17results about How to "High restoration accuracy" patented technology

The invention relates to the technical field of space telescope image processing, and particularly provides a large-view-field spliced space telescope image high-precision restoration method, which comprises the following steps of: constructing a distribution relation of wavefront aberrations with different frequencies along with a view field according to optical parameters of a telescope; based on the relation between the intensity two-dimensional matrix of any field-of-view image plane PSF image and the wave aberration of the corresponding field-of-view, an image plane PSF image of a specific field-of-view is actually measured through a wavefront sensor arranged on the telescope, and the wave aberration of the specific field-of-view is calculated based on the actually measured image plane PSF image; the PSF of any view field is derived according to the distribution rule of wavefront aberrations with different frequencies along with the view field and the relation between the intensity two-dimensional matrix of the image plane PSF image and the wave aberration, and the PSF of any view field derived from the actually measured PSF is utilized to realize the high-precision restoration of the spliced space telescope image through an image block restoration method. According to the method, the actually-measured PSF is adopted for image restoration, the defect that estimation PSF is adopted during traditional non-blind deconvolution is overcome, and the restoration precision is improved.

The invention belongs to the technical field of image processing, and particularly relates to a traffic image rain removal method based on a reference image, which comprises the following steps of: selecting and establishing a data set; preprocessing the data set; a rain removal model is constructed, and a backbone network extracts rich features by stacking a plurality of encoder modules, a multi-scale feature matching module and a decoder module; training the rain removal model by using the training set in the target data set, and obtaining a trained rain removal model after the trained rain removal model is verified to be qualified through the test set; and inputting a traffic rain map to be processed into the trained rain removal model for background image reconstruction, and outputting a reconstructed traffic road image by the rain removal model. The invention constructs a novel network model for natural image rain removal research, the network model focuses on feature extraction, and aims to accurately capture potential features in a rain map and a reference image corresponding to the rain map and ensure that more long-distance dependence information can be captured so as to enhance the restoration precision of a traffic background image.

The invention discloses a space-based infrared coding spectral imaging optical system and an imaging method thereof, and belongs to the technical field of optics, the space-based infrared coding spectral imaging optical system is composed of a long-wave infrared channel and a medium-wave infrared channel, the two channels share a three-mirror system for primary image imaging, a light splitter is adopted for light splitting, medium-wave infrared light is reflected, long-wave infrared light is transmitted, and collimation is performed after light splitting. Dispersion and aliasing of spectrums are carried out in a biprism mode, each sub-channel is composed of a front prism, a main optical lens, a relay lens 1, a coding plate (a primary imaging surface), a relay lens 2, a rear prism and the like, data acquisition is carried out after dispersion aliasing is carried out, and resolving imaging is carried out by adopting a spectrum coding algorithm.

This invention discloses a hyperspectral image restoration method and system based on dual-enhanced low-rank tensor constraints, belonging to the field of image processing technology. The steps are as follows: S1: Acquire hyperspectral image data of the target area; S2: Image preprocessing to generate a test image; S3: Input the test image into a dual-enhanced low-rank tensor constraint model to obtain the restored image; wherein the dual-enhanced low-rank tensor constraint model includes a global prior learning module, a nonlocal prior learning module, and a prior integration module. The test image is first input into the global prior learning module to generate a global learning result, then the test image and the global learning result are input into the nonlocal prior learning module to generate a nonlocal learning result, and finally, the prior integration module performs prior weighted integration of the global and nonlocal learning results to obtain the restored image. The effect is that its performance is superior to other hyperspectral remote sensing image restoration methods, and it has a greater advantage in accurately estimating Earth monitoring data.

The invention discloses a hyperspectral and multispectral image fusion method based on classification and multilevel residual enhancement, and relates to the technical field of new-generation information. According to the hyperspectral and multispectral image fusion method, the obtained reconstructed high-resolution hyperspectral image is accurate, the deviation between the reconstructed high-resolution hyperspectral image and the label corresponding to the source image is small, image detail reconstruction is prominent, and high reduction precision can be achieved; moreover, the hyperspectral and multispectral image fusion method provided by the invention has relatively high robustness and adaptability when the source image with relatively high background noise is fused, and the interference of the background noise on the image fusion quality can be effectively inhibited; in addition, the hyperspectral and multispectral image fusion method provided by the invention also has relatively high distinguishing capability and reconstruction precision for different types of ground features.

This invention discloses a method for restoring turbulent degradation images based on complex amplitude detection, belonging to the field of computational optics imaging technology. This method constructs a computational optics imaging system without a hardware correction unit. It utilizes a wavefront sensor and an imaging sensor to simultaneously acquire Hartmann images and target degradation images. A computational unit performs wavefront complex amplitude reconstruction and aberration correction. Based on this, a physically constrained end-to-end neural network architecture is designed. By reconstructing the wavefront complex amplitude, it achieves accurate mapping and inference from the Hartmann image to the point spread function of the imaging system. Finally, a multi-scale deconvolutional network is combined to complete high-quality restoration of the turbulent degradation image. This invention eliminates the need for a hardware corrector, overcomes the physical limitations of traditional adaptive optics, effectively solves the problem of insufficient point spread function accuracy, and enables time-delay-free and highly efficient turbulent image restoration under low-cost conditions.

The invention relates to the technical field of space telescope image processing, and specifically provides a method for high-precision restoration of large-field-of-view spliced ​​space telescope images, constructs the distribution relationship of wavefront aberrations of different frequencies with the field of view according to the optical parameters of the telescope, and based on the relationship between the intensity two-dimensional matrix of the PSF image of the image plane of any field of view and the wave aberration of the corresponding field of view in Fourier optical theory, measures the image plane PSF image of a specific field of view through a wavefront sensor arranged on the telescope, calculates the wave aberration of the specific field of view based on the measured image plane PSF image, and derives the PSF of any field of view through the distribution law of wavefront aberrations of different frequencies with the field of view and the relationship between the intensity two-dimensional matrix of the PSF image of the image plane and the wave aberration, and uses the PSF of any field of view derived from the measured PSF to realize high-precision restoration of the spliced ​​space telescope image through the image block restoration method. The invention uses the measured PSF for image restoration, solves the drawback of using the estimated PSF in the traditional non-blind deconvolution, and improves the restoration accuracy.

This application discloses a method for reconstructing the spatial distribution of regional rainfall based on deep learning, belonging to the field of deep learning technology. The method includes: acquiring the elevation and monthly rainfall of each grid within a target area; dividing the area into feature sub-regions based on the numerical distribution of the grid's elevation, slope, monthly rainfall, and monthly rainfall variation gradient; randomly deploying rain gauges within each feature sub-region to construct a feature mask; selecting rainfall reference data to correct rainfall observation data to obtain rainfall label data; selecting rainfall label data and feature masks from the training period to train the model; selecting rainfall label data and feature masks from the testing period to test the trained model; and obtaining recommended deployment areas for rain gauges based on the test results. This application can more accurately reconstruct the spatial distribution of regional rainfall under limited rain gauge conditions, effectively supporting extreme weather prediction and water resource assessment, while optimizing the station network layout and achieving a balance between accuracy improvement and cost control.

The invention discloses an automatic system for precisely reducing and controlling molten copper by using natural gas. The automatic system comprises a data collection module, a data processing module, a gas input module, a buffer module, a gas output module and a gas detection and discharge module, through real-time data collection, processing and control, the copper liquid reduction efficiency can be greatly improved, the energy consumption can be reduced, the copper liquid reduction accuracy can be improved, and the oxygen content and the temperature of the copper liquid can be controlled within an accurate range.

This application relates to a high-resolution reconstruction method for photovoltaic power generation data. The method includes: collecting photovoltaic data at a resolution lower than a first preset level and time-aligned weather data; performing frequency and time domain modeling on the photovoltaic data and weather data using Fourier transform to obtain input frequency domain features; selectively enhancing the input frequency domain features using learnable frequency domain channel attention to obtain a frequency-modulated sequence; and modeling the frequency-modulated sequence using a Mamba state-space network to obtain reconstructed frequency domain features; restoring the reconstructed frequency domain features to a time domain output through inverse frequency domain transform; and fusing the time domain output with the original time domain features to generate photovoltaic data and weather features at a resolution higher than a second preset level based on the fused features. This solves the problems in related technologies, such as the lack of an effective multimodal feature fusion mechanism, which makes it difficult to deeply integrate key external information such as meteorological data with the power sequence, and the bias in frequency domain modeling, tending to learn low-frequency trends while ignoring high-frequency details, leading to rapid fluctuation distortion in the reconstructed signal.

The invention discloses a method for coding a laser radar point cloud in unmanned driving, which comprises the following steps of: firstly, dividing the point cloud into an intra-frame point cloud and an inter-frame point cloud, removing point cloud data space redundancy by adopting a clustering-based intra-frame prediction technology aiming at the intra-frame point cloud, and predicting the inter-frame point cloud based on the point cloud prediction technology aiming at the inter-frame point cloud; and the point cloud data time redundancy is removed. And the residual data is coded, so that the point cloud compression rate is improved.

The present application relates to the technical field of knowledge graph, specifically to a low-voltage power distribution cabinet intelligent operation and maintenance decision support method and system based on AI, comprising the following steps: obtaining low-voltage power distribution cabinet power-off nodes, electricity testing nodes, ground wire connection nodes and operation dependent edges, establishing an operation and maintenance standard graph, extracting field clock-in nodes and timestamp parameters, comparing node parameters in the operation and maintenance standard graph, and generating actual operation subgraphs. In the present application, the team reliability score is sorted in descending order, truncated and screened, a renewal list is generated, and the low-voltage power distribution cabinet node number is matched. The team credit evaluation result can be directly mapped to the high-risk operation permission identification and resource scheduling decision instruction, forming a closed-loop processing chain from operation process verification, abnormal collection, responsibility transmission to scheduling landing, which helps to improve the pertinence of violation identification and the discrimination degree of team screening.

The invention belongs to but not limited to the technical field of point cloud acquisition, and particularly relates to a three-dimensional point cloud up-sampling method and system for full-plane projection, and the method comprises the steps: projecting all scanned point clouds to a two-dimensional plane; in order to conveniently operate points projected on a two-dimensional plane, a quadtree data structure is established, coordinate transformation is performed on the points on a projection plane, namely, three-dimensional coordinates are converted into two-dimensional coordinates, the projection plane is rotated to be parallel to an xoy plane by using a Rodrigue rotation formula, and then x and y coordinates are directly taken; establishing a quadtree data structure, and performing quick Poisson disk sampling; the points are restored to the three-dimensional space; and reforming and smoothing the point cloud: if the point cloud restored to the three-dimensional space is not completely fit with the original point cloud, smoothing the point cloud and reforming the point cloud.

The application discloses a method for correcting echelle spectrometer spectrum coordinates based on least square and polynomial fitting, which gives priority to the accuracy of spectrum restoration, and establishes an error correction and compensation model of actual imaging and theoretical imaging. The wavelength of the corrected imaging coordinates of the light spot is estimated, so as to establish a spectrum restoration model of two-dimensional spectrum pixel coordinates and wavelength. The method has high restoration accuracy and convenient operation, and can realize high-precision calibration only by using a small amount of characteristic wavelengths, and can be popularized and used in various types of echelle spectrometers and various spectral instruments and equipment with multiple dispersion characteristics.

The invention belongs to the field of high-voltage switch equipment fault identification, and discloses a high-voltage switch equipment abnormal sound source positioning method and system, any position around a high-voltage switch equipment is used as an acquisition original point, a pitch angle and an azimuth angle are acquired by using a power pattern of an abnormal sound source, and the abnormal sound source is acquired by using translation and rotation of a sound valley transmission plate. And meanwhile, by combining a triangle principle, accurate calculation and positioning of the space coordinates of the abnormal sound source are realized. The initial direction positioning of the pitch angle and the azimuth angle greatly improves the subsequent positioning efficiency, the sound valley transmission plate can effectively avoid mutual interference between sound sources, the positioning robustness is ensured, and the positioning precision is improved; according to the method, the abnormal sound positioning precision is improved, the limitation of multi-angle collection in a traditional abnormal sound positioning mode is broken through, the difficulty and potential safety hazards of manual multi-angle collection in the high altitude or in the limited space are avoided, and the efficiency and comprehensiveness of troubleshooting of the high-voltage switchgear are effectively improved.

The invention relates to the technical field of three-dimensional model data management, in particular to a visual three-dimensional model modeling method and system for a silica gel product. The method comprises the following steps: collecting entity size data, material elastic rebound parameters and product deformation data under preset pressure of a silica gel product; constructing an initial three-dimensional model of the silica gel product based on the entity size data, and marking a structure stress node position of the initial three-dimensional model; according to the position of the structure stress node, positioning the structure stress node corresponding to the deformation data in the initial three-dimensional model; and establishing a stress deformation mapping relation between the structure stress node and the product deformation data based on the material elastic rebound parameter, driving the corresponding area of the initial three-dimensional model to deform, and generating a visual three-dimensional model reflecting the elastic characteristic of the silica gel product. By means of the three-dimensional modeling technology, real restoration of the elastic characteristic of the silica gel product is achieved, and the goodness of fit between the visual three-dimensional model of the silica gel product and actual product deformation is improved.

This invention discloses a method and system for detecting and evaluating the settlement of buried pipelines based on ground-penetrating radar (GPR). The detection method acquires B-Scan mask images of shallow-buried pipelines, extracts the overall and local characteristics of target hyperbolic reflection signal feature points in the images, removes singular points, performs curve fitting on all valid target hyperbolic reflection signal feature points, and calculates and scores the depth and wave velocity values ​​corresponding to the target feature points to obtain the pipeline burial depth. The evaluation method, based on the pipeline settlement detection results, identifies the location of maximum settlement deformation by using the angle formed by the height change between two points on the pipeline, and predicts the location where the risk of fracture in the detected section may occur. The detection system implements this detection method, and the evaluation system implements this evaluation method. This application solves the problem in engineering measurements where hyperbolic reflection signals with characteristic damage caused by electromagnetic wave attenuation and coupling cannot be effectively calculated, significantly improving the data's processability and analyzability.