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基于彩色滤波阵列(CFA)的图像传感器在每个像素位置获得三原色红(R)、绿(G)和蓝(B)中的一种分量,其缺失分量需要根据周围像素插值得到。目前提出的许多种插值算法,绝大部分采用Bayer排列模式。本文在色差恒定假设基础上,提出一种基于双边滤波器的自适应Bayer模型插值算法,对G通道的估计采用自适应滤波器进行插值,对R和B通道的插值采用双边滤波器。算法利用待插值像素与不同距离像素相关性不同的思想,根据图像边缘自适应设定滤波模板,能较准确估计G、B和R、G通道之间的色差值。实验结果表明,对比多尺度色差梯度算法和边缘强度滤波等算法,插值后的图像不仅主观视觉,且客观评价指标(彩色峰值信噪比,CPSNR)均优于这些算法。
A color filter array (CFA) -based image sensor obtains one of the three primary colors of red (R), green (G) and blue (B) at each pixel location, and its missing component needs to be interpolated from the surrounding pixels. Many kinds of interpolation algorithms proposed at present adopt the Bayer arrangement mode for the most part. Based on the constant assumption of color difference, this paper proposes an adaptive Bayer model interpolation algorithm based on bilateral filter. The adaptive filter is used to interpolate the G channel and the bilateral filter is used to interpolate the R and B channels. The algorithm uses the different correlativity between pixels to be interpolated and pixels at different distances, and adaptively sets the filtering template according to the edge of the image to accurately estimate the color difference between G, B, R and G channels. The experimental results show that the interpolated image is not only subjective, but also objectively evaluated (color peak signal-to-noise ratio, CPSNR) are superior to these algorithms by contrasting algorithms such as multi-scale color difference gradient algorithm and edge intensity filtering.