摘要
本文提出了一种新的滤波器———模糊检测加权均值 (FDWM)滤波器 .根据被污染图像的直方图的特点 ,利用它所反映的图像统计特性 ,建立模糊隶属函数 ,改进算法设计 ,并结合新的检测算法进行噪声消除 .对于盐椒噪声图像 ,当噪声率超过 30 %时 ,FDWM的去噪效果远远优于常规方法 ,特别是当噪声率超过 5 0 %时 ,FDWM的优越性更加突出 ,无论其主观视觉效果还是其峰值信噪比或均方误差都表明了这一点 .
A new filter—Fuzzy Detection Weighted Mean filter is presented in this paper.Based on the histogram of corrupted image and its statistic characteristic,we construct the fuzzy membership functions and present the design methodology of FDWM combining new detection algorithm.For salt pepper impulse noise image,when the noise probability exceeds 30%,FDWM gives superior performance compared with conventional filters,especially when noise probability is more than 50%,the advantage of FDWM is more prominent than other filters.This is showed by the subjective vision and peak signal to noise rate (PSNR) or mean square error (MSE).
出处
《电子学报》
EI
CAS
CSCD
北大核心
2000年第10期31-35,共5页
Acta Electronica Sinica
基金
国家自然科学基金!(No.69772 0 2 6)
广东省自然科学基金!(No .970 4 84)
关键词
模糊检测加权均值
模糊技术
图像处理
虑波器
fuzzy detection weighted mean
fuzzy technique
histogram
membership function
impulse noise
image processing
