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Fuzzy weighted average filtering for mixture noises

机译:混合噪声的模糊加权平均滤波

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摘要

The classic nonlinear filter performs well in impulse noise suppression and edge preserving. However, the classic nonlinear filtering is not good at reducing the mixture of Gaussian noise and impulse noise. In this paper, we investigate the nonlinear filtering techniques to eliminate the mixture of impulse noise and Gaussian noise. Based on fuzzy theory, we present a weighted average filter by making use of the fuzzy membership functions to optimize the weights of the filter. Computational results, which have been obtained from experiments for noise attenuation, indicate that the new algorithm is promising.
机译:经典的非线性滤波器在脉冲噪声抑制和边缘保持方面表现出色。但是,经典的非线性滤波并不能很好地减少高斯噪声和脉冲噪声的混合。在本文中,我们研究了非线性滤波技术,以消除脉冲噪声和高斯噪声的混合。基于模糊理论,我们提出了一种加权平均滤波器,利用模糊隶属函数来优化滤波器的权重。从噪声衰减实验获得的计算结果表明,该新算法很有希望。

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