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Color interpolation algorithm of CCD based on green components and signal correlation

机译:基于绿色分量和信号相关性的CCD彩色插值算法

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Signal CCD/CMOS sensors capture image information by covering the sensor surface with a color filter array(CFA). For each pixel, only one of three primary colors(red, green and blue) can pass through the color filter array(CFA). The other two missing color components are estimated by the values of the surrounding pixels. In Bayer array, the green components are half of the total pixels, but both red pixel and blue pixel components are quarter, so green components contain more information, which can be reference to color interpolation of red components and blue components. Based on this principle, in this paper, a simple and effective color interpolation algorithm based on green components and signal correlation for Bayer pattern images was proposed. The first step is to interpolate R, G and B components using the method-bilinear interpolation. The second step is to revise the results of bilinear interpolation by adding some green components on the results of bilinear interpolation. The calculation of the values to be added should consider the influence of correlation between the three channels. There are two major contributions in the paper. The first one is to demosaick G component more precisely. The second one is the spectral-spatial correlations between the three color channels is taken into consideration. At last, through MATLAB simulation experiments, experimental pictures and quantitative data for performance evaluation-Peak Signal to Noise Ratio(PSNR) were gotten. The results of simulation experiments show, compared with other color interpolation algorithms, the proposed algorithm performs well in both visual perception and PSNR measurement. And the proposed algorithm does not increase the complexity of calculation but ensures the real-time of system. Theory and experiments show the method is reasonable and has important engineering significance.
机译:信号CCD / CMOS传感器通过用彩色滤光片阵列(CFA)覆盖传感器表面来捕获图像信息。对于每个像素,只有三种原色(红色,绿色和蓝色)中的一种可以通过滤色镜阵列(CFA)。其他两个缺失的颜色分量由周围像素的值估算。在拜耳阵列中,绿色分量占总像素的一半,但是红色像素分量和蓝色像素分量均为四分之一,因此绿色分量包含更多信息,可以参考红色分量和蓝色分量的颜色插值。基于此原理,本文提出了一种基于绿色分量和信号相关性的拜耳图案图像简单有效的颜色插值算法。第一步是使用双线性插值方法对R,G和B分量进行插值。第二步是通过在双线性插值结果上添加一些绿色成分来修改双线性插值结果。计算要相加的值时应考虑三个通道之间相关性的影响。本文有两个主要贡献。第一个是更精确地去马赛克G分量。第二个是考虑了三个颜色通道之间的光谱空间相关性。最后,通过MATLAB仿真实验,获得了用于性能评估的实验图片和定量数据-峰值信噪比(PSNR)。仿真实验结果表明,与其他颜色插值算法相比,该算法在视觉感知和PSNR测量方面表现良好。所提算法不会增加计算的复杂度,但可以保证系统的实时性。理论和实验表明,该方法是合理的,具有重要的工程意义。

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