摘要
图像中噪声的消除是图像处理与识别的重要环节,噪声滤除效果的好坏直接影响着后续图像处理与识别的质量.为此,提出一种用于图像降噪的空间域滤波算法,自适应均值滤波算法(Adaptive Averaging Filtering Algorithm,AAFA).该算法中局部窗口的系数(掩模系数)是根据局部窗口内各像素与中心像素间的灰度和空间关系计算的,即局部窗口中心像素灰度均值的计算既考虑了窗口内各像素与中心像素间的灰度值差异,又顾及了窗口内各像素与中心像素间的距离.利用该算法进行图像降噪的实验结果表明,相对于经典的空间域均值滤波算法和其它的均值滤波算法,该算法的噪声滤除效果更好.
Image denoising is one of the important steps in image processing and recognition,and directly determines the quality of image processing and recognition.This paper proposed a spatial domian filtering algorithm for image denoising,adaptive averaging filtering algorithm-AAFA.In AAFA,the coefficients of local window（mask coefficients） are calculated according to the gray-scale and spatial relationship between the central pixel and the other neighboring pixels in the current local window,i.e.,computation of gray-scale averaging value of central pixel in local window considers both gray value difference and spatial distance between the central pixel and the other neighboring pixels in current local window.Experimental results show that the proposed algorithm has better denoising performance than conventional spatial domain mean filtering algorithm and other averaging filtering algorithm.
出处
《小型微型计算机系统》
CSCD
北大核心
2011年第12期2495-2498,共4页
Journal of Chinese Computer Systems
基金
中国博士后科学基金项目(20090451167)资助
江苏博士后科学基金项目(0901077C)资助
关键词
图像降噪
均值
窗口
系数
image denoising
averaging value
window
coefficient
