摘要
针对图像中的高斯白噪声,提出了一种利用像素邻域信息进行噪声方差估计的方法。基于图像邻域像素存在一定的相关性,给出一种图像分块区域"块内邻域相关度"的计算方法,并通过块的"块内邻域相关度"寻找图像的平滑区域,然后用选取的平滑区域加权平均估计整个图像的噪声方差。实验数据表明"块内邻域相关度"的方法能够有效地估计图像噪声。
This paper uses neighborhood information of image pixels to estimate noise variance in a Gaussian white noise image. As there is a certain correlation among neighborhood pixels, it defines an algorithm about block neighborhood relevance in a blocking image. Using the neighborhood relevance it can select the smoothing regions in an image and estimate noise variance with the selecting smoothing regions. Experimental data presents that it is an effective method to estimate image noise.
出处
《计算机与现代化》
2009年第12期82-84,88,共4页
Computer and Modernization
基金
浙江省科技厅重点工业项目(2007c21014)
关键词
图像处理
块内邻域相关度
图像噪声估计
噪声方差估计
image processing
block neighborhood relevance
image noise estimation
noise variance estimation
