91 results about "Matrix completion" patented technology

The invention relates to the technical field of 3D point cloud data processing and 3D scene reconstruction. A fusing method of a 3D laser point cloud and a 2D image comprises the following steps: (1) making a black-and-white grid vertical hole calibration board; (2) collecting 3D laser point cloud and 2D images; (3) calculating the space coordinates of the centers of the vertical holes; (4) calculating the pixel coordinates of the centers of the vertical holes; and (5) calculating a mapping matrix to complete data fusion. The method has the advantages as follows: firstly, linear point cloud data of a laser scanner and image data shot by a camera are used, and the amount of data sampled is small; secondly, for solving of the mapping relation between 3D laser point cloud and 2D images, the amount of calculation is small, the calculation process is simple, and the calculation efficiency is high; thirdly, real-time 3D laser point cloud and 2D image fusion can be realized; fourthly, the space coordinates of the centers of the vertical holes are calculated using an interval matrix, there are multiple constraints, and calculation is more accurate; and fifthly, the homographic relation between the laser scanning plane and the camera imaging plane is directly constructed based on the imaging principle of the camera to solve the mapping matrix, and the calculation method is simple and reliable.

The invention relates to a method for error suppression of inertial concretionary coarse alignment of a strapdown inertial navigation system and belongs to the technical field of inertial navigation. The method comprises the following steps of 1, according to current longitude and latitude of a carrier, carrying out transformation of an earth coordinate system into a navigation coordinate system, 2, driving two shafts of a rotation-type inertial navigation system to periodically rotate according to a certain rotating scheme, 3, according to angular velocity information output by a gyroscope in coarse alignment, updating a direction cosine matrix of a posture change of an inertial measurement unit (IMU) coordinate system relative to a p0 coordinate system through calculating a numerical solution of a matrix differential equation, and 4, orderly calculating solutions of matrixes to obtain a posture matrix of the carrier so that coarse alignment is finished. The method has the advantages that through an integral operation in coarse alignment, swinging and shaking-caused error components of outputs of an accelerometer of a ship in alignment of storm-caused swinging and shaking can be compensated; and through IMU double-shaft rotation modulation, an accelerometer zero-bias error accumulated over time is suppressed so that the precision of inertial concretionary coarse alignment is improved.

The invention relates to a superpixel segmentation method based on the fuzzy theory. The superpixel segmentation method improves fitness of superpixel edges and original image edges, and segmented superpixels have an undiversified internal structure and uniform gray scale. The superpixel segmentation method comprises steps of 1) processing images and initializing cluster centers; 2) adding coordinate distances of pixel points into the fuzzy C-means clustering algorithm and establishing an objective function; 3) updating a membership matrix; 4) updating cluster centers with gray scale values and coordinates included; 5) repeating steps 3) and 4) until a termination condition that the change amount of the cluster center gray scale values is smaller than an artificially set threshold value or iteration times are larger than some artificially set value; 6) completing initial superpixel division based on the finally obtained membership matrix; and 7) performing post-processing to complete the final superpixel division by combining sets of points ,which are isolated and unavoidably exist in superpixels generated after the above six steps, with adjacent superpixels which have the maximum similarity.

The invention discloses a realization method of an FDA MIMO radar system based on matrix completion, belongs to the field of radar technology, and aims at reducing measuring data which needs processing and obtaining higher distance, angle and Doppler-dimension resolutions. The method comprises the following steps that 1) according to practical requirements and characteristics of the FDA MIMO radar system, an emission carrier wave, an frequency array, the amount of emission antennas and the code-element length of the emission carrier wave are determined, and an emission model of a FDA MIMO radar is established; 2) according to a target space environment, the type of reception antennas and the amount of antennas of the FDA MIMO radar are determined, and a reception signal model is constructed; 3) based on obtained partial reception data, a Lq norm space processing technology to obtain recovery of a data matrix; and 4) the data matrix is combined with a parameter estimation method to obtain combined estimation of a target distance, an orientation 2D space and Doppler.

The invention discloses a method for estimating the angle of MIMO (Multiple-Input Multiple-Output) radar with array element faults based on block Hankel matrix completion. According to the method, firstly, a matrix with a 2-fold Hankel structure is constructed by using column vectors of a virtual array covariance matrix, a block Hankel matrix with a 4-fold Hankel structure is constructed by takinga matrix formed by column vectors as a sub-matrix for enabling each row and each column of the constructed block Hankel matrix to have sampling elements and meet the low-rank property, and missing data in the block Hankel matrix is completed by utilizing matrix completion; then, the corresponding redundant elements are averaged in the recovered block Hankel matrix; and finally, inverse transformation is carried out on the block Hankel matrix without data missing to obtain a complete virtual array covariance matrix, and the DOD (Direction of departure) and DOA (Direction of arrival) of a target are estimated by adopting an array covariance matrix-based algorithm (such as an ESPRIT algorithm). According to the method, a large amount of missing data in the covariance matrix of the MIMO radarvirtual array with the array element faults can be effectively recovered, and the angle estimation performance when the array element faults are transmitted or received is improved.

The invention discloses a non-local image inpainting method based on low-rank matrix recovery. The method comprises the following steps: pre-completing a low-rank texture and a natural image respectively; partitioning the pre-completed image into a plurality image blocks, and calculating the matching block matrix of each image block on the basis of block matching and a grouping method; inpainting each image block in the matching block matrix by using low-rank matrix completion; integrating the repairing results of all the image blocks, and repairing an image to be repaired according to an integration result. Two image completion methods based on examples and numerical calculation are used comprehensively. The method has a wider application scene range than an existing image completion method. In particularly, the image can be reconstructed from random sampling in an almost perfect way. Moreover, pre-completion is performed firstly, and block completion is performed secondly in a grouping way, so that the repairing accuracy is increased greatly. The method can be conveniently applied to a plurality of practical applications such as rendering acceleration, image inpainting and object removal.

In a method and magnetic resonance (MR) apparatus for MR image reconstruction, an image reconstruction algorithm is used that operates on one calibration matrix that is formed by reorganizing a number of individual, undersampled k-space data sets respectively acquired by multiple reception coils in a parallel MR data acquisition from a subject exhibiting motion. The motion causes the k-space data sets to exhibit errors. In order to use the calibration matrix in the reconstruction algorithm, it is subjected to an iterative rank reduction procedure in which, in each iteration, a residual is calculated for each data point that represents how poorly, due to motion-induced corruptions, that data point satisfies the low rank constraint, and non-satisfying data points are removed from the data point for the next iteration. The resulting low rank matrix at the end of the iterations is then used to produce images with fewer motion-induced errors.

A method and system are proposed to obtain a reduced speckle noise image of a subject from optical coherence tomography (OCT) image data of the subject. The cross sectional images each comprise a plurality of scan lines obtained by measuring the time delay of light reflected, in a depth direction, from optical interfaces within the subject. The method comprises two aligning steps. First the cross sectional images are aligned, then image patches of the aligned cross sectional images are aligned to form a set of aligned patches. An image matrix is then formed from the aligned patches; and matrix completion is applied to the image matrix to obtain a reduced speckle noise image of the subject.

The present invention belongs to the field of network management and network measurement and provides an SDN-based network flow matrix measurement method, which aims to meet the constraint of the flow-aggregation feasibility and the constraint of limited resources for network measurement and lowers the estimation error of a flow matrix. According to the technical scheme of the invention, the flows of the same destination node are aggregated together, and a convergence matrix is designed based on the de-agglomeration and routing rules. The flow matrix is estimated through the two-step process. During the first step, a routing rule (namely called an old rule) composed of most aggregated flows is selected to generate a new rule, so that the difference between the number of aggregated flows in the old rule and the number of aggregated flows in the new rule is minimum. After that, a flow matrix is estimated through the matrix completion technology. During the second step, the flow matrix estimated during the first step is adopted as a basis, and the largest front k flows are selected from the flow matrix to be measured directly. According to the technical scheme of the invention, the measurement period is shortened and the difficulty in directly measuring each flow is reduced. Meanwhile, the constraint of the flow-aggregation feasibility is met, and the estimation error is relatively low.

The invention relates to a recommendation system data completion method based on convex optimization local low-rank matrix approximation. The method includes the steps of 1) constructing a recommendation system data matrix M according to the user's rating of a product in a recommendation system, and representing the data on unrated products by the user as 0 element in M; 2) selecting anchor points, dividing the recommendation system data matrix into a plurality of local matrices using a kernel smoothing method, the number of local matrices being the same as the number of the anchor points; and 3) solving a matrix completion model according to a convex optimization local low-rank matrix approximation algorithm, and completing the 0 element in the matrix M according to the matrix completion model to obtain a recommendation system data matrix X after completion. Compared with the prior art, the invention can finish the recommendation system matrix data completion while guaranteeing the operation speed and the accuracy.

The invention relates to a registration method for an inspection tour map and a reference map based on SURF characteristics. The registration method comprises the following steps: acquiring the inspection tour map and the reference map of a target area; Extracting features in the image by using an SURF algorithm; carrying out Euclidean distance sorting on the feature points after feature extraction, calculating Euclidean distances between all SURF feature points of the inspection tour map and the reference map, and finding out a minimum distance value; Arranging the inspection images subjectedto feature extraction and the reference image in parallel, and performing second screening of registration point pairs near an average value of registration lines; And for the screened matching pointpairs, calculating an affine transformation matrix, and utilizing the matrix to complete registration of the inspection tour map and the reference map. According to the method, the inspection tour map and the reference map are registered by using the SURF features, the SURF operator has scale and rotation invariance, and has very high robustness on image noise, light change, affine deformation and the like, so that accurate feature descriptor extraction can be carried out for the same object in the inspection tour map and the reference map.

An image fusion method based on contrast analysis comprises the following steps of: 1, constructing the morphological gradient graph of an input image and the morphological gradient graph of an enhanced image of the input image separately; 2, subjecting the morphological gradient graphs of the input image and the enhanced image thereof to subtraction to obtain a contrast difference graph of the unenhanced and enhanced input images; 3, creating a fusion coefficient matrix according to the contrast difference graph; and 4, fusing the input image and the enhanced image thereof according to the fusion coefficient matrix, subjecting fused processed image pixels to range control in order that the pixels are within a reasonable image range and are output. The single-graph fusion of the present invention aims at the fusion of the input image and the enhanced image thereof which have the same image information essence and is not fusion of different images. The image output by the image fusion method has uniform grayscale distribution and has completely retained details. The method is effective on not only grayscale images, but also color images, and is higher in fidelity of the restoration of the color images in associated color channels.

A feedback application may be executing on a data processing system to transmit a screen update to at least two computers. The feedback application receives an indication of completion from a first computer, in response to transmitting the screen update. The feedback application updates a completion gauge to indicate a partial completion among participants, in response to receiving the indication of completion from the first computer. The feedback application receives a second indication of completion from a second computer, in response to transmitting the screen update. The feedback application updates the completion gauge to indicate a completion among participants, in response to receiving the indication of completion from the second computer.