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Estimation of Image Noise Using Polynomial Masks

机译:使用多项式掩模估计图像噪声

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摘要

Many computer vision and image processing algorithms rely on the knowledge of the image noise variance as their input parameter. However, in practice, the distinction between noise and image features is not easy to draw. In this paper, image noise variance is estimated by a novel method employing rigorously derived polynomial masks. The method is based on the assumption that the image can be locally represented as a polynomial of the given degree and constitutes a generalization of some of previously proposed approaches.
机译:许多计算机视觉和图像处理算法都依赖于图像噪声方差的知识作为输入参数。但是,实际上,噪声和图像特征之间的区别并不容易得出。在本文中,通过采用严格导出的多项式掩码的新方法来估计图像噪声方差。该方法基于这样的假设:图像可以局部表示为给定次数的多项式,并且构成了一些先前提出的方法的概括。

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