关键词: 自适应神经网络模糊推理系统,综合滤波器,噪声图像,噪声点,图像重建 中图法分类号TP391文献标识码A

Abstract: A new impulse noise detector based on an adaptive neuro-fuzzy inference system(ANFIS) was presented．The proposed operator is a hybrid filter obtained by appropriately combining a median filtering,a Wiener filtering and the ANFIS．The noise is exactly estimated through the proposed operator．The internal parameters of the ANFIS are adaptively optimized by training．The training is easily accomplished by using simple artificial images that can be generated in a computer．The noise image,noise estimation of median filtering and noise estimation of Wiener filter are as three inputs of adaptive neural fuzzy system．The output of the adaptive neural fuzzy system is judged whether the pixel is a noise point by means of a fixed threshold value．If it is a noise point,the median filter is used．If it is a real image point,remain unchanged．The distinctive feature of the proposed operator is that it offers well line,edge,detail and texture preservation performance while,at the same time,effectively removing noise from the input image．Simulation experiments show that the proposed operator may be used for efficient restoration of digital images corrupted by impulse noise without distorting the useful information in the image.

Key words: ANFIS,Hybrid filter,Noise image,Noise point,Reconstruction of image