9results about How to "Fast imaging" patented technology

This invention discloses an online super-resolution imaging method for scanning radar based on the minimization criterion. By establishing an azimuth echo convolution model and discretizing it, the super-resolution problem is transformed. Under a regularization framework, the minimization criterion is used to construct an analytically optimizeable cost function containing sparse prior information, transforming the forward-looking imaging resolution improvement problem into an optimization estimation problem. By dividing the antenna measurement matrix into rows and blocks, matrix operations are degraded into the continuous accumulation of vector operations, enabling real-time online updates of targets in the forward-looking region. Finally, the conjugate gradient method is used to degrade and invert the matrix, outputting the super-resolution result. This method can achieve rapid imaging with limited system memory through an online conjugate gradient super-resolution algorithm based on the minimization criterion. Compared with existing batch processing regularization methods, it eliminates false targets, significantly reduces computational complexity, and is beneficial for rapid imaging of scanning radar.

The present application belongs to the field of tunnel advanced prediction technology, and discloses a tunnel advanced prediction electromagnetic observation system and a detection method. The observation mode of surface emission, underground reception, multi-source emission and multi-component reception is adopted. In this mode, high-power emission can be conveniently used, the problems of high transportation cost in the tunnel and low signal-to-noise ratio of collected data are improved, the coverage area of observation data can be improved, and more effective information can be obtained. Based on the observation system, a tunnel advanced prediction inversion algorithm based on deep learning is developed, quasi-three-dimensional joint inversion of multi-component, time-domain and frequency-domain signals is realized, the advantages of deep learning algorithm are fully utilized, time-domain and frequency-domain electromagnetic signals are fully utilized, the calculation efficiency and detection precision of inversion are improved, the non-uniqueness in inversion is reduced, and rapid imaging of underground space structure is realized.

This application discloses an illumination rotation module arranged in a structured light super-resolution illumination microscopic imaging optical system. It includes a rotatable galvanometer with two parallel and opposite mirror surfaces arranged relative to a rotation axis intersecting the principal optical axis. M mirror groups, each comprising at least three mirrors, are arranged around the galvanometer. When the galvanometer is at an angular position about the rotation axis, linearly polarized light incident on the illumination rotation module is reflected sequentially through one mirror surface of the galvanometer, each mirror in a mirror group corresponding to the angular position, and the other mirror surface of the galvanometer. This causes the propagation direction and deflection direction of the linearly polarized light to rotate synchronously before exiting the illumination rotation module. This application also discloses a structured light super-resolution illumination microscopic imaging optical system.

This application provides a multi-nucleus magnetic resonance imaging (MRI) device, belonging to the field of medical device technology. A multi-nucleus radio frequency (RF) transmitting unit is used to generate RF signals from at least two different nuclides. A gradient magnetic field unit is used to provide the gradient magnetic field required for spatial encoding. A multi-nucleus RF receiving unit is used to receive echo signals from different nuclides. A control unit is configured to adjust the timing sequence of the multi-nucleus RF transmitting unit, the multi-nucleus RF receiving unit, and the gradient magnetic field unit to achieve parallel excitation and synchronous reception of at least two different nuclides. Through the multi-nucleus RF transmitting unit, the gradient magnetic field unit, the multi-nucleus RF receiving unit, and the control unit in this application, parallel excitation of RF signals from at least two different nuclides and synchronous reception of echo signals from different nuclides are achieved, reducing the number of excitations and reception time required for imaging, improving imaging speed, and solving the problem of slow imaging speed in traditional devices.

The application provides a dipole double-layer casing well imaging method based on an Inception module, forward modeling is performed on a real double-layer casing well model, a dipole excitation mode is adopted, different sizes of double-layer casing well array logging signals are obtained according to the forward model, neural network parameters based on the Inception module are set, and the obtained characteristic signal array is input into a neural network containing the Inception module for training and verification, the training result of the neural network is saved, and the network structure of the neural network containing the Inception module and the model trained by the optimal parameters are used for carrying out longitudinal wave and transverse wave slowness inversion and imaging on the double-layer casing well. The application establishes the relationship between the characteristic signal and the real longitudinal wave and transverse wave slowness graph of the dipole double-layer casing by using the neural network containing the Inception module, can realize fast and high-resolution imaging, and effectively improves the robustness of the neural network.

The application provides a 360-degree panoramic deep-rotation visual imaging device and a shooting method in a pipeline, which comprises a support, a ranging-zoom camera module with ranging-zoom function and a control module, the ranging-zoom camera module comprises a camera and a depth sensor, a slip ring is installed on the top of the support, the ranging-zoom camera module is installed above the slip ring, a motor and an encoder are respectively arranged on the two sides of the slip ring, the slip ring drives the ranging-zoom camera module to rotate under the action of the motor, the encoder converts the rotating displacement data into digital pulse information during the rotation of the slip ring and transmits the digital pulse information to the control module, and the control module is arranged in the support. The application can synchronously obtain a panoramic image sequence of the inner surface of the pipeline, and obtain a high-definition panoramic image of the inner surface through an image splicing fusion method, thereby improving the efficiency of panoramic imaging in the pipeline.

This invention discloses a multi-channel light-slice microscopic imaging device. The image acquisition module includes multiple image detectors. A laser array emits multiple excitation beams of different wavelengths, which are then combined into a single incident beam by an optical path module. This incident beam passes through a scanning galvanometer and an imaging module before illuminating the sample on a stage mounted on a three-dimensional displacement platform. The imaging objective in the imaging module collects fluorescence signals from the sample, which are then split by the beam-splitting module to form multiple fluorescence signals of different wavelengths and projected onto the multiple image detectors. Each image detector forms an image imaging channel. Multiple image imaging channels receive multiple fluorescence signals of different wavelengths and transmit them to the corresponding image detectors. The three-dimensional displacement platform enables three-dimensional displacement movement of the sample slice. By employing a strategy of continuous motion imaging of the sample slice and simultaneous detection and acquisition of fluorescence signals by multiple image detectors, the time interval between sample preparation and imaging, as well as the pauses during imaging, can be reduced.

The application discloses a spectral super-resolution method based on a variational autoencoder, and comprises the following steps: inputting a target RGB image into a first convolutional layer of a spectral super-resolution network to obtain a plurality of feature maps containing shallow layer features corresponding to the target RGB image; inputting the feature maps into an attention mechanism module of the spectral super-resolution network to perform feature mapping on the feature maps; inputting the feature maps subjected to the feature mapping into a second convolutional layer of the spectral super-resolution network to reconstruct a target hyperspectral image corresponding to the target RGB image; and training the spectral super-resolution network according to a first hyperspectral image and a first RGB image extracted by the variational autoencoder, wherein the first hyperspectral image is reconstructed by the untrained spectral super-resolution network on the basis of a training RGB image. The target RGB image is acquired by a common camera, so that the image acquisition difficulty is low, and the hyperspectral image is reconstructed by the spectral super-resolution network, so that the imaging time is short, and the method can be widely applied to the field of spectral super-resolution.