Classic non-local means (CNLM) algorithm uses the inherent self-similarity in images for noise removal. The denoised pixel value is estimated through the weighted average of all the pixels in its non-local neighborhoo...Classic non-local means (CNLM) algorithm uses the inherent self-similarity in images for noise removal. The denoised pixel value is estimated through the weighted average of all the pixels in its non-local neighborhood. In the CNLM algorithm, the differences between the pixel value and the distance of the pixel to the center are both taken into consideration to calculate the weighting coefficients. However, the Gaussian kernel cannot reflect the information of edge and structure due to its isotropy, and it has poor performance in flat regions. In this paper, an improved non-local means algorithm based on local edge direction is presented for image denoising. In edge and structure regions, the steering kernel regression (SKR) coefficients are used to calculate the weights, and in flat regions the average kernel is used. Experiments show that the proposed algorithm can effectively protect edge and structure while removing noises better when compared with the CNLM algorithm.展开更多
The effect of the particle size of coal dust on explosion pressure and the rising rate of explosion pressure is studied. Three coal dusts from Lingan Coal Mine in Canada and Datong Coal Mine in China are selected to t...The effect of the particle size of coal dust on explosion pressure and the rising rate of explosion pressure is studied. Three coal dusts from Lingan Coal Mine in Canada and Datong Coal Mine in China are selected to test. The influence of particle size on the maximum explosion pressure P max and maximum pressure rising rate (d p /d t ) max of each coal dust was tested experimentally. The results indicate that with the decrease of particle size of coal dusts, explosion pressure increases on condition of the same concentration. If the concentration of coal dust is different, the maximum explosion pressure appears at the concentration of 500 g/m^3. The smaller the particle size of coal dusts, the larger the rising rate of explosion pressure of coal dust. When the concentration of coal dust is 500 g/m^3, the rising rate of explosion pressure of each coal dust is the maximum.展开更多
基金National Key Research and Development Program of China(No.2016YFC0101601)Fund for Shanxi“1331 Project”Key Innovative Research Team+1 种基金Shanxi Province Science Foundation for Youths(No.201601D021080)Universities Science and Technology Innovation Project of Shanxi Province(No.2017107)
文摘Classic non-local means (CNLM) algorithm uses the inherent self-similarity in images for noise removal. The denoised pixel value is estimated through the weighted average of all the pixels in its non-local neighborhood. In the CNLM algorithm, the differences between the pixel value and the distance of the pixel to the center are both taken into consideration to calculate the weighting coefficients. However, the Gaussian kernel cannot reflect the information of edge and structure due to its isotropy, and it has poor performance in flat regions. In this paper, an improved non-local means algorithm based on local edge direction is presented for image denoising. In edge and structure regions, the steering kernel regression (SKR) coefficients are used to calculate the weights, and in flat regions the average kernel is used. Experiments show that the proposed algorithm can effectively protect edge and structure while removing noises better when compared with the CNLM algorithm.
基金National Natural Science Foundation of China(No.11802272)Special Foundation for Platform Base and Outstanding Talent of Shanxi Province(No.201705D211002)Major Research and Development Project of Shanxi Province(No.201603D121012)
文摘The effect of the particle size of coal dust on explosion pressure and the rising rate of explosion pressure is studied. Three coal dusts from Lingan Coal Mine in Canada and Datong Coal Mine in China are selected to test. The influence of particle size on the maximum explosion pressure P max and maximum pressure rising rate (d p /d t ) max of each coal dust was tested experimentally. The results indicate that with the decrease of particle size of coal dusts, explosion pressure increases on condition of the same concentration. If the concentration of coal dust is different, the maximum explosion pressure appears at the concentration of 500 g/m^3. The smaller the particle size of coal dusts, the larger the rising rate of explosion pressure of coal dust. When the concentration of coal dust is 500 g/m^3, the rising rate of explosion pressure of each coal dust is the maximum.