基于边缘检测的噪声滤波
A Filtering Method for Images Based on Edge Detection

作者: 费赓柢 , 李岳阳 , 孙 俊 :江南大学轻工过程先进控制教育部重点实验室,无锡;

关键词: 图像滤波边缘检测器神经模糊推理系统脉冲噪声Image Filtering Edge Detector Neuro-Fuzzy Inference System Impulse Noise

摘要:
对于被椒盐脉冲噪声污染的灰度图像,提出了一种新的图像滤波方法。新滤波方法将中值滤波器,边缘检测器和一个自适应神经模糊推理系统(ANFIS)相结合。在所提出的滤波方法中,首先对该系统进行优化训练,确定其参数,然后用优化后的系统对被椒盐脉冲噪声污染的图像进行噪声滤波。实验结果表明,与传统滤波方法相比,新滤波方法能有效地去除图像中椒盐脉冲噪声,并且更能够保留原有图像中的边缘和细节等信息

Abstract:
As to the gray scales images corrupted by impulse noise, a new noise filtering method is presented. The proposed filter is constructed by combining a median filter, an edge detector, and an adaptive neuro-fuzzy inference system (ANFIS). The proposed noise filter consists of two modes of operation, namely, training and testing (filtering). As demonstrated by the experimental results, the proposed filter not only has the ability of noise attenuation but also possesses desirable capability of details preservation. It significantly outperforms other conventional filters.

文章引用: 费赓柢 , 李岳阳 , 孙 俊 (2014) 基于边缘检测的噪声滤波。 图像与信号处理, 3, 39-51. doi: 10.12677/JISP.2014.32007

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