模糊加权均值滤波器

Fuzzy Weighted Average Filter

主要研究了受混合噪声污染图象的降噪滤波问题，运用模糊数学思想提出了一种基于模糊隶属度的加权均值滤波器．该算法利用模糊隶属度函数的概念，对均值滤波器的权值加以优化，使其不仅在降低高斯噪声的能力方面较均值滤波有所提高，而且对于脉冲噪声及混合噪声也有很好的抑制能力．

This paper mainly studied the problem of the noise suppression for images corrupted by different kinds of noises. A weighted average filter based on the fuzzy theory is presented. The algorithm first looks on the pixels in the filter window as elements of a fuzzy set, and then optimizes the membership of each element of the fuzzy set by iteration ways. In the end, the filter gets its weights of the pixels in the window from the memberships of the fuzzy set. Computer simulations show that the presented filter is not only better than average filter in the field of suppression of Gaussian noise, but also good at the suppression of impulse noise. So it has good performance to image corrupted by mixture noise.