35 results about "Least squares matching" patented technology

The invention discloses a steady automatic matching method for high-resolution satellite image connecting points. The method comprises the following steps of: A, performing automatic enhancement by using Wallis filter technology, generating pyramid images of each layer and extracting the images by using feature extraction operators; B, forecasting an initial point position of identical points by using satellite image orientation parameters and upper pyramid matching results of characteristic points, establishing an epipolar geometric constraint equation, and performing geometric coarse correction on matched window images; C, removing error matched points in the matching result of the pyramid images of each layer by using an RFM model-based block adjustment method; and D, repeating the steps B, C and D till the primary image layer, and finally refining the matching result by using a double-sheet least square matching method. The method can greatly reduce the artificial editing workload of connecting point measurement and improve the automation degree of satellite image data processing by combining block adjustment and satellite image matching, and has remarkable economic benefit and social benefit.

Methods and apparatuses for processing seismic data carrying information about a subsurface structure are provided. One method includes splitting the seismic data in groups, each group including subsets of seismic data for which a distance from a respective shot point to a receiver line in a patch of active detectors corresponding to the shot point is within a predetermined range for the group, and extracting signal data for each block Hankel matrix based on an SVD analysis thereof. Another method includes extracting signal data by subtracting from seismic data an estimated noise model obtained by rank reduction of a Hankel matrix followed by dip filtering, enhanced based on a least square matching filter with the seismic data.

The invention discloses a low-altitude remote sensing image high-precision matching method with consistent image space. Firstly, SURF feature matching is carried out on the top layer of an image pyramid, and an affine transformation relation between a base image and a search image is built; then, feature point extraction is carried out on the base image, the affine transformation relation is used as a geometric constraint condition, a feature point window is switched to the search image, meanwhile, a window of the search image is corrected and re-sampled to be in an image space coordinate system of the base image, correlation coefficient matching is carried out, polynomial iteration is used for removing a gross error, obtained corresponding image points are utilized for resolving and updating the affine transformation relation between the base image and the search image again, and then the lower-layer image matching is carried out until bottom-layer image matching; finally, a matching result is converted to be under an image space coordinate system of the search image, and high-precision least squares matching is carried out. The method solves the problems that due to the fact that the problems of large rotating, geometry deformation and the like exist in the image space, the matching success rate is low, and a failure easily happens, and the matching efficiency and the success rate of a low-altitude image are greatly improved.

A method for correcting distortions in multi-focus image stacks comprising the steps: acquiring a plurality of N colour images with an optical system; wherein each color image encompasses a plurality of pixels; converting each of two successive colour images of the N images into monochrome images; scaling each of the monochrome images to a conveniently M by M image; calculating a geometric transformation and a radiometric transformation of the two successive images, wherein the geometric transformation and the radiometric transformation is determined by a set of coefficients, which are determined by least square matching, and using the determined set of coefficients from each of two successive images, to correct each image sequentially and thereby constructing the multi-focus image by applying the determined parameter set to each of the successive images.

The invention relates to an ultrasonic detection image three-dimensional calibration method. According to the method, posture information of an ultrasonic probe is obtained in real time through a receiver on the ultrasonic probe, so that the coordinate of any point, including a cotton line intersection point, in a template can be converted into a receiver coordinate system; an ultrasonic image of the cotton line intersection point is obtained by scanning the cotton line intersection point in the mesh-shaped template through the ultrasonic probe; space vectors are built through the cotton line intersection point in the template, the coordinate of a cotton line intersection point imaging point in the ultrasonic image is calculated according geometric characteristics between the space vectors in the template, and accordingly the relation between the receiver coordinate system Or and a probe scanning image coordinate system Oi is calculated and positioned by means of least square matching of the same point. Compared with the prior art, the coordinate of the same point in an image coordinate system is calculated through the relation of the space vectors, human factor influences caused when the coordinate of the same point of the image is obtained manually in the prior art are avoided, and accordingly the method has the advantages of being high in calibration precision and reconstruction precision, high in calibration speed and the like.

The invention provides a satellite platform chattering detection method and system based on a multispectral image. The satellite platform chattering detection method based on the multispectral image comprises the steps of data preparation, wherein the original multispectral image is preprocessed, and a non-registered multispectral image is obtained; wave band selection, wherein two wave bands for detection are selected; intensive matching, wherein a sample point is selected, a pixel-level matching result is obtained through related image matching, coordinates of homologous image points of the sub-pixel accuracy are obtained through a least-square matching method, and matched homologous points are obtained; chattering analysis, wherein registering errors of the matched homologous points are calculated point by point, the variation of the registering errors along with imaging lines is obtained through analysis line by line, spectral analysis is carried out on platform chattering time sequence data through Fourier transform, and the spectrum features caused by chattering are obtained. The satellite platform chattering detection method and system based on the multispectral image achieve satellite platform chattering detection without high-accuracy and high-frequency chattering measurement equipment, and can accurately obtain the chattering frequency.

The invention relates to a method for matching a remote sensing image and a reference image based on a global geometric constraint. The method is characterized in that the method comprises a step of constructing a geometric model of remote sensing image imaging, a step of reading reference image data and a remote sensing image to be matched and preprocessing the reference image data to obtain thereference image, a step of preprocessing the remote sensing image to be matched, a step of carrying out affine-scale invariant feature transformation matching on the reference image and a remote sensing image to be registered, extracting a feature point and obtaining an initial value of the least squares matching, and a step of carrying out least squares matching through a global constraint leastsquares matching model based on the initial value of the least squares matching and outputting radiation deformation parameters and geometric deformation parameters of the remote sensing image to be registered.

An online automatic matching method for geometric correction of a remote sensing image relates to the technical field of remote sensing image matching. The method has the advantage that uniformly distributed control points are efficiently and reliably obtained by virtue of free or low-cost network image map resources by fully utilizing prior geometric information of the remote sensing image. The method comprises: dividing a to-be-matched image into a plurality of regions according to the number of control points required to be acquired by utilizing an initial imaging model of the remote sensing image, and taking an image block with a certain size in each region as a processing unit; determining an approximate range of a reference image block according to the range of a to-be-matched image unit and the initial imaging model, then downloading the reference image block through a network and re-sampling the reference image block to ensure that the resolution ratio of the reference image block is close to that of the to-be-matched image unit; and performing SIFT matching on the to-be-matched image unit and the reference image block, removing gross error points, finally selecting an optimal matching point from the rest of matching points, performing least square matching, and correcting point coordinates.

A non-contact real-time eye movement identification method based on an intelligent camera comprises the steps that (1) the intelligent camera is used for collecting face images of detected objects and stores the collected images; (2) each eye movement state template is manufactured from the multiple obtained face images according to the different detected objects; (3) official detection is started, and after the images are preprocessed simply, eye interested areas are rapidly positioned from the face images; (4) feature matching is carried out on the intersected areas, the eye movement states are sequentially matched through the least-square matching method based on grey level transformation and geometric transformation, and an accurate identification result is obtained; (5) the original images and the identification result are correlated and output to an interaction touch screen, and the current eye movement state is displayed. The method can be sued for identifying the eye movement direction and the face inclination angle, and has high real-time performance and reliability.

The invention discloses a large-plotting-scale tilt image measuring method based on a depth image; the depth image acquired by dense matching of the tilt images is used as a data source, an image point position of a to-be-measured target is measured on single image, a three-dimensional coordinate of the to-be-measured target is calculated through a geometry relationship between the single image and the depth image, multi-view information of the to-be-measured target is searched through an optimal baseline principle and a least square method, and thus the reliability and stability of the finally obtained measurement three-dimensional coordinate are improved. While the large-plotting-scale image measurement precision can be met, the measurement work efficiency of large-plotting-scale field work measurement is improved, and a large amount of field work measurement workload is saved.

The invention discloses a digital image disguising and reconstructing method based on block sequences. The method comprises the following steps: sub blocks obtained by dividing public image and secret image matrixes are scanned into sequences as secret sequences and public sequences; random disturbance is added to the sequences with the same element value; and least squares matching is performed directly on isometric transformation sequences obtained by cyclically moving the secret sequences rightwards and the public sequences in corresponding positions to find out the cyclical rightward moving step size with minimum residual and matching parameters, so that a secret image is disguised as a public image, and the disguised public image can be reconstructed as a secret image. The method of the invention is easy to implement. As only matching of isometric transformation sequences in corresponding positions is performed, the encoding time is reduced, the number of isometric transformations is increased, the matching accuracy is improved, the problems of detail loss and overflow caused by transformation from a smooth block to a complex block and recovery from a smooth block to a complex texture block can be effectively avoided, and the visual quality of disguised and reconstructed images is further improved.

The invention provides a least-square matching method based on an object space vertical double-face element. The method is mainly used in matching of characteristics points on building corner lines in a city area remote sensing image, and includes the steps of building initial normal vectors of each point in point cloud in dense matching, wherein the initial normal vectors include two vertical initial normal vectors, then building an error equation on the basis of the initial normal vectors of each three-dimensional point, carrying out iterative optimization of the double-face element parameter, and searching for the position of the optimal matching point. Compared with an original single face element algorithm, the characteristic points of the building corner lines can be matched, and model precision of a building in the remote sensing image is greatly improved.

The present invention discloses a digital audio camouflage and reconstruction method based on segmented sequences. The method comprises the steps of taking sub segment sequences obtained by dividing a published audio and a secret audio as a secret sequence and a published sequence, adding random perturbations to the sequences with the same element value, directly carrying out least squares matching on an equidistant transformation sequence obtained by the rotate right of the secret sequence and a corresponding position published sequence, finding a rotate right step length with a minimum residual error and a matched parameter, and thus camouflaging the secret audio as the published audio and further reconstructing the camouflaged audio as the secret audio. The method is easy to realize, since only the corresponding position equidistant transformation sequence matching is carried out, while the encoding time is reduced, the equidistant transformation number is raised, the matching precision is improved, the detail loss and overflow problems brought by the deformation from a smooth block to a complex block and the restoration from the smooth block to a complex texture block can be effectively avoided, and thus the auditory quality of camouflaged and reconstructed audios is improved further.

The invention provides a method for evaluating an influence of information hiding capacity on the measurement precision of a remote sensing image. The method comprises the following steps of: performing information hiding with different capacities on data of the remote sensing image of the original carrier by a remote sensing image information hiding method based on a Forstner characteristic point, and objectively and quantitatively evaluating the quality of the remote sensing image subjected to the information hiding; and evaluating the influence of the information hiding capacity on the measurement precision of the remote sensing image by a least square matching method. Therefore, an objective and accurate reference standard is provided for design of a better information hiding algorithm; and the method is high in practical value.

The invention discloses an optical satellite remote sensing image detection method. The invention provides an optical satellite remote sensing image detection method, and the method comprises the steps: obtaining an optical satellite remote sensing image, extracting a shadow region in the optical satellite remote sensing image, carrying out the shadow region reconstruction processing of the shadow region, and constructing a ratio graph and a multi-scale detail graph based on the optical satellite remote sensing image after the shadow region reconstruction processing. Performing binaryzation on the multi-scale detail image, distinguishing a target area, extracting an area of interest from a downward-looking image of the target area, performing prediction of the same area of interest on a forward-looking image and a backward-looking image in the target area according to the area of interest, and performing prediction of the same area of interest on the basis of epipolar constraint conditions. And performing least square matching on the downward-looking image, the forward-looking image and the rear-looking image, and performing forward intersection according to a matching result to obtain a digital earth surface model, so that the processing efficiency of remote sensing satellite image data is further improved.

The invention belongs to the technical field of remote sensing image processing image matching, and discloses a least square matching method based on adaptive object-side elements, and the method comprises the steps: obtaining an initial object-side three-dimensional point coordinate through the spatial forward intersection and collinear equation projection relation of an initial matching image pair, and taking the initial object-side three-dimensional point coordinate as an object-side element main point; determining the size of a matched object aspect element and the position of a to-be-matched pixel in the image window according to the correlation of each pixel in the image window obtained by projecting the object-object element to the to-be-matched image by taking the object-object element main point as a reference, and establishing an error equation according to a spatial geometric projection relationship; and obtaining radiation distortion and geometric distortion correction values through least square iterative optimization, and searching for an optimal matching point position. The method can improve the matching precision and the matching success rate.

The invention is a multi-channel based least-square matching method. The method is mainly used for matching and optimization of multi-channel remote sensing images. The method comprises the steps thatfirstly, a fixed-size image window which centers on initial rough matching points is selected; then, an error equation is established based on brightness values of corresponding pixels in corresponding channels in the image window, radiometric distortion and geometric distortion are conducted to correct iterative optimization of parameters, and the best matching point location is searched for. Compared with an original grayscale image-based matching method, the method can reduce the interference of color differences on matching results and improve the precision and stability of remote sensingimage matching.