摘要
提出了一种改进的自适应中值滤波算法,以有效地去除图像中的脉冲噪声,并保留图像细节。在进行噪声点检测时,引入了最小集合距离测度,有效地避免了将高频细节信号误判为噪声。采用最小无污染点集合的中值恢复噪声点,消除了其邻域噪声点的影响。通过与RAMF、NASMF等方法的比较实验表明,新算法噪声检测的正确率高、降噪与保留细节效果好,尤其对含噪声密度高的图像的处理效果优势更为明显。
An improved adaptive median filter is proposed to restore images corrupted by impulse noise. There are mainly three improved points in this algorithm. First, the image pixels are classified into signal pixels and noise pixels according to the decision criterion. Second, a measure, denoted as minimum set distance, is introduced to avoid misclassification of high frequency signal as noise,＂ Third, the median of minimum uncorrupted pixel set is used to restore noise pixel, in order to eliminate its neighborhood noise impact. The results of comparison experiments with RAMF and NASMF demonstrate that the proposed method can detect noise with high accuracy, remove noise efficiently while retaining image details, especially to images with high noise density.
出处
《计算机应用》
CSCD
北大核心
2008年第7期1732-1734,共3页
journal of Computer Applications
基金
国家自然科学基金资助项目(60772133)
陕西省自然科学基金资助项目(2007F22)
关键词
噪声检测
中值滤波
自适应
图像增强
noise detection
median filtering
adaptive
image enhancement
作者简介
卫保国（1970-），陕西乾县人，副教授，博士，主要研究方向：图像处理、模式识别。（wbg@nwpu．edu．cn）
