一种脉冲噪声模糊检测和滤波算法

脉冲噪声滤波一直是图像处理研究热点。提出一种适合各种脉冲噪声,基于模糊检测和滤波新算法。这种非线性滤波算法由脉冲噪声检测和脉冲噪声滤波两部分组成,能够很好的保留原图像的轮廓清晰度。基于梯度模糊度的观点,我们构造了一个用隶属函数描述的脉冲噪声模糊集。将隶属函数用于滤波,实质是对邻像素的模糊度加权平均。实验结果显示:无论图像中含脉冲噪声多少,该算法都能快速、高效检测去除脉冲噪声算法。

A fuzzy impulse noise detection and reduction algorithm

Removing or reducing impulse noise is a very active research area in image processing.In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: fuzzy impulse noise detection and reduction method.This nonlinear filtering technique contains two steps: an impulse noise detection step and a reduction step that preserves edge sharpness.Based on the concept of fuzzy gradient values,our detection method constructs a fuzzy set impulse noise.This fuzzy set is represented by a membership function that will be used by the filtering method,which is a fuzzy averaging of neighboring pixels.Experimental results show that it is not only very fast,but also very effective for reducing little as well as very high impulse noise.