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Improved method for blind estimation of the variance of mixed noise using weighted LMS line fitting algorithm

机译:加权LMS线拟合算法盲估计混合噪声方差的改进方法。

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The paper addresses blind evaluation of the parameters of mixed noise in images. The conventional approach is based on line fitting in the scatter-plot of local variance estimates using LMS algorithm. This does not utilize the fact that the points in the scatter pot typically appear in clusters that depend on the image. It is shown that the use of weighted LMS algorithm that takes into account the number of points in clusters provides considerable improvement in the accuracy of line fitting and, thus, better estimation of the parameters of mixed noise.
机译:本文讨论了图像中混合噪声参数的盲目评估。常规方法基于使用LMS算法在局部方差估计的散点图中的线拟合。这没有利用以下事实:分散罐中的点通常出现在依赖于图像的群集中。结果表明,使用加权LMS算法(考虑了群集中的点数)可以显着提高线拟合的准确性,从而更好地估计混合噪声的参数。

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