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111results about How to "Reduce refactoring time" patented technology

Multi-task super-resolution image reconstruction method based on KSVD dictionary learning

The invention discloses a multi-task super-resolution image reconstruction method based on KSVD dictionary learning, which mainly solves the problem of relatively serious quality reduction of the reconstructed image under high amplification factors in the existing method. The method mainly comprises the following steps: firstly, inputting a training image, and filtering the training image to extract features; extracting image blocks to construct a matrix M, and dividing the matrix M into K classes to acquire K pairs of initial dictionaries H1, H2...Hk and L1, L2...Lk; then, training the K pairs of initial dictionaries H1, H2...Hk and L1, L2...Lk into K pairs of new dictionaries Dh1, Dh2...Dhk and Dl1, Dl2...Dlk by utilizing a KSVD method; and finally, carrying out super-resolution reconstruction on the input low-resolution image by utilizing a multi-task algorithm and the dictionaries Dh1, Dh2...Dhk and Dl1, Dl2...Dlk to acquire a final reconstructed image. The invention can reconstruct various natural images containing non-texture images such as animals, plants, people and the like and images with stronger texture features such as buildings and the like, and can effectively improve the quality of the reconstructed image under high amplification factors.
Owner:XIDIAN UNIV

Method for accurately reconstructing dissimilar material microcosmic finite element grid model on basis of CT (computed tomography) images

The invention provides a method for accurately reconstructing a microcosmic finite element grid model of a dissimilar material on the basis of CT (computed tomography) images. According to the method, sequence CT images are acquired through industrial CT, and micro-structural information in the CT images is mapped onto the reconstructed finite element grid model on basis of digitization and threshold segmentation, so that any detailed structural information in the dissimilar material can be represented in the reconstructed model. The method improves the reconstruction accuracy by means of contrast-limited adaptive histogram equalization, median filtering and pixel interpolation, and improves the reconstruction efficiency through image cut and pixel combination. With the method, rectangular (two-dimensional) and cuboid (three-dimensional) unit grid models with higher finite element analysis accuracy are directly reconstructed, error accumulation during reconstruction, grid partition and other links of the existing geometric reconstruction method is avoided, and reconstruction accuracy and efficiency are improved. The method can be widely applied to fields such as performance prediction and optimization design of dissimilar materials.
Owner:XI AN JIAOTONG UNIV

Multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method

The invention discloses a multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method, which relates to the technical field of information and communication. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method is provided for solving the problem of recovering an original multiband signal from multiple observed value vectors with unknown sparsity after continuous-limited module conversion through sampling by a modulated broadband converter under an Xampling framework. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method comprises the steps of: conducting self-adaptive estimation on sparsity of a signal; updating the sparsity with a given step length factor through repeated iteration so that the sparsity gradually approaches the actual sparsity of the signal; correcting a support set through a backtracking thought and a minimum mean square criterion; stopping iteration until an residual error is less than a set threshold value; and finally reconstructing an original multiband signal through pseudo inverse operation by utilizing the obtained complete support set. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method can achieve the analog reconstruction of the multiband signal based on compressed sensing.
Owner:HARBIN INST OF TECH

An image compression sensing method based on a sparse denoising self-coding network

The invention claims an image compression sensing method based on a sparse denoising self-coding network, and belongs to the technical field of deep learning and image processing. The method comprisesthe following steps: 1, obtaining an original image signal x as training data, preprocessing the data and completing signal corrosion to obtain the formula as shown in the specification; 2, buildinga coding sub-network of a sparse denoising self-coding network, and obtaining a measurement value y by the image signal x through the coding sub-network; 3, setting up a decoding sub-network of the sparse denoising self-coding network, obtaining a reconstructed picture as shown in the specification by the measurement value y through the decoding sub-network, 4, introducing sparsity limitation, andgenerating a loss function JSDAE (W, b); and 5, carrying out joint training on the coding and decoding sub-networks through a back propagation algorithm, updating parameters and obtaining an optimalsparse denoising self-coding network. Sparsity limitation is added on the basis of the denoising self-coding network, image compression and reconstruction are integrated into a unified self-coding network framework, the quality of reconstructed images is effectively improved, and the reconstruction time is greatly shortened.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

Image structure model-based compressed sensing image reconstruction method

The invention discloses an image structure model-based compressed sensing image reconstruction method, which mainly solves the problems that image structure information is not considered and blind iteration is carried out in the conventional method. The method comprises the following steps of: inputting an image A, and performing Fourier transform on the image A to obtain a Fourier coefficient matrix X1 of the input image A; sampling the Fourier coefficient matrix X1 according to a density variable sampling model for fully sampling Fourier coefficients at low frequency to obtain an observation vector f; performing inverse Fourier transform on the observation vector f to obtain a transformed image X2; performing edge detection on the transformed image X2 to obtain an edge detection image X3; performing Wavelet transform and Curvelet transform on the edge detection image X3, finding an edge position and positions of large coefficients, and finding corresponding coefficients in the transformed image X2 according to the obtained positions; and performing Wavelet-curvelet frame-based Split Bregman reconstruction algorithm to iterate for 20 times and finally obtaining the required reconstructed image. The method has the advantages of higher accuracy, better effect and shorter time for image reconstruction.
Owner:XIDIAN UNIV

Compressed sensing based color imaging device and compressed sensing based color imaging method

The invention discloses a compressed sensing based color imaging device and a compressed sensing based color imaging method. The compressed sensing based color imaging device comprises a PC (personal computer), a DLP (digital light projector), a target image, a single-pixel photon detector and a data collection and control module. The PC, the DLP and the single-pixel photon detector are connected with the data collection and control module. The PC generates a two-dimensional random binary projected intensity image. The data collection and control module controls the DLP to perform binary intensity image projection on the target image under red, green, blue and white structured light sequentially to acquire digital signals of the red, green, blue and white structured light respectively and send the digital signals to the PC, reconstructs the signals of the red, green, blue and white structured light through compressed sensing to acquire four monochrome gray level images, and performing color fusion on the four monochrome gray level images to acquire a final color image. The compressed sensing based color imaging device and the compressed sensing based color imaging method have the advantages that light filters are not needed, and simple structure and low cost are achieved; sampling frequency can be reduced, and color fidelity can be guaranteed without reduction of image resolution.
Owner:NANJING UNIV OF SCI & TECH

Image structure-based particle swarm optimization non-convex compressed sensing image reconstruction method

The present invention discloses an image structure-based particle swarm optimization non-convex compressed sensing reconstruction method. The method comprises: 1. according to an observation vector, distinguishing an image block structure, and marking an image block as smooth, unidirectional and multi-directional; 3. clustering observation vectors corresponding to different types of image blocks, and constructing a corresponding over-complete redundant dictionary for each type of the image blocks; 4. constructing an initial population for each type of the image blocks; 5. for each type of the smooth image blocks, using a particle swarm algorithm based on a grouping initialization policy to search an atomic combination with an optimal scale; 6. for each type of the unidirectional and multi-directional image blocks, using a particle swarm algorithm based on a cross and an atomic direction constraint to search an atomic combination with an optimal direction and scale; and 7. calculating an estimated value of all image blocks, and sequentially splicing into an entire image to output. According to the method of the present invention, reconstruction time is short, and the reconstructed image has good visual effects, a high peak signal to noise ratio, and high structural similarity. The method can be used for non-convex compressed sensing reconstruction of an image signal.
Owner:XIDIAN UNIV

Power distribution network reconstruction method and system

The invention discloses a power distribution network reconstruction method and system. The method comprises the steps that an incidence matrix model is established according to the connection relation of father nodes and son nodes in a power distribution network and branch switches, and the on-off states of the branch switches are assigned to form an incidence matrix set; all incidence matrixes are used for simulating a topological structure of the power distribution network, whether the topological structure has a looped network is judged, if the topological structure has a looped network, the incidence matrixes corresponding to the topological structures are eliminated, if the topological structure has no a looped network, the topological structure is subjected to load flow calculation, and if the topological structure does not meet load flow constraints, the incidence matrixes corresponding to the topological structure are eliminated; a target function and constraint conditions are established, the target function is solved through adoption of an improved particle swarm optimization according to the restraint conditions so as to obtain the best topological structure; the power distribution network is reconstructed according to the best topological structure. The power distribution network reconstruction method and system can reduce needed time of power distribution network reconstruction by improving the optimizing speed.
Owner:CHINA ENERGY ENG GRP GUANGDONG ELECTRIC POWER DESIGN INST CO LTD

Feedback Reconstruction Algorithm for Large Scale MIMO Channels Based on Compressed Sensing

The invention discloses a large-scale MIMO channel feedback reconstruction algorithm based on compressed sensing, including such steps as setting up system model, installing multiple antennas at basestation, serving multiple users at the same time, receiving each user with single antenna, uniformly linearly arranging antennas at base station and obtaining channel matrix at receiving end by channel estimation; 2, a channel state information compression step, vectorizing the channel matrix, a vector is obtained, the vector is compressed by the observation matrix to obtain the observation vector, and the observation vector (img file = 'DEST_PATH_IMAGE001. TIF' wi= '10' he= '14'/) is sent to the base station through the feedback link. S3, the channel state information reconstruction step: after receiving the observed value vector, the base station performs numerical initialization and cyclic iteration, and finally obtains the reconstructed signal. The invention adopts the generalized orthogonal matching pursuit algorithm as the channel feedback reconstruction algorithm, which reduces the iterative times, not only effectively improves the reconstruction accuracy of the channel state information, but also shortens the reconstruction time.
Owner:NANJING UNIV OF POSTS & TELECOMM

Video coding and decoding system based on dictionary learning and compressed sensing

The invention relates to the field of video compressed sensing and image sparse representation, and discloses a video coding and decoding system based on compressed sensing. The video coding and decoding system based on compressed sensing is designed to make a wireless video sensing network have the advantages that the complexity and calculated amount of a coding terminal are small, the volume of data transmitted through a channel is small and a decoding terminal can carry out high-quality real-time video reconstruction. According to the technical scheme, the video coding and decoding system based on dictionary learning and compressed sensing mainly comprises the video coding terminal and the video decoding terminal, wherein the coding terminal is used for temporarily storing image pixel data of K frames, reducing the dimensionality of the image pixel data of the K frames and transmitting data after dimensionality reduction to the decoding terminal through a wireless transmitting module according to the compressed sensing theory, and the decoding terminal is used for decoding the K frames according to the compressed sensing reconstruction algorithm (namely, the improved NSL0 method), storing the K frames and finally forming a video through integration according to frame sequences and outputting the video. The video coding and decoding system based on compressed sensing is mainly applied to video compressed sensing and transmission.
Owner:TIANJIN UNIV

Motion-compensation-and-block-based video compressed sensing processing method

The invention discloses a motion-compensation-and-block-based video compressed sensing (CS) processing method, and relates to the technical field of a video compressed sensing technology. The processing method comprises the steps: 1) a block image residual error frame reconstruction method; 2) a block CS image residual error frame reconstruction algorithm; and 3) a reference frame method based on bidirectional reconstruction. The motion-compensation-and-block-based video compressed sensing processing method uses a motion-estimation algorithm to analyze the motion vector and the residual error data between video frames, and takes the residual error data between video frames to replace the video frames as the compression reconstruction object, so that the video compression ratio is greatly improved. At the same time, the motion-compensation-and-block-based video compressed sensing processing method mainly utilizes a forward/backward bidirectional reconstruction idea and is supplemented by a dynamic adaptive selection reconstruction algorithm, and automatically operates different video reconstruction algorithms according to the exchanging speed of the video content, so that the calculation complexity and the reconstruction time during the video reconstruction process can be effectively reduced.
Owner:袁琳琳

Dual-redundancy FC-AE-1553 network reconstruction method based on switched topology

InactiveCN112468328ATroubleshoot refactoring issuesRestoring transmission scheduling capabilitiesData switching networksNetwork controlEngineering
The invention provides a dual-redundancy FC-AE-1553 network reconstruction method based on switching topology, which comprises the following steps: in a network in which a network communication node adopts a redundant backup design and a node transmission channel is a dual-redundancy channel, adding a network fault detection mechanism and a main / standby node communication function switching mechanism; after the network controller or the network end node breaks down, switching the backup network end node to the network controller, uploading a network message scheduling table, completing networkcommand frame organization scheduling and network management control, and taking over the communication function of the broken-down network controller; or switching to the network end node, and switching the physical mapping relationship between the address of the network end node and the switching port by the network switch, so as to take over the function of the fault end node and complete thenetwork message communication function. According to the method, the reconstruction problem of the switched FC-AE-1553 network is solved, the reconstruction time is shortened, and the network reliability is improved.
Owner:LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC

Active power distribution network reconstruction method and device

The invention discloses an active power distribution network reconstruction method and device. The active power distribution network reconstruction method comprises the following steps: obtaining a plurality of time periods in a preset time; obtaining network loss of a plurality of nodes in an active power distribution network at each time period in the plurality of time periods; comparing the network loss of the plurality of nodes, and sequentially obtaining three nodes, whose network loss is the smallest; carrying out one-to-one pairing on the nodes at adjacent two time periods to form three topological chains, wherein the three nodes are paired with the nodes, of which the switching action times are fewest, in the three nodes at the adjacent time periods in a sequence that the switching action times are from the least to most; and selecting the topological chain, of which the sum of the network loss and the switching cost is the least, in the three topological chains formed in the preset time, as a reconstruction scheme of the active power distribution network, wherein the switching cost is the cost generated by the switching action. According to the reconstruction method and device, the problem that reconstruction of the active power distribution network consumes a relatively long time in the prior art is solved, and the effect of reducing the consumed time of the reconstruction of the active power distribution network is achieved.
Owner:STATE GRID CORP OF CHINA +4
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