9 results about "Coded aperture" patented technology

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.

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 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 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.

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.

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.