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173 results about "Anisotropic diffusion" patented technology

In image processing and computer vision, anisotropic diffusion, also called Perona–Malik diffusion, is a technique aiming at reducing image noise without removing significant parts of the image content, typically edges, lines or other details that are important for the interpretation of the image. Anisotropic diffusion resembles the process that creates a scale space, where an image generates a parameterized family of successively more and more blurred images based on a diffusion process. Each of the resulting images in this family are given as a convolution between the image and a 2D isotropic Gaussian filter, where the width of the filter increases with the parameter. This diffusion process is a linear and space-invariant transformation of the original image. Anisotropic diffusion is a generalization of this diffusion process: it produces a family of parameterized images, but each resulting image is a combination between the original image and a filter that depends on the local content of the original image. As a consequence, anisotropic diffusion is a non-linear and space-variant transformation of the original image.

Remote sensing image registration method based on anisotropic gradient dimension space

ActiveCN105427298AImprove correct match rateOvercome the problem of large nonlinear changes in brightnessImage enhancementImage analysisReference imageImage pair
The invention discloses a remote sensing image registration method based on anisotropic gradient dimension space, which mainly solves the problem of relatively low correct matching rate under the condition of relatively great brightness nonlinear change of the remote sensing images. The implementing steps of the remote sensing image registration method based on anisotropic gradient dimension space are as follows: (1) inputting remote sensing image pairs; (2) constructing dimension space of anisotropic diffusion; (3) calculating a gradient amplitude image; (4) detecting feature points; (5) generating a main direction of the feature points; (6) generating a descriptor of each feature point; (7) matching the feature points; (8) deleting wrongly matched feature point pairs; and (9) registering a reference image and a to-be-registered image. As feature point detection, feature point main direction generation and feature point descriptor generation are carried out on the gradient amplitude image in the anisotropic dimension space, the situation of relatively great brightness nonlinear change of the images can be dealt efficiently, and the remote sensing image registration method based on anisotropic gradient dimension space can be applied to complex multisource and multispectral remote sensing image registration.
Owner:XIDIAN UNIV

Gas infrared image enhancing method based on anisotropic diffusion

The invention relates to a gas infrared image enhancing method based on anisotropic diffusion and belongs to the field of gas detection. The method comprises the following steps of: firstly, preprocessing a gas infrared video sequence image, and respectively processing by two ways, wherein one way uses a forward anisotropic diffusion algorithm so as to spread a gas cloud cluster region, and the other way uses a bidirectional anisotropic diffusion algorithm so as to reduce the noise, and protect and enhance the detail and edge of an image background; then, carrying out discontinuous frame difference on a first processing result, and accumulating difference results; and marking the gas cloud cluster region by the means that a K mean value is clustered in the accumulated result, confirming the position coordinate of the gas cloud cluster, and finally rendering the gas cloud cluster in a colorizing way according to the corresponding position of the coordinate in a second processing result, so that the interpretation property of the gas cloud cluster can be observably improved, the quality of the gas infrared image can be improved, and human eyes can quickly detect the formed gas cloud cluster when the gas leaks. The method can be used for detecting the leakage of the invisible hazardous gas.
Owner:BEIJING INSTITUTE OF TECHNOLOGYGY

Scene flow estimation method based on 3D local rigidity and depth map guided anisotropic smoothing

ActiveCN106485675ASolve the problem of edge distortionReduce repair errorsImage enhancementImage analysisColor imageEnergy functional
The invention relates to a scene flow estimation method based on 3D local rigidity and depth map guided anisotropic smoothing. The method comprises the following steps: S1, acquiring a texture image and a depth image which are aligned at the same time through an RGB-D sensor; S2, building a scene flow estimation energy functional, and calcualting a dense scene flow based on a 3D local rigidity surface hypothesis and a global constrained method, wherein the form of a scene flow energy function is shown in the description; S3, designing date items based on the texture image and the depth image as well as the 3D local rigidity surface hypothesis; S4, designing smoothing items based on a depth map driven anisotropic diffusion tensor and total variation regularization; S5, creating an image pyramid, and adopting a coarse-to-fine solution strategy; and S6, calculating a scene flow by use of a duality method, and introducing scene flow auxiliary variables. According to the invention, the weight of a space-domain filter is determined by both the chromatic aberration and location relationship between the pixels of a color image, and therefore, the edge distortion problem in the process of repair is solved. In order to reduce repair error, the weight of a value-domain filter is determined by the color information and the structural similarity coefficient.
Owner:HARBIN ENG UNIV

Method for extracting video object contour based on centroid tracking and improved GVF Snake

ActiveCN103218830AGet precise contoursGet precise outlineImage analysisMotion vectorVideo sequence
The invention discloses a method for extracting video object contour based on centroid tracking and improved GVF Snake. The method is characterized by comprising the following steps of according to the condition that the movement trend of adjacent frames is similar in short time, dividing a video sequence into a plurality of sections, wherein each section has k frames of video, taking the first two frames in the section as key frames, detecting the effect of eliminating the background border based on the change of t obvious test, and acquiring an initial movement area; extracting a critical quadrangle as an initial contour of the key frames, performing intra-frame GVF Snake evolution, searching the exact contour, then forecasting initial contours of the subsequent frames through the movement vector between centroids of the intra-frame movement object contours of the key frames, and then performing the exact intra-frame GVF Snake contour positioning of the subsequent frames; and by the analogy, extracting the object contour of all frames. The improved model adopts four-direction anisotropic diffusion, and adopts fidelity term coefficients with fast descending speed to enhance the performance to enter into concave; and the convergence to a weak edge is kept. By the method, the shortcoming of manually acquiring the initial contours is conquered.
Owner:丰县新中牧饲料有限公司

Pre-stack seismic parameter inversion method based on anisotropic Markov random field

InactiveCN106932819AAccurately reflect layered featuresImprove protectionSeismic signal processingWeight coefficientLongitudinal wave
The invention discloses a pre-stack seismic parameter inversion method based on an anisotropic Markov random field. The method comprises: establishing an objective function of a pre-stack seismic parameter; calculating a longitudinal wave reflection coefficient based on a Zoprez equation, and obtaining a data item of the objective function according to 2-norm of an error of between a seismic record obtained by measurement and a synthesized seismic record; acquiring anisotropic Markov random domain weight coefficients of data points in different directions by using an anisotropic diffusion method; acquiring a priori constraint term of the objective function; extracting logging data of a to-be-inverted region and carrying out inversion parameter logarithmic linear fitting on the logging data; determining an objective function and carrying out minimum optimizing based on a rapid simulated annealing algorithm; and completing iterative optimization of the objective function and outputting an inversion result. Therefore, the influence of anisotropy of the stratum on the inversion result can be corrected by using the anisotropic Markov weight coefficients, thereby reflecting the stratiform feature of the strata accurately and protecting the fault and the boundary well.
Owner:HOHAI UNIV

Phase-control modeling method for seismic elastic parameters on basis of coordinate multi-phase cooperation Kriging

The invention discloses a phase-control modeling method for seismic elastic parameters on the basis of coordinate multi-phase cooperation Kriging. The phase-control modeling method includes steps of dividing modeling grids inside target layers by the aid of equal-proportion grid division processes and forming a plurality of planes which are used as target locations for modeling elastic parameters; respectively extracting well logging elastic parameters, seismic attribute parameters and sedimentary phase information which are used as modeling data, selecting master variables and selecting first cooperation variables and second cooperation variables; utilizing the obtain master variables, the obtained first cooperation variables and the obtained second cooperation variables as calculation parameters and carrying out interpolation calculation by the aid of coordinate multi-phase cooperation Kriging processes to obtain parameter values of all to-be-estimated points on the planes; carrying out generalization processing by the aid of anisotropic diffusion processes to obtain generalized and processed seismic elastic parameter modeling results. The parameter values of all the to-be-estimated points on the planes are used as multi-source data fusion modeling results. The phase-control modeling method has the advantages that calculation abnormal points and boundary noisy points can be eliminated, accordingly, the multi-information parameter synthetic modeling precision can be improved, a large quantity of real geological information is fused, and accordingly the phase-control modeling is good in applicability.
Owner:HOHAI UNIV
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