基于极大似然法的椒盐噪声滤波算法

A New Salt and Pepper Noise Filter Algorithm based on the Maximum Likehood Method

本文提出了一种新的基于极大似然法的椒盐噪声滤波算法。在传统BP算法中引入了极大似然估计,在训练样本时能够在考虑网络逼近行为的同时对噪声分布进行估计。而且针对椒盐噪声模型构造了新的鲁棒误差函数,从而使算法本身的抗干扰性增强。实验结果表明了该算法与传统BP算法相比具有更好的滤波性能。

One kind of new salt and pepper noise filter algorithm based on the maximum likehood method was proposed in this article. The maximum likelihood was introduced into the traditional BP algorithm for the sake of estimating the noise distribution during the network approaching of the training sample.And in order to enhance algorithm BP＇ s Anti-noise property,a new robust error function was accordingly defined in view of the salt ＆ pepper noise.The experimental results indicated our approach has the better filter performance compares with the traditional BP algorithm.