California Micro Devices(CMD)的Praetorian专用集成无源(ASIP)电磁抗干扰滤波器阵列新增两款器件CM1418和CM1419。这些滤波器具有静电(ESD)保护功能。可用于手机等产品。CM1419是一种基于电感的EMI滤波器阵列,它集成了两个Pi...California Micro Devices(CMD)的Praetorian专用集成无源(ASIP)电磁抗干扰滤波器阵列新增两款器件CM1418和CM1419。这些滤波器具有静电(ESD)保护功能。可用于手机等产品。CM1419是一种基于电感的EMI滤波器阵列,它集成了两个Pi滤波器(C-L-C)。每个通道的元件值为117pF/3nH/117pF。与滤波器端口相连的ESD二极管可承受峰值达4-30kV的ESD,已经超过IEC61000-4-2国际标准的要求。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
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.