双迭代等距均值滤波的医学图像恢复北大核心CSCD

医学图像中往往有很多与脉冲噪声灰度相同的像素,因此含脉冲噪声的医学图像的恢复非常困难。为了获得比现有的脉冲噪声滤波器更好的噪声抑制和纹理结构保持效果,提出了一种双迭代等距均值滤波(dual iterative equidistant mean filter,DIEMF)的医学图像恢复方法。该方法采用等距离邻域进行噪声检测和去除;噪声检测器循环地利用邻域的非最值像素与中心像素之间的平均绝对差,以及利用多数原则,将噪声像素与无噪像素区分开来;噪声去除采用自适应和双迭代的方法,以等距邻域中无噪像素和先前恢复像素的平均值作为中心噪声像素的灰度估计值,充分利用最近的先前恢复的像素。实验结果表明,该方法在噪声抑制和纹理结构保持方面优于现有的方法,特别是对于低密度噪声,它比现有的滤波器具有显著的优越性。

Medical image restoration by a dual iterative equidistant mean filter

Medical image is often rich in pixels with the same intensity as the i mpulse noise so that medical image restoration in the presence of impulse noise is remarkably difficult.To gain a better capability of impulse noise reduction and structure preservation for medical image than the state-of-the- art filters in literatures,we propose a dual iterative equidistant mean filter (DIEMF) for medical image restoration.In the proposed method,an equidistant neighborhood is proposed for noise detection and removal processing;the noise detector discrimi nates noisy pixel from noise free ones by the averaged absolute difference between the neighboring non-extreme pixels and central pixel circularly,as well as majority rule;the noise removal technique uses adaptive and dual iterative method,takes the mean of noise free pixels and previous restored pixels in equidistant neighborhood as the estimated intensity of central noisy pixel,taking full advantage of the nearest previous restored pixels.Experimental results shown th at the proposed method outperforms the state-of-the-art methods in noise reduction and structure preservation,espec ially for low noise level,it shows remarkable superiority over the state-of-th e-art filters.