176 results about "Anisotropic diffusion" patented technology

The invention described herein relates to structured porous materials, where the porous structure provides a tailored Poisson's ratio behavior. In particular, the structures of this invention are tailored to provide a range in Poisson's ratio ranging from a negative Poisson's ratio to a zero Poisson's. Two exemplar structures, each consisting of a pattern of elliptical or elliptical-like voids in an elastomeric sheet, are presented. The Poisson's ratios are imparted to the substrate via the mechanics of the deformation of the voids (stretching, opening, and closing) and the mechanics of the material (rotation, translation, bending, and stretching). The geometry of the voids and the remaining substrate are not limited to those presented in the models and experiments of the exemplars, but can vary over a wide range of sizes and shapes. The invention applies to both two-dimensional structured materials as well as three dimensionally structured materials.

A light guide plate has a hologram pattern on a light exit surface. The hologram pattern anisotropically diffuses light in the direction parallel with a light incident surface of the light guide plate. On a back surface of the light guide plate are formed mirror-polished prism structures extending parallel with the light incident surface. A downward-pointing prism sheet with a given prism apex angle is placed on the light exit surface of the light guide plate. The use of the downward-pointing prism sheet together with the light guide plate having the anisotropic diffusion hologram pattern integrally formed thereon produces a liquid crystal display device with enhanced luminance properties.

A noisy image is transformed through a wavelet transform into multiple scales. The wavelet coefficients are classified at each scale into two categories corresponding to irregular coefficients, edge-related and regular coefficients. Different denoising algorithms are applied to different classes. Alternatively, a denoising technique is applied to the finest scale, and the wavelet coefficients at all scales are denoised through anisotropic diffusion.

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.

A method for background replacement. The method takes an input image of one or more frames of video, or a still image, and performs an initial classification of the pixels (14) as foreground or background pixels. The classification is refined (16) using one of several techniques, including anisotropic diffusion or morphological filtering. After the refined classification is completed, a feathering process (18) is used to overlay the foreground pixels from the original image on the pixels of the new background, resulting in a new output image (20).

A light source device includes an excitation light source that generates excitation light, a phosphor wheel including a phosphor segment that generates fluorescent light by excitation of the excitation light, and a mirror that guides the excitation light from the excitation light source to the phosphor wheel and emits the fluorescent light from the phosphor wheel as illumination light. The phosphor wheel further includes an anisotropic diffusion and reflection unit that diffuses and reflects incident excitation light such that an optical path for the incident excitation light and an optical path for the diffused excitation light after incidence of the excitation light are not overlapped. The mirror includes a first region that reflects the excitation light and transmits the fluorescent light and a second region that transmits the fluorescent light and the diffused excitation light which the anisotropic diffusion and reflection unit has diffused and reflected.

A method for image relighting is presented which receives an input image having at least one spurious edge directly resulting from a first illumination present when the input image was acquired, performs anisotropic diffusion on the input image to form a diffusion image, removes the first illumination using the diffusion image to generate a reflectance image and applies a second illumination to the reflectance image. An apparatus for relighting is presented which includes a processor operably coupled to memory storing input image having a first illumination present when the input image was acquired, and functional processing including an anisotropic diffusion module to perform anisotropic diffusion on the input image to form a diffusion image, a combination module which removes the first illumination using the diffusion image to generate a reflectance image, a second illumination module which generates a second illumination, and a lighting application model which applies the second illumination.

A computer system for processing interferometric synthetic aperture radar (SAP) images includes a database for storing SAR images to be processed, and a processor for processing interferometric SAR images from the database. The processing includes receiving first and second complex SAR data sets of a same scene, with the second complex SAR data set being offset in phase with respect to the first complex SAR data set. Each complex SAR data set includes a plurality of pixels. An interferogram is formed based on the first and second complex SAR data sets for providing a phase difference therebetween. A complex anisotropic diffusion algorithm is applied to the interferogram. The interferogram includes a real and an imaginary part for each pixel. A shock filter is applied to the interferogram. The processing further includes performing a two-dimensional variational phase unwrapping on the interferogram after application of the shock filter.

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.

The invention provides a raindrop identifying method, belongs to the field of digital image identification, and aims to automatically identify a raindrop target in the raindrop image and extract related raindrop information so as to improve the automation and precision of raining weather phenomenon observation. The method is applied to automatic observation and acquisition of a raindrop spectrum in the raining weather phenomenon observation. The method comprises the following steps in sequence: 1, image acquisition; 2, image pretreatment; 3, image differentiation; 4, extraction of the edge gradient image; 5, binarization of the edge gradient image; 6, image morphologic treatment; and 7, extraction of the raindrop information. In the method of the invention, the anisotropic diffusion smoothing filter is used as a method for the image pretreatment, the edge gradient information is used as effective characteristics of the raindrop target, an image morphologic method is also utilized to effectively identify the raindrop target and extract the related raindrop information, and thus the automaticity and the precision on the raining weather phenomenon observation can be improved.

The invention discloses a method for segmenting a three-dimensional ultrasonic image, belonging to the technical field of the digital image processing. The method comprises the following steps: (1) preprocessing spots of the three-dimensional ultrasonic image by adopting a normalized anisotropic diffusion method of a three-dimensional wavelet according to the characteristics of the three-dimensional ultrasonic image to remove spot noise; (2) initializing the preprocessed three-dimensional ultrasonic image by adopting a Canny edge detection operator; and (3) segmenting the three-dimensional ultrasonic image three-dimensionally by using a B-Surface and GVF Snake based three-dimensional deformation model. The method disclosed by the invention can be used to rapidly and accurately segment the three-dimensional ultrasonic image and particularly has strong noise robustness. The method for automatically segmenting the three-dimensional ultrasonic image can be also used for segmenting other three-dimensional images such as CT (computed tomography) images, MRI (magnetic resonance images) and PET (position-emission tomography) images, thereby having high application value.

An illumination device includes a diffusion member having an anisotropic diffusion surface, a rotary shaft member configured to rotate the anisotropic diffusion surface while a coherent light beam from a light source is illuminated on the anisotropic diffusion surface, and an optical device that further diffuses a coherent light beam diffused on the anisotropic diffusion surface, wherein the coherent light beam diffused on the anisotropic diffusion surface is diffused in a form of line and the diffused coherent light beam in the form of line is configured to move to draw a locus of rotation in one direction in accordance with the rotation of the anisotropic diffusion surface.

The invention discloses a method for denoising and enhancing an anisotropic diffusion image with controllable diffusion degree based on a track model. The method is characterized by comprising the following steps of: firstly, calculating a structure tensor and a Hessian matrix of each pixel point; secondly, decomposing the characteristic values of the structure tensor of each image point; thirdly, constructing a diffusion tensor of each image point, enabling the characteristic vector of the diffusion tensor to be the characteristic vector of the structure tensor, making the characteristic value as a function of the diffusion rate, i.e., a function of the characteristic value of the structure vector, and making the diffusion degree controllable by adjusting the parameter of the function; and finally, iteratively solving the track model. By adopting the method, the image can be effectively denoised and enhanced.

A light guide plate 10 comprising an entry surface 11 on at least one side surface, a rectangular exit surface 12 orthogonal to the entry surface 11 and a reflecting surface 13, wherein the reflecting surface 13 has a deflection pattern that receives a ray of light incoming from the entry surface 11 or the exit surface 12 at a certain angle to the normal to the exit surface 12 and outputs the ray of light at a reduced angle to the normal, the deflection pattern has a plurality of arcuate deflection pattern elements formed on a plurality of concentric circles, the exit surface 12 has an anisotropic diffusion pattern that transmits so as to spread, a ray of light incoming from the deflection pattern at an angle up to a specified angle with respect to the normal the exit surface 12, the anisotropic diffusion pattern spreads the ray of light incoming from the deflection pattern so that the width of diffusion in a direction orthogonal to the radial direction of arcs of the concentric circles is larger than that in the radial direction, and the center of the concentric circles is positioned on any one of the side surfaces of the light guide plate 10 or in the vicinity thereof.

This invention describes methods and systems for tasking nodes in a distributed ad hoc network. A node is selected to participate in a data gathering or a routing task based on its potential contribution to information gain and the cost associated with performing the task such as communication bandwidth usage. This invention describes methods and systems for implementing various selection strategies at each node, using local knowledge about the network. For resource-limited sensor networks, the information-driven data gathering and routing strategies significantly improve the scalability and quality of sensing systems, while minimizing resource cost.

An antiglare film has an internal diffusion layer, composed of a transparent matrix and a transparent diffusive material, and surface irregularities. The diffusive material has a different refractive index from the transparent matrix, exhibits anisotropic diffusion resulting from the anisotropic shape of the particles thereof, and is dispersed in the transparent matrix so that the particles are oriented parallel to one another and to a normal to the film.

Methods and apparatuses for image processing are presented. An exemplary method is provided which provides a model which includes information not found in the digital image, accessing digital image data and the model, and performing anisotropic diffusion on the digital image data utilizing the model. An apparatus for processing a digital image is presented which includes a processor operably coupled to memory storing digital image data, a model which includes information not found in the digital image data, and functional processing units for controlling image processing, where the functional processing units include a model generation module, and a model-based anisotropic diffusion module which performs anisotropic diffusion on the digital image data utilizing the information provided by the model.

The invention discloses a depth image enhancement method based on anisotropic diffusion. The similarity among pixel points of a color image corresponding to a depth image is used as a basis of depth diffusion, and based on the known depth of the depth image, filling of a depth missing region of the depth image is finished. Through the depth image enhancement method based on the anisotropic diffusion, the defect that in a traditional depth enhancement method based on interpolation, edges of an object are blurry is overcome, meanwhile, the limit of the size of a wave filtering window in a depth enhancement method based on wave filtering is broken through, and the depth image enhancement method based on the anisotropic diffusion has the advantages of being high in universality, high in robustness and the like. The depth image enhancement method based on the anisotropic diffusion can be widely used for a variety of depth images which have missing depth regions, and in a practical application process, based on the color image and the depth image which are in correspondence to each other, a good depth image missing region filling effect can be achieved.

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.

The invention discloses a mobile phone image denoising method based on wavelet transform edge detection. The mobile phone image denoising method disclosed by the invention can be used for effectively smoothing noise, reserving image edge details and removing colour noise at the same time, so that an ideal denoising effect is obtained. The mobile phone image denoising method disclosed by the invention comprises the following steps: firstly, reading a colour noise image, and converting an input image into a YUV colour space from an RGB colour space; secondly, smoothing the image by adopting a Gaussian filter, and carrying out lowpass filtering on a Y channel image three times; thirdly, detecting the edge of the image by utilizing a wavelet transform algorithm; fourthly, obtaining a binary image of the edge by carrying out threshold segmentation; fifthly, smoothing noise by carrying out anisotropic diffusion at the edge region of the image; sixthly, carrying out mean filtering in a smooth region of the image for denoising; seventhly, further removing the colour noise from the image in the smooth region; and eighthly, converting the image into the RGB colour space from the YUV colour space to obtain a final denoised image.

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.

An exemplary illumination normalization method is provided which includes receiving an input image having at least one spurious edge directly resulting from illumination, performing anisotropic diffusion on the input image to form a diffusion image, and removing at the least one spurious edge using the diffusion image. Another embodiment consistent with the invention is an apparatus for performing illumination normalization in an image which includes a processor operably coupled to a memory storing input image data which contains an object of interest having at least one spurious edge directly resulting from illumination, a model of a representative object of interest, and functional processing units for controlling image processing, wherein the functional processing units further include a model based anisotropic diffusion module which predicts edge information regarding the object of interest based upon the model, and produces a reflectance estimation utilizing the predicted edge information.

Provided is a side light type surface light source, which has a high light use efficiency, a high luminance and a wide view angle. A liquid crystal display device using such light source is also provided. The surface light source is provided with a light source; a light guide body having at least one light incoming surface facing the light source and a light outgoing surface substantially orthogonally intersecting with the light incoming surface; and a first optical film arranged to face the light outputting surface. On the light guide body, a plurality of linear grooves or linear protruding sections are arranged substantially parallel on the light outputting surface or on the rear surface of the light outputting surface not outputting light. The first optical film has anisotropic diffusion characteristics, and is arranged to have a direction, in which the anisotropic diffusion is maximum, substantially parallel to the longitudinal direction of the linear grooves or the linear protruding sections.

The invention discloses an automatic precise partition method for a prostate ultrasonic image and belongs to the field of computer-aided diagnosis. The method comprises the following steps of: extracting the textural features of the prostate ultrasonic image under different scales through Gabor by using a multi-scale space constructed by anisotropic diffusion; meanwhile, constructing a prostate shape space by a non-parameter kernel density estimation method, and searching in the shape space through mean shift; under the dual constraints of the textural features and the shape space, roughly partitioning a prostate contour; and finally, refining a partition result in a self-adaptive detection range by using active contour models in combination with orientation gradients, and accurately partitioning the prostate ultrasonic image stably at last. By the method, the problems of low contrast ratio of ultrasonic images and large interference of speckle noise and shadow areas in partition are solved; the prostate ultrasonic image can be accurately partitioned; and the method can adapt to ultrasonic machines which are produced by different manufacturers and have different models, and is not sensitive to the parameter setting of an ultrasonic imaging system.

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.

A method, apparatus, and medium for removing shading of an image are provided. The method of removing shading of an image includes: smoothing an input image; performing a gradient operation for the input image; performing normalization using the smoothed image and the images for which the gradient operation is performed; and integrating the normalized images. The apparatus for removing shading of an image includes: a smoothing unit smoothing an input image using a predetermined smoothing kernel; a gradient operation unit performing a gradient operation for the input image using a predetermined gradient operator; a normalization unit performing normalization using the smoothed image and the images for which the gradient operation is performed; and an image integration unit integrating the normalized images. According to the method, apparatus, and medium, by defining a face image model analysis and intrinsic and extrinsic factors and setting up a rational assumption, an integral normalized gradient image not sensitive to illumination is provided. Also, by employing an anisotropic diffusion method, a moire phenomenon in an edge region of an image can be avoided.

An exemplary illumination normalization method is provided which includes receiving an input image having at least one spurious edge directly resulting from illumination, performing anisotropic diffusion on the input image to form a diffusion image, and removing at the least one spurious edge using the diffusion image. Another embodiment consistent with the invention is an apparatus for performing illumination normalization in an image which includes a processor operably coupled to a memory storing input image data which contains an object of interest having at least one spurious edge directly resulting from illumination, a model of a representative object of interest, and functional processing units for controlling image processing, wherein the functional processing units further include a model based anisotropic diffusion module which predicts edge information regarding the object of interest based upon the model, and produces a reflectance estimation utilizing the predicted edge information.

The backlight has an anisotropic diffusion sheet disposed between the reflective polarizing plate and the optical path converter. The anisotropic diffusion sheet includes a refractive index anisotropic diffusion sheet stretched in an absorption axis direction in which a concave-convex portion is formed on a surface of the reflective polarized plate, and an isotropic material part laminated on a surface of the concave-convex part. The isotropic material part has an isotropic reflective index. The refractive index of the isotropic material part is the same as the refractive index in the transmission axis direction perpendicular to a stretching direction of the refractive index anisotropic sheet.

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.