In order to investigate the restoration of low resolution images, the linear and nonlinear interpolation methods were applied for the interpolation of the com- mon information matrix obtained from a series of pictures...In order to investigate the restoration of low resolution images, the linear and nonlinear interpolation methods were applied for the interpolation of the com- mon information matrix obtained from a series of pictures, getting the restructuring matrix. The characteristic block with the best restoration effect was determined by analyzing the pixel difference of the common information of each image at the same position. Then the characteristic blocks and their original blocks were used to build and train neural network. Finally, images were restored by the neural network and the differences between pictures were reduced. Experimental results showed that this method could significantly improve the efficiency and precision of algorithm.展开更多
In this letter, an adaptive interpolation algorithm based on edge detection is proposed. With this algorithm, all the missing green values can be reconstructed in Bayer pattern image by using edge detection interpolat...In this letter, an adaptive interpolation algorithm based on edge detection is proposed. With this algorithm, all the missing green values can be reconstructed in Bayer pattern image by using edge detection interpolation method. Reconstructed images composed of green pixels are classified according to the high frequency components in image, and the threshold T needed for all kinds of green images in the edge detection is determined through experiments. The edge detection is carried out based on the one Dimensional (1D) gradient operator. If the gradient value is greater than T, this pixel is located on the edge; otherwise the pixel is in the smooth area of the image. Finally, the simple bilinear interpolation is used for the smooth area while the Laplacian interpolation with the second-order correction term is adopted to reconstruct the other red/blue values on the edge. This algorithm resolves effectively the conflicts between reconstructing high quality color image and reducing computational complexity, and thus largely enhances the processing speed for the reconstructed color image.展开更多
An efficient adaptive approximation demosaicking algorithm based on the sampled edge pattern was presented for mosaic images from Bayer color filter array. The proposed algorithm determined edge patterns by four neare...An efficient adaptive approximation demosaicking algorithm based on the sampled edge pattern was presented for mosaic images from Bayer color filter array. The proposed algorithm determined edge patterns by four nearest green values surrounding the green interpolation location. Then according to the edge patterns, different adaptive interpolation steps were applied. Simulations on 12 Kodak photos and 15 IMAX high-quality images showed that the proposed method outperformed the other four demosaicking methods (bilinear, effective color interpolation, Lu's method and Chen's method) for average color peak signal to noise ratios and maintained a relatively low complexity owing to constant color-difference interpolation step and a reasonable terminating condition of iteration.展开更多
The spectral representation method (SRM) is most widely used in simulating the stochastic field.The proper orthogonal decomposition (POD) based SRM is an important form.This paper investigates the approximate approach...The spectral representation method (SRM) is most widely used in simulating the stochastic field.The proper orthogonal decomposition (POD) based SRM is an important form.This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems,i.e.,the seismic ground motion and wind velocity fields simulations.Then,the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM).It is concluded that the CPSRM maintains a much higher accuracy than the PSRM.In the CPSRM,the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy;the linearly distributed interpolation nodes are effective in the ground motions simulation;however,the exponentially distributed interpolation nodes are effective in the wind velocity simulation.展开更多
An element decomposition method with variance strain stabilization(EDM-VSS) is proposed. In the present EDM-VSS, the quadrilateral element is first divided into four sub-triangular cells, and the local strains in sub-...An element decomposition method with variance strain stabilization(EDM-VSS) is proposed. In the present EDM-VSS, the quadrilateral element is first divided into four sub-triangular cells, and the local strains in sub-triangular cells are obtained using linear interpolation function. For each quadrilateral element, the strain of the whole quadrilateral is the weighted average value of the local strains, which means only one integration point is adopted to construct the stiffness matrix. The stabilization item of the stiffness matrix is constructed by variance of the local strains, which can eliminate the instability of the one-point integration formulation and largely increase the accuracy of the element. Compared with conventional full integration quadrilateral element, the EDM-VSS achieves more accurate results and expends much lower computational cost. More importantly, as no mapping or coordinate transformation is involved in the present EDM-VSS, the restriction on the conventional quadrilateral elements can be removed and problem domain can be discretized in more flexible ways. To verify the accuracy and stability of the present formulation, a number of numerical examples are studied to demonstrate the efficiency of the present EDM-VSS.展开更多
基金Supported by the Youth Fund for Science and Technology Research of Institution of Higher Education in Hebei Province in 2016(QN2016243)~~
文摘In order to investigate the restoration of low resolution images, the linear and nonlinear interpolation methods were applied for the interpolation of the com- mon information matrix obtained from a series of pictures, getting the restructuring matrix. The characteristic block with the best restoration effect was determined by analyzing the pixel difference of the common information of each image at the same position. Then the characteristic blocks and their original blocks were used to build and train neural network. Finally, images were restored by the neural network and the differences between pictures were reduced. Experimental results showed that this method could significantly improve the efficiency and precision of algorithm.
基金Supported by the Natural Science Foundation of Shanxi Province (No.20051019).
文摘In this letter, an adaptive interpolation algorithm based on edge detection is proposed. With this algorithm, all the missing green values can be reconstructed in Bayer pattern image by using edge detection interpolation method. Reconstructed images composed of green pixels are classified according to the high frequency components in image, and the threshold T needed for all kinds of green images in the edge detection is determined through experiments. The edge detection is carried out based on the one Dimensional (1D) gradient operator. If the gradient value is greater than T, this pixel is located on the edge; otherwise the pixel is in the smooth area of the image. Finally, the simple bilinear interpolation is used for the smooth area while the Laplacian interpolation with the second-order correction term is adopted to reconstruct the other red/blue values on the edge. This algorithm resolves effectively the conflicts between reconstructing high quality color image and reducing computational complexity, and thus largely enhances the processing speed for the reconstructed color image.
基金Supported by National Natural Science Foundation of China(No.60975001 and No.61271412)
文摘An efficient adaptive approximation demosaicking algorithm based on the sampled edge pattern was presented for mosaic images from Bayer color filter array. The proposed algorithm determined edge patterns by four nearest green values surrounding the green interpolation location. Then according to the edge patterns, different adaptive interpolation steps were applied. Simulations on 12 Kodak photos and 15 IMAX high-quality images showed that the proposed method outperformed the other four demosaicking methods (bilinear, effective color interpolation, Lu's method and Chen's method) for average color peak signal to noise ratios and maintained a relatively low complexity owing to constant color-difference interpolation step and a reasonable terminating condition of iteration.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51278382,90815020)the Chang Jiang Scholars Program and the Innovative Research Team Program of the Ministry of Education of China (Grant No. IRT1125)the "111" Project (Grant No.B13024)
文摘The spectral representation method (SRM) is most widely used in simulating the stochastic field.The proper orthogonal decomposition (POD) based SRM is an important form.This paper investigates the approximate approaches to the POD-based SRM in simulating two typical problems,i.e.,the seismic ground motion and wind velocity fields simulations.Then,the accuracy resulting from the power spectral density matrix-based POD method (PSRM) is compared to that of the coherency matrix-based POD method (CPSRM).It is concluded that the CPSRM maintains a much higher accuracy than the PSRM.In the CPSRM,the linear interpolation of eigenvectors and third-order polynomial interpolation of eigenvalues can be accepted to attain high accuracy;the linearly distributed interpolation nodes are effective in the ground motions simulation;however,the exponentially distributed interpolation nodes are effective in the wind velocity simulation.
基金supported by the National Natural Science Foundation of China(Grant Nos.11472101 and 61232014)Postdoctoral Science Foundation of China(Grant No.2013M531780)the National Laboratory for Electric Vehicles Foundations
文摘An element decomposition method with variance strain stabilization(EDM-VSS) is proposed. In the present EDM-VSS, the quadrilateral element is first divided into four sub-triangular cells, and the local strains in sub-triangular cells are obtained using linear interpolation function. For each quadrilateral element, the strain of the whole quadrilateral is the weighted average value of the local strains, which means only one integration point is adopted to construct the stiffness matrix. The stabilization item of the stiffness matrix is constructed by variance of the local strains, which can eliminate the instability of the one-point integration formulation and largely increase the accuracy of the element. Compared with conventional full integration quadrilateral element, the EDM-VSS achieves more accurate results and expends much lower computational cost. More importantly, as no mapping or coordinate transformation is involved in the present EDM-VSS, the restriction on the conventional quadrilateral elements can be removed and problem domain can be discretized in more flexible ways. To verify the accuracy and stability of the present formulation, a number of numerical examples are studied to demonstrate the efficiency of the present EDM-VSS.