Impulse Noise Filter Based on Fuzzy Neural Network
基于模糊神经网络的脉冲噪声滤波器

A new filter based on a Fuzzy Neural Network(FNN) of Sugeno type is presented for images corrupted by impulse noise.Impulse noise results in the quality decline of image and can be reduced by nonlinear image filters, such as FNN image filter. FNN image filter does better than other kind fo filters when judged of subjective vision quality because its way of working is even close to that of mankind's eyes. The network structure of filter is good at ditecting different patterns of noisy pixel while the fuzzy mechanism embedded in the network can remove impulse and keep details and textures. Sugeno type NN have simple structure and other merit, which makes it suit for constructing FNN filter. A learning method based on the genetic algorithm is adopted to adjust the network parameters from a set of training data. The preliminary experimental result shows that the Fuzzy Neural Network filter performs better than the Median Filter when used to cancel impulse noise from scene image.