4results about How to "Eliminate artifacts" patented technology

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.