39 results about "Texture gradient" patented technology

A method for quantifying the texture homogeneity of a polycrystalline material is described. The method involves selecting a reference pole orientation; scanning in increments a cross-section of the polycrystalline material having a thickness with scanning orientation imaging microscopy or other measuring technique to obtain actual pole orientations of a multiplicity of grains throughout the cross-section of the polycrystalline material. The orientation differences between the reference pole orientation and actual pole orientations of a multiplicity of grains is then determined. A value of misorientation from the reference pole orientation at each grain measured throughout the thickness is then assigned. The average misorientation of each measured increment throughout the thickness is then determined. A texture gradient and/or texture banding can then be obtained by determining the first and/or second derivative, respectively, of the average misorientation of each measured increment through the thickness of the sample used for evaluation. A method to predict the sputtering efficiency of a target is also described as well as a system for quantifying the texture homogeneity of a polycrystalline material.

The invention discloses a segmentation method of a watershed texture image on the basis of morphological Haar wavelet gradient extraction, which relates to the technical filed of image processing and aims at solving the excessive segmentation problem of watershed texture image segmentation. The method not only can reduce excessive segmentation, but also is much better than other post processing methods solving the problem of excessive segmentation in arithmetic speed. The steps for realizing the method are as follows: (1) a texture gradient image TG is extracted by carrying out morphological Haar wavelet conversion to the original texture image; (2) after circumrotating by 90 degrees, the original image is used for extracting a texture gradient image RTG with a morphological Haar wavelet; (3) the texture gradient image RTG and the texture gradient image TG are subjected to circumrotation weighting to obtain a texture gradient image G; (4) morphological filtering is carried out to the texture gradient image G to obtain a texture gradient image OCG after being smoothed; and (5) marker-watershed segmentation is carried out to the texture gradient image OCG to obtain the final texture segmentation result. Compared with the image segmentation standards, the image segmentation result of the method is validated to basically meet standards.

The invention discloses a textile defect detecting algorithm based on texture gradients. Firstly, texture gradients of sub-band characteristics after wavelet transformation are calculated, marked watershed segmentation is carried out on a texture gradient image, and a textile defect detecting system based on the texture gradients is primarily finished; secondly, non-local average filtering is utilized to eliminate imaging noise in a textile image and influences of other uncorrelated details, useful texture details are highlighted, preprocessing is completed, and texture enhancement is achieved; at last, on the bases of the texture enhancement and the texture gradients, an MRF model is utilized to extract a defect zone boundary, texture defects can also be well extracted by means of the method, and the defect that in watershed marking, a threshold value needs to be chosen manually is eliminated. The textile defect detecting algorithm based on the texture gradients has the advantages of being capable of rapidly and accurately distinguishing defects of textiles and wide in application, improving the quality of the textiles, and the like.

The invention relates to a method for manufacturing a glazed tile with a glaze three-dimensional effect. The method comprises a printing process of printing on an unglazed biscuit through a relief silk screen plate with a certain thickness and a relief roller with a certain depth, so as to form texture patterns with a variable concave-convex effect, and a once-firing process, thus preparing the glazed tile with a glaze three-dimensional effect. The glazed tile manufactured by the invention can generate a concave-convex texture gradient effect, and is good in decoration effect, high in durability, good in antifouling performance, variable in patterns, and can well reflect change of the natural color of stone.

The invention discloses a visual perception enlightening high-resolution remote-sensing image segmentation method, and the method enables an object boundary in an image to be divided into an intensity boundary corresponding to a spectrum homogeneous area, and a texture boundary corresponding to a spectrum change area, and respectively extracts two types of visual information which serve as the main basis of segmentation. The method comprises the steps: filtering noise and texture information in the image through a nonlinear filtering method, and obtaining the intensity gradient through a gradient operator; analyzing the texture features of the image through employing a Gabor filter, enabling the filtering output of a plurality of channels to be merged and processed through the gradient operator, and obtaining the texture gradient of the image; carrying out the fusion of the intensity gradient and the texture gradient, carrying out the conversion of the gradient image after fusion through watershed conversion, and achieving the segmentation of the image. Compared with the prior art, the method improves the boundary accuracy of image segmentation, reduces the over-segmentation and under-segmentation phenomena, and can be effectively used in the field of high-resolution remote-sensing image information processing.

The invention discloses a white cell segmentation method based on multi-feature nonlinear combination. The method includes extracting the gray scale of white cells, color and texture gradient information of CIE Lab space and spectrum information of the white cells; combining in a nonlinear manner; processing the combined information in manners of orientated watershed transform and ultra metric boundary mapping OWT-UCM, and acquiring algorithm segmented results; performing corresponded parameter adjustment of the algorithm segmented results and expert segmented results; determining parameters until acquiring a predetermined segmentation result, and finally using the parameters for segmenting other white cells. The method has the advantages that the single feature noise influence is reduced, multiple pieces of feature information are combined in the nonlinear manner, the smaller training errors can be acquired as compared with that of the linear combination method, and the better segmentation result can be acquired; meanwhile, the combination information can be adjusted in an iterative manner, parameters of the network can be adjusted, a target can be closer gradually according to the predetermined result, and the target unavailability and inappropriate adjustment are avoided.

A decorative covering for an internal trim component for a vehicle comprises an outer surface that includes a gradient characteristic when referenced to an adjacent trim component. The gradient characteristic may comprise a plurality of texture gradient zones and/or a plurality of color gradients. A method of manufacturing the decorative covering and the internal trim component with the decorative covering is also disclosed.

The invention relates to an anti-shadow and anti-covering method for detecting and tracing multiple moving targets and belongs to the technical field of image processing. The method comprises the following steps: performing mixed gauss based background modeling by combining a classified floating strategy; segmenting a moving target prospect by using a three-frame difference algorithm combining with an 8 neighborhood summation operation; adopting shadow detection with invariant texture gradient difference and color characteristics to mark a detected shadow to be red; eliminating a red shadow area at a target tracking stage; and performing multi-target tracing by adopting a strategy of combining Camshift and Kalman wave filtering. The anti-shadow and anti-covering method for detecting and tracing the multiple moving targets can be used for effectively detecting shadows of the moving targets, is small in calculated amount and high in real-time property, can effectively improve a 'cavity' phenomenon, has good stability for detecting the moving targets, and meanwhile can realize stable tracing of the moving targets in a shielding scene.

The invention relates to a bionic compound eye microlens technology-based 3-3-2 dimension object detection method and system. Through a bionic compound eye microlens system-based low-resolution data acquisition method, an object region is subjected to capture imaging, according to microlens array images taken by two microlens devices, constructing a low-resolution image by a linear weighted average method, reconstructing a 3D profile of an object by a forward intersection measurement method, if the object image is effectively captured and is shown in the low-resolution image, reconstructing a high-resolution image of the object region by the microlens array images as base data by a regularization method, and after the high-resolution 2D image of the object region is acquired, carrying out precise recognition on the object by a texture gradient-based GAC model. Through addition of a process for acquiring the 3D profile of an object by a low-resolution image, redundant image unmeaning processing is effectively avoided and real-time processing efficiency and accuracy of the system are improved.

A confidence map for optical flow gradients is constructed calculating a set of census texture gradients for each pixel of an image, filtering said gradients and extracting confidence values from said gradients using a plurality of decision tree classifiers. A confidence map is then generated from said confidence values.

The invention provides a bidirectional intra-frame directional prediction method and device. According to the method, the texture gradient property of a coding block is utilized, and the defect that the boundary discontinuity of intra-frame prediction and the intra-frame prediction precision are reduced as the distance between a prediction pixel and a reference pixel is increased is solved. According to the method, the gradient characteristic of a residual error of the coding block is considered, and the prediction adopts an exponential relationship between a weighting coefficient and the distance between the prediction pixel and the reference pixel, so that the intra-frame prediction performance is improved. The invention further provides a corresponding device while the bidirectional intra-frame directional prediction method is provided.

The correlation between a depth map and a texture map is used, classification of edge blocks and flat blocks is carried out on the depth map, a block motion matching criterion with texture gradient information added is adopted to obtain motion vectors of different macro blocks according to marks, motion vector post-processing and adaptive interpolation are carried out on the different macro blocks respectively, and a depth map interpolation frame and a texture map interpolation frame are obtained at the same time. Compared with the traditional frame rate up conversion method, the method of the invention enhances processing on edges of the depth map, the interpolated depth map has better edge features, and the interpolated texture map has better quality.

The invention provides an image processing method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: carrying out the calculation and statistics of the texture gradient of a to-be-processed image, and determining an intermediate-frequency texture region and a high-frequency texture region in the to-be-processed image; and enhancing the intermediate-frequency texture region and the high-frequency texture region in different enhancement modes to obtain a processed image. According to the method, intermediate-frequency textures and high-frequency textures are enhanced to different degrees, and the original intention of texture enhancement is better met, so that the intermediate-frequency textures are not lost by a relatively large quantization step size at a low bit rate as much as possible, and a prediction mode is stabilized by enhancing the textures; the high-frequency strong texture enhancement is weak, the excessive phenomenon after enhancement is reduced, and the subjective quality of the image can be improved.

The invention provides a total variational model based on saliency and a total variational model based on the total variational model and the total variational model based on saliency. 2- norm-optimized image fusion method and apparatus utilizes saliency weight coefficients based on frequency domain filtering method to express the contribution degree of source image to the fusion image in the datafidelity term, so that the fusion image can be adaptively fused with infrared salient information under the visible light background sensitive to human vision. At the same time, use 2-norm as a new regular term, the norm transfers the texture gradient information of the source image to the fusion image comprehensively, which overcomes the problems of low contrast and black artifact noise in the traditional fusion method to a certain extent, and shows superior fusion performance, which is more effective than the existing typical fusion technology.

System and method embodiments are provided for achieving improved View Synthesis Distortion (VSD) calculation and more accurate distortion estimation of encoded video frames. An embodiment method includes obtaining a depth map value for a video frame and determining a weighting factor for depth distortion in accordance with the depth map value. The weighting factor maps a pixel range of the depth map value to an output function having higher values for closer image objects and lower values for farther image objects. The VSD for the video frame is then calculated as a function of absolute horizontal texture gradients weighted by a depth distortion value and the weighting factor determined in accordance with the depth map value.

The invention discloses a preparation method of an anti-heat-scouring coating on the surface of a titanium alloy. The method adopts gas-phase deposition equipment to conducting multi-time depositing on the surface of the titanium alloy to coat different components, the coatings of different texture structures effectively improves the high-temperature anti-heat-seismic performance and the antioxidant properties of a substrate in the using process, and the problem of heat matching is solved for preventing the stress concentration at the interface of the titanium alloy. The preparation method comprises the steps that 1, an interface binding layer is deposited on the surface of the titanium alloy; 2, a component gradient coating is deposited on the surface of the interface binding layer; 3, the texture gradient coating is prepared on the surface of the component gradient coating; and 4, an anti-wear composite coating is prepared on the surface of the texture gradient coating. The preparation method has the advantages that a PVD coating technology is adopted, the preparation of the four coatings of the different texture composition gradients is achieved, the heat scouring of the targetmaterials of various materials can be effectively prevented, and the operation is simple.

The invention discloses a method and a device for realizing heavy mosaics. The method comprises the following steps of: calculating gradients of a unit where a pixel point needing green interpolation in a multi-unit CFA image is located in multiple directions, and calculating texture gradient matrixes of the unit and adjacent units; calculating a texture similarity coefficient according to the texture gradient matrixes of the unit and the adjacent unit, determining an interpolation direction according to the texture similarity coefficient and the gradient in each direction, and performing green component interpolation on the pixel point of the unit; respectively carrying out blue component interpolation and red component interpolation on the pixel points at the red and blue component positions according to the full-resolution green channel obtained by interpolation, and carrying out red and blue component interpolation on the pixel points at the green component position according to the blue and red channels obtained by interpolation; and combining all color channels to obtain a re-mosaic image. Therefore, according to the method, the algorithm complexity can be reduced, the hardware overhead can be reduced, hardware realization is facilitated, and the processing flow has real-time performance.

The invention relates to a video compression prediction method, which comprises the following steps of: dividing an image into a plurality of MBs with the same size, and selecting one MB as a currentMB; predicting the current MB through a prediction method based on pixel-level multi-component reference to obtain a first prediction residual error of the current MB; predicting the current MB through an adaptive texture gradient prediction method based on inflection point sampling to obtain a second prediction residual error of the current MB; and selecting a final prediction residual error of the current MB according to the first prediction residual error and the second prediction residual error. According to the method, the optimal prediction method is selected from a prediction method based on pixel-level multi-component reference and a prediction method based on inflection point sampling and adaptive texture gradient through a prediction selection algorithm, and the prediction effectof a complex texture image can be further optimized.

The invention discloses an endoscope weak texture image enhancement method and device, visual error perception can be removed, the number of extracted visual feature points is increased, and texture gradient information of the image is improved. The method comprises the following steps: (I) extracting endoscope image data in a clinical operation; (II) acquiring a highlight area in the single-frame endoscope image based on color channel intensity offset; (III) complementing the image area of the endoscope according to the highlight area of the endoscope; (IV) on the basis of the spatial symmetry of the image, carrying out spatial symmetry description on the weak texture region of the endoscope image and carrying out color gradient description on the weak texture region of the endoscope image on the basis of the color gradient of the image; (V) obtaining a weak texture index according to the weighted sum of the image pixel space symmetry and the color gradient, and quantifying the endoscope weak texture image data; and (VI) performing adaptive gradient preservation on the weak texture image based on the local linear relation.

The invention relates to a prediction method for video compression, and the method comprises the steps: dividing an image into a plurality of MBs with the same size, and selecting one MB as a currentMB; predicting the current MB through a prediction method based on pixel-level single-component reference to obtain a first prediction residual error of the current MB; predicting the current MB through an adaptive texture gradient prediction method based on non-distance sampling to obtain a second prediction residual error of the current MB; and selecting a final prediction residual error according to the first prediction residual error and the second prediction residual error. According to the method, the optimal prediction method is selected from the prediction method based on pixel-level single-component reference and the prediction method based on non-distance sampling adaptive texture gradient through a prediction selection algorithm, and the prediction effect of a complex texture image can be further optimized.