, a magnetic analyzer and an FOP detector, the ion source adopts a symmetrical magnetic field structure, and a cathode emission device and a hot filament are respectively located at two ends of the ion source; the coding plate is arranged right in front of the ion source; the electrostatic analyzer is composed of two coaxial cylindrical electrodes; the magnetic field structure of the magnetic analyzer is a direct asymmetric fan-shaped magnetic field; the electrostatic analyzer and the magnetic analyzer are combined in a reverse serial connection manner; the FOP detector adopts a micro-channel plate + fluorescent screen + CMOS camera imaging mode. According to the invention, the limitation of large sizes of ion beams and imaging light spots thereof under a conventional single-slit outlet structure of a mass spectrometer is overcome by adopting a coding aperture mode, so that the mass resolution of the mass spectrum imaging device is remarkably improved, the sensitivity is high, the imaging speed is high, the signal-to-noise ratio is high, and the detection of lower-content substances is realized.

The invention provides a coding aperture imaging short-time image motion determination method based on a ConvNeXt coarse image motion estimation network and constraint phase correlation, and the method comprises the steps: determining an effective matching region in a coding modulation effective field of view, inputting two adjacent frames into ConvNeXt in a paired manner, extracting cross-frame multi-scale features, generating a structure guide weight according to feature difference, and carrying out the weighted convergence, regressing the coarse image motion vector and the displacement search range and generating a structure highlighting feature map; then roughly aligning a to-be-detected frame, respectively calculating an image phase correlation graph and a structure phase correlation graph in a limited range, fusing the image phase correlation graph and the structure phase correlation graph to obtain a joint phase correlation graph, calculating displacement confidence coefficient based on peak position consistency and main peak prominence, screening displacement peaks, and performing sub-pixel refinement in a local window to obtain a refined image motion vector; finally, outputting a final image motion and a quality mark according to confidence and consistency judgment, and generating a compensation control quantity or a zero compensation control quantity according to the final image motion and the quality mark; the method can improve the image motion judgment reliability and reduce the error compensation risk.

According to an embodiment, an optical device includes a liquid crystal panel which displays a coded aperture pattern, an optical system including a lens, an imaging device including a plurality of sensor elements and a plurality of color filters, and a controller connected to the liquid crystal panel, the optical system, and the imaging element, wherein the liquid crystal panel comprises a polarizer which modulates infrared light and transmits visible light.

A near-eye light-field display apparatus is provided, which includes a display module, a first lens module, an aperture device, and a second lens module. The display module displays light-field data. The first lens module collimates light rays emitted from the display module. The aperture device generates a plurality of coded apertures. The collimated light rays are modulated by the coded apertures. The second lens module focuses the modulated light rays on an image plane to form a real image.

This invention provides a coded aperture snapshot spectral imaging system and hyperspectral image reconstruction method based on orthogonal dual-dispersion. The system acquires horizontal and vertical compressed measurement images by synchronously compressing samples through orthogonally set horizontal and vertical dispersion channels and a shared spatial modulation mask. The reconstruction method includes: establishing an optimization equation containing prior terms based on an imaging mathematical model, constructing a dual-dispersion depth unfolding framework (DDDU), and decomposing the optimization equation into data subproblems and prior subproblems. The data subproblems are independently optimized through closed-form solutions of horizontal and vertical dispersion, preserving the complementary information structure of the two channels; the prior subproblems are jointly denoised and feature-fused using a dual-dispersion information fusion Transformer (DDIFT). High-fidelity hyperspectral image reconstruction is achieved through iterative solution. This invention innovatively combines orthogonal dual-dispersion channel design to improve the sampling rate and effectively utilizes complementary spectral information through an algorithm combining physical models and deep learning, thereby improving imaging and reconstruction performance.