12results about How to "Eliminate artifacts" patented technology

The invention provides an image mirror surface highlight removal method and device based on a gradient mask and electronic equipment. The method comprises the following steps: acquiring a mirror surface highlight image and prior semantic information thereof; based on the prior semantic information, performing mirror surface highlight detection on the mirror surface highlight image to obtain a highlight detection result; according to the highlight detection result and the gray scale and illumination information of the mirror surface highlight image, constructing a gradient mask used for representing highlight intensity change; and based on the gradient mask and the prior semantic information, performing image restoration on a highlight area of the mirror surface highlight image, and performing adaptive fusion on a restoration result and a non-highlight area in the mirror surface highlight image to obtain an output image after mirror surface highlight is removed. According to the technical scheme, by introducing the prior semantic information and the gradient mask, accurate detection and smooth restoration of the mirror surface highlight area are realized, and the visual quality of the image can be improved.

The invention discloses a single-layer Compton camera system and an imaging method, and relates to the technical field of nuclear radiation imaging. The system comprises a single-plane pixel type gamma ray detector used for collecting gamma ray interaction event data, including time information and energy information of each interaction and two-dimensional position information in a detector plane, and forming pixel counting distribution; the shielding structure is arranged on one side of the plane of the detector, is located in a local area of the detector and is used for enabling pixel counting distribution to generate a local counting missing feature when gamma rays are incident from one side where the shielding structure is located; and the judging and imaging module is used for judging a gamma ray incident side based on the local counting missing feature and executing Compton imaging reconstruction in a corresponding hemispherical view field range according to the judged incident side. According to the invention, partitioned omnidirectional imaging can be carried out on the radioactive source under the condition that a detector does not need to act on depth information, and meanwhile, generation of mirror image artifacts is avoided.

The application provides a kind of three-dimensional induced polarization inversion and target identification method based on deep learning, comprising: preprocessing three-dimensional induced polarization observation data collected by multiple sources to obtain preprocessed induced polarization data;Based on non-structural multi-scale grid, a three-dimensional induced polarization forward and inversion model is constructed, the preprocessed induced polarization data is input into the three-dimensional induced polarization forward and inversion model, and iterative solution is carried out combined with grid self-adaptive encryption and joint inversion objective function to generate three-dimensional electrical property characteristic data;Apply mixed regularization constraint to three-dimensional electrical property characteristic data to generate high-resolution three-dimensional electrical property data volume;The mixed regularization constraint contains smoothing constraint and total variation constraint, and the weight proportion of the smoothing constraint and the total variation constraint is dynamically adjusted according to the detection depth;Input the high-resolution three-dimensional electrical property data volume into the deep learning identification model to output the target identification result.The application effectively eliminates the false anomaly of complex fault structure, greatly improves the accuracy and efficiency of deep mineral exploration, and is suitable for fine exploration scene of deep deposit.

The utility model discloses a dustproof motor, which comprises a motor body and an electrostatic adsorption mechanism arranged on the motor body and used for adsorbing small particles in the motor body. The electrostatic adsorption mechanism comprises a conductive unit and a dust sticking unit covering the surface of the conductive unit. According to the utility model, through the synergistic effect of active electrostatic adsorption and passive dust-sticking fixation, the limitation of the traditional motor dust-proof technology is broken through, the POG imaging problem caused by the fact that small particles fall on a BG is avoided, and the imaging quality and the reliability of the camera module are remarkably improved.

The application relates to a crowd-sourced street view video three-dimensional reconstruction enhancement method based on a semantic evolution loop. The method comprises the following steps: obtaining an initial three-dimensional reconstruction result, identifying a rendering artifact area in the initial three-dimensional reconstruction result and generating an artifact mask; performing extension processing on the artifact mask to obtain a repair mask; combining the repair mask and a semantic repair instruction to perform semantic repair on the artifact area, thereby obtaining a three-dimensional reconstruction intermediate result; constructing a tubular constraint space based on an original collection track, generating a virtual camera track covering an unobserved area, performing perspective expansion on the intermediate result, and obtaining a reconstruction view under an expanded perspective; calculating a geometric compatibility index of the reconstruction view and a corresponding re-projection rendering view, and if the consistency requirement is met, the reconstruction view is used as supplementary training data to feed back optimization, the three-dimensional reconstruction result is iteratively updated, and the method is stopped until the stop condition is met. The method can improve the fidelity and geometric consistency of the three-dimensional reconstruction result of fragmented crowd-sourced data.

The application discloses a kind of magnetic field inversion current methods based on near-field scanning, including steps: obtaining magnetic field data in circuit, and as input;The magnetic field is extended measurement plane, and the magnetic field matrix is obtained, so that the original magnetic field matrix H is continuous on the current of boundary;The relationship between magnetic field and current in frequency domain space is constructed;Using Tikhonov regularization method to reconstruct current distribution, and using GCV method to optimize the regularization parameter required by Tikhonov regularization method;Extract the structural information of static current model, use it as a mask, and apply it to the result of radio frequency current model;Output the current in the original measurement window as the current reconstructed by the final method.The application eliminates the current artifact on the boundary by extending the measurement plane, automatically solves the current distribution by regularization, avoids the error caused by empirical selection of filter parameters, improves the accuracy of reconstructed current, and finally suppresses spatial noise by mask method to realize accurate reconstruction of radio frequency current.

The present application relates to a kind of single exposure Raw video HDR reconstruction method and system, belong to computer vision and image processing technical field.The method comprises: obtaining single exposure bayer format Raw video sequence;Channel decomposition parallel alignment module is constructed, and input frame is decomposed into full channel flow, red blue channel flow and double green channel flow three parallel branches, using the physical characteristics that red blue channel is not easy to saturate in highlight area and green channel high signal-to-noise ratio, respectively, different feature extraction and alignment are carried out;Exposure complementary mask guided repair module is constructed, by calculating overexposure mask and dividing timing complementary area, using normal exposure information of adjacent frame in complementary area to repair the overexposure area of current frame;Multi-stream features are fused using cross attention mechanism, and high dynamic range video frame is reconstructed by combining mask guided color loss.The present application effectively solves the problem of highlight overflow and dark noise without alternating exposure, avoids ghosting artifacts, and significantly improves the reconstruction quality of HDR video.

This invention relates to brain-computer interfaces, specifically to a brain-computer interface-based emotion and stress management system. The control unit acquires the user's multimodal signals using a non-invasive multimodal signal acquisition device and preprocesses the EEG signals using an EEG signal processing module. The control unit then estimates the power spectral density of the preprocessed EEG signals using a power spectral density estimation module to obtain the power spectral density of the EEG signals. A relaxation level acquisition module obtains the user's relaxation level based on the power spectral density of the EEG signals, a coefficient of variation acquisition module obtains the coefficient of variation for the corresponding frequency band based on the power spectral density of the EEG signals, and a Schumann resonance energy index acquisition module obtains the Schumann resonance energy index corresponding to the first and second harmonics based on the power spectral density of the EEG signals. The technical solution provided by this invention overcomes the shortcomings of existing technologies, such as the difficulty in accurately identifying the user's emotional state and the inability to provide personalized real-time intervention.

This invention relates to the field of optical precision inspection, and particularly to a sub-aperture stitching inspection method based on a frequency-domain and spatial-domain collaborative strategy. The method includes: acquiring discrete phase data of the sub-apertures; constructing a continuous physical field model; performing coarse alignment of adjacent sub-apertures using frequency-domain phase correlation technology to obtain integer pixel displacements between adjacent sub-apertures; performing sub-pixel fine alignment using a numerical gradient method based on the continuous physical field model and a normalized cross-correlation function with an embedded geometric error culling operator; constructing a global robust energy functional for global optimization; solving for the zero-curvature pose under a floating reference, and then performing Gaussian gradient weighted fusion and adaptive orthogonal base surface reconstruction to obtain the full-aperture surface shape of the large-aperture optical element. This invention solves the problems of strong initial value dependence, displacement-tilt degeneracy, cumulative error warping, and sensitivity to outliers in traditional sub-aperture stitching inspection methods, achieving ultra-high precision and high robustness in the sub-aperture stitching inspection of large-aperture optical elements.

This invention discloses a CT image enhancement method and apparatus based on global consistency optimization, comprising: performing Gaussian fitting on the pixel intensity distribution of a low-dose CT image to obtain a fitting result containing multiple categories of Gaussian distribution components; calculating the probability of each pixel intensity belonging to each category of the Gaussian distribution component based on the fitting result, and assigning a pixel label to each pixel accordingly; constructing a global optimization objective function containing consistency constraints of adjacent pixel labels, and adjusting the pixel labels through iterative optimization to maximize the objective function, obtaining optimized pixel labels; and performing adaptive deviation reduction processing on the intensity value of each pixel by shrinking it towards the mean of the Gaussian distribution component corresponding to each optimized pixel label, thereby generating an enhanced CT image. This invention can simultaneously achieve noise suppression and detail preservation under low radiation dose conditions, and is applicable to scenarios such as industrial non-destructive testing, medical diagnosis, and high-resolution microscopic imaging.

The application discloses a kind of single-pixel imaging method and device based on array light source, including obtaining the illumination light field of array light beam and the back light intensity detection value of the reflection back after array light beam irradiation on target object;Based on back light intensity detection value and illumination light field, reconstruct target image as rough target image;Based on rough target image and back light intensity detection value, reconstruct target image using depth neural network without training, output final target image.The present application realizes high efficiency imaging and long distance target detection based on array light source, while removing image noise, artifact and periodicity by introducing depth neural network, further improves the imaging quality and imaging efficiency of single-pixel imaging.

The invention provides a gas extraction pipeline leakage positioning method based on fusion of a mobile sound array and spatial interpolation, and belongs to the field of sound field separation and noise positioning. According to the method, the resolution of gas extraction pipeline leakage positioning can be improved, and meanwhile, the spatial distribution of leakage positions is fully considered to improve the positioning precision and the calculation efficiency. Specifically, through multi-position measurement of a mobile microphone array, virtual aperture expansion is fused to predict sound source data of a non-measurement position of the mobile microphone array, and then synthetic aperture calculation is performed through integration; for a non-free sound field, a pipeline three-dimensional structure in an inspection range is obtained through SLAM, a pipeline grid structure in a microphone array line-of-sight range and a pipeline grid structure in a non-line-of-sight range are divided on the basis of the pipeline three-dimensional structure, and a leakage position is analyzed and represented through a sound transfer function covering direct sound, reflected sound and diffracted sound.