Classified-Filter-based Post-Compensation Interpolation for Color Filter Array demosaicing

Jing-Ming Guo, Yun-Fu Liu, B. Lai, Peng-Hua Wang, Jiann-Der Lee
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引用次数: 2

Abstract

In this paper, a classified-based post-compensation algorithm for Color Filter Array (CFA) demosaicing is proposed. This technique can be used for improving the image quality of the interpolated results obtained by other CFA images. First, each pixel is classified according to its neighborhood texture variance and angle. Then, different Least-Mean-Square (LMS) filters are trained to adopt for dealing pixels of various characteristics. As documented in the experimental results, the proposed scheme can substantially boost the image quality; in addition, a better visual perceptual can be obtained. Notably, the proposed method can be considered as effective post-compensation by applying for any former schemes to yield an even better image quality.
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基于分类滤波器的彩色滤波器阵列去马赛克后补偿插值
提出了一种基于分类的彩色滤波阵列(CFA)去马赛克后补偿算法。该技术可用于提高其他CFA图像插值结果的图像质量。首先,根据邻域纹理方差和角度对每个像素进行分类。然后,训练不同的最小均方(LMS)滤波器来处理不同特征的像素。实验结果表明,该方案可以显著提高图像质量;此外,还可以获得较好的视觉感知。值得注意的是,该方法可以被认为是一种有效的后补偿方法,它可以应用于任何先前的方案,从而获得更好的图像质量。
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