103results about How to "Fast refactoring" patented technology

The invention discloses an edge structure information based block compression perception reconfiguration method which mainly overcomes the defects of low speed and obvious block effect of a reconstructed image in the prior art. The method comprises the following steps of: (1) dividing an image into 32*32 blocks; (2) carrying out wavelet transform on the image blocks, reserving low-frequency signals of the image blocks, and compressing and sampling high-frequency signals; (3) zeroing all high-frequency image block parts, carrying out reverse wavelet transform on the reserved low-frequency information and the zeroed parts to obtain a blurred image and carrying out edge detection on the image; (4) reconstructing image blocks without edges by adopting an orthogonal matching pursuit method, reconstructing image blocks with edges by adopting an MP (Monolithic Processor) method guided by edge structure information, and reconstructing non-edge parts by adopting a generalized inverse method; and (5) splicing reconstructed image blocks to obtain a reconstructed image of an original image. Compared with the prior art, the method has the advantages of high speed and good reconstruction effect and is suitable for reconstructing natural images and SAR (Synthetic Aperture Radar) images.

The invention discloses a method for fast establishing interactive tunnel and wall rock body three-dimensional models, which comprises the following steps: A. tunnel line position information base establishment: collecting tunnel line position information and establishing a line position information base; B. geological exploration base establishment: carrying out standardized processing on hole drilling data obtained through geological exploration; C. three-dimensional stratigraphical profile constraint information base establishment: collecting three-dimensional stratigraphical profile constraint information; D. three-dimensional stratigraphical boundary constraint information base establishment: collecting self defined model establishing boundary; E. real three-dimensional tunnel model establishment: precisely establishing a tunnel three-dimensional model according to the information of tunnel line positions, the tunnel hole body outer cross section and the inner cross section; F. real three-dimensional wall rock model establishment: establishing a wall rock model according to the hole drilling and stratigraphical information; and G. tunnel digging and profile real-time cutting display based on the wall rack model body unit. The model establishing efficiency and precision of the tunnel simulation and digitalized design can be improved, the real-time cutting display of the tunnel passing through the wall rock and any vertical profile can be realized, and the fast reestablishment of the model can be realized.

The invention discloses a distributed microphon array sound source positioning method based on space sparsity, comprising steps of performing signal characteristic extraction through two steps of discrete cosine transform (discrete cosine transform DCT), utilizing the characteristics to construct a sparsity positioning model in order to comprehensively utilize the short time or long time characteristics of the voice signal, reducing the dimension of the model, utilizing a dictionary learning method to perform correction on the model, adopting an approximating I0 norm reconstruction algorithm to perform reconstruction on a sparse signal to find a sound source. The invention has no special requirement on the array structure, requires less calculation, effectively improves the capability of resisting noise and reverberation and positioning accuracy, and is suitable for indoor sound positioning and widely applicable to the video conference system, the voice recognition system and the intelligent robots.

According to a ground feature contour extraction method based on a ground laser point cloud provided by the invention, surface-based space measurement breaking through a traditional single-point measurement mode is introduced into urban measurement application, and the urban measurement efficiency is improved. As the most important space entity of a city, the three-dimensional information of ground objects, especially buildings, is the important basic geographic information of the city and has important application value. The whole scanning process is high in data acquisition efficiency, ground control points do not need to be specially arranged, scanning measurement is slightly influenced by the external environment, and the measurement precision is high. Not only is automation degree ofbuilding space data acquisition improved, but also scanned point cloud can express real three-dimensional information and detail structure of a building in detail. Accurate contour information is acquired by means of the point cloud data, and a three-dimensional model of the building is reconstructed. The method has the advantages of high interaction performance, high intelligent degree, high expandability, high extraction speed, high contour extraction precision and the like.

The invention discloses a rapid compression perception reconstruction method facing to a wearable device, and belongs to the signal processing field. The method comprises the steps of: performing compression measurement to an original electrocardiogram signal x through a constructed m*n dimension random sparse binary observation matrix phi, so as to get an observation vector y, the length of which is m; and based on the observation matrix phi and the observation vector y, reconstructing the original signal by the compression perception reconstruction method learned from the alternating direction multiplier method and the block sparse Bayes, so as to get an estimation vector of the original signal, which is as shown in the description. Compared with the conventional compression perception reconstruction method learned from the block sparse Bayes, the method provided by the invention is advantaged in reaching quicker reconstruction speed on the premise of ensuring the reconstruction precision.

The invention relates to a signal reconstruction method based on block compressed sensing, which can be used for comprehensively and systematically designing signal sampling and phase reconstruction technology based on block compressed sensing from sampling, block optimizing and reconstitution respectively, wherein the design for each part is simple and efficient in consideration of practicability of systematic design at the same time; the designed signal reconstruction method based on block compressed sensing has the following advantages: (1) the method can save the space of a system; the design reduces the storage space needed by a measurement matrix via adopting a method of block compression, simultaneously compresses the block signal at a sampling end when sampling and reduces the complexity of the sampling end; (2) a proposed reconstruction algorithm is fast in reconstruction speed and strong in robustness, besides, a system effectively overcomes the shortcoming of blocking effect in the block compressed sensing.

The invention relates to a rapid method and system for directly reconstructing a structured light illumination super-resolution image in an airspace, wherein the rapid method and system can be widelyapplied to researches in the fields of biology, medicine, material science, microelectronics and the like. Therefore, a problem that the super-resolution microscopic real-time dynamic observation is difficult due to complex operation and serious time consumption of a current structured light illumination super-resolution image reconstruction method is solved. Compared with a traditional frequency-domain SIM super-resolution image reconstruction method, the provided method has the advantages that the operation is completely carried out in the space domain and thus the processes of frequency spectrum separation, frequency spectrum movement, frequency spectrum fusion and the like are avoided and time-consuming multi-times forward/inverse Fourier transform operations are avoided, so that a problem of artifact noise caused by frequency spectrum operation is completely solved; a demodulation matrix for super-resolution reconstruction can be generated in advance, the related operations are only multiplication and addition operations and thus the process is simple and easy to implement, so that the reconstruction speed of the SIM super-resolution image is greatly increased.

The invention discloses a self-adaptive regularized smoothed l<0> norm method. A regularized SL0 algorithm is improved; in a steepest ascent method in an inner loop, a signal residual item estimated value iterative for the first time and a sparse signal estimated deviation value before and after the iteration are used as the selection basis of current regularization parameters; therefore, the signal sparse degree and the weight value of an error tolerance item in an outer loop every time can be adjusted self-adaptively; the balance of the two is kept in an optimization process; therefore, the reconstruction error of sparse signals can be effectively reduced; the anti-noise interference capability of the algorithm is improved; large-scale matrix inversion operation projected in operation of a feasible solution set in an iterative process can be avoided by introducing a SVD method; and the reconstruction speed to the sparse signals in the method disclosed by the invention is effectively increased.

The invention provides a remote sensing image super resolution method based on dictionary learning, comprising the following steps: S1, performing dictionary learning of corresponding feature types based on an image library of different feature types; S2, identifying the feature type of an original image; and S3, carrying out an image super resolution reconstruction process using a corresponding feature type dictionary. The invention puts forward a super resolution method based on dictionary learning using the idea of feature classification. As the number of atoms in a dictionary used in the reconstruction process is reduced greatly, the dictionary scale is reduced greatly. The proportion of effective atoms in the classification dictionary used is increased significantly, so that the number of effective atoms in the dictionary used in the reconstruction process is almost the same as a general dictionary, and the speed of reconstruction is improved significantly while the quality of reconstruction is ensured. The process only involves the adjustment of parameters, the computation efficiency is high, and the reconstruction quality of remote sensing images is high.

The invention discloses a synthetic aperture radar (SAR) imaging method based on a graphics processing unit (GPU). Through the SAR imaging method, based on compressive sensing theory, SAR imaging of a sparse scene is realized. The method is characterized in that: the method comprises the following steps: establishing a sparse SAR imaging module and determining a reconstruction algorithm of the module; based on the size of the SAR imaging, determining sizes of grids and thread blocks required by parallel parts of the reconstruction algorithm and allocating storage space, which is used for storing data in the reconstruction algorithm, for the GPU; and reading the observation data from outside by the GPU, performing sparse reconstruction on the SAR imaging based on the reconstruction algorithm, and returning reconstruction results. The parallel performance of the GPU is utilized in the SAR imaging method, and thus rapid reconstruction of the SAR imaging which is based on the compressive sensing theory is realized.

Embodiments of the present application provide a metadata management and data reconstruction method and device, and a storage medium. In an embodiment of that present application, the RAID technologyis used to organize and manage the storage resources in the storage system, Aiming at the hard disk domain in the storage system, the metadata in the hard disk domain is organized and managed according to the RAID technology. When the hard disk domain is created, the ID of the hard disk domain and the ID of each physical hard disk under the hard disk domain are stored in the attribute descriptionarea of each hard disk. When the storage pool is built, the relationship between the storage pool and the hard disk domain and the mapping relationship between the storage pool and the chunking groupcontained in the storage pool are stored in the attribute description area of each hard disk. Based on the metadata organization structure, when the physical hard disk in the hard disk domain has a hard disk failure, other blocks belonging to the same block group can be quickly indexed according to the information stored in the attribute description area, which is helpful to improve the reconstruction speed of the data stored in the physical hard disk.

The invention discloses a super-resolution structure illumination obvious micro-imaging method based on space-frequency domain hybrid reconstruction. The method comprises the following steps: 1) generating a stripe-shaped illumination light field; 2) illuminating and exciting a to-be-detected sample to generate a fluorescence signal by utilizing the stripe-shaped illumination light field under the conditions of different stripe directions and different phase shifting steps; 3) collecting fluorescence signals to obtain original fluorescence images excited by different stripe-shaped illumination light fields; and 4) if an original fluorescence image does not comprise a defocus background, processing the original fluorescence image which does not comprise the defocus background by using a space-frequency domain hybrid reconstruction algorithm to obtain a super-resolution image; and if an original fluorescence image comprises the defocus background, processing the original fluorescence image comprising the defocus background by using the space-frequency domain hybrid reconstruction algorithm to obtain a super-resolution image with a chromatography effect. According to the method, the calculation amount required in the reconstruction process is reduced by more than two times, and the reconstruction speed can be increased to more than 80 times of that of an existing super-resolution reconstruction algorithm.

The invention provides a resource creation method and device. A storage pool comprises K pieces of PD (Physical Disk) which are not dilated and M pieces of dilated PD. The method comprises the following steps: in a resource creation process, selecting multiple pieces of VD (Virtual Disk) used for creating resources from the K pieces of PD and the M pieces of PD, wherein the selected multiple pieces of VD are evenly distributed in the K pieces of PD and the M pieces of PD; and after resource creation is finished, carrying out equilibrium processing on the multiple pieces of VD in the K pieces of PD and the M pieces of PD to cause a use ratio of the K pieces of PD and a use ratio of the M pieces of PD to be kept at an effective range of an average use ratio. Through the technical scheme of the resource creation method and device, when any one piece of PD in the storage pool breaks down, a reconstruction process is triggered, at the time, the data of the failed PD is recovered on the basis of the data of all pieces of PD, an amount of the PD which participates in the reconstruction process is large, a reconstruction speed is greatly improved, reconstruction efficiency is not lowered by dilatation, the reconstruction pressure of the M pieces of dilated PD is lightened, and influence on business is reduced.

The invention belongs to the technical field of semiconductors, and particularly relates to a software-defined on-chip system, a data interaction method and a system architecture, the system comprises a wafer-level interconnection substrate, a plurality of prefabricated members arranged on the wafer-level interconnection substrate, and a software-defined on-chip interconnection network used for interconnection among different prefabricated members, each prefabricated member is integrated with different function calculation particles according to field application function requirements; the prefabricated members follow a unified interface standard and a physical layer protocol specification, and data exchange is carried out between the prefabricated members through a wafer-level interconnection substrate and a software-defined on-chip interconnection network, so that different function calculation particles are recombined and/or rebuilt in a software-defined mode to adapt to different application requirements and task mapping requirements. According to the method, boundary conditions such as a design method, a calculation normal form, an implementation material and an integration mode of an existing integrated circuit are broken through, and flexible interconnection and functional reconstruction of different prefabricated members for field application are realized, so that complex and diversified application task requirements are met.

The invention discloses a method and a device for calculating a polar coordinate system matrix in a two-dimensional reconstruction algorithm. The method comprises the following steps: S100: establishing a polar coordinate projection model of a two-dimensional field of view to be reconstructed; S200, calculating the overlapping area of the projection beam and the polar coordinate grid at the i-th projection angle as a system matrix element value amn, wherein m in the subscript is a detector primitive number and n is a grid numb; S300: traversing and calculating all overlapping areas under the projection angle to obtain the system matrix A= {amn} of the two-dimensional field of view to be reconstructed. The system matrix under other projection angles can be obtained by adjusting the positionof the system matrix element value in the system matrix according to the change of the projection angle without repeated calculation. The method can improve the precision of algebraic iterative two-dimensional reconstruction algorithm, and avoid recalculating the system matrix when the projection angle changes, and improve the computational efficiency. Another aspect of the invention also provides an apparatus for use in the method.

The invention discloses a multi-view remote sensing image three-dimensional reconstruction method based on disparity maps and key points, which mainly solves the defect of low remote sensing image reconstruction precision in the prior art, and comprises the following implementation steps: (1) selecting an image pair; (2) generating a ground object category label; (3) generating a disparity map fused with the ground object category tags; (4) generating a digital surface model DSM of each image pair; (5) fusing the digital surface model DSM of each image pair; (6) marking key points; (7) optimizing the fused digital surface model DSM; and (8) three-dimensionally reconstructing the three-dimensional model. The reconstruction precision of the remote sensing target of the building and the ground category is improved, the parallax calculation precision requirements of label targets of different ground object categories can be met in a self-adaptive mode, and the reconstruction speed of the remote sensing image is increased.