红外与毫米波学报, 2001, 20 (3): 199, 网络出版: 2006-05-10
在小波域中进行图像噪声方差估计的EM方法
EM ALGORITHM FOR ESTIMATING THE NOISE DEVIATION OF THE IMAGE IN THE WAVELET DOMAIN
小波变换 混合高斯模型 期望最大似然函数算法(EM算法). wavelet transform gaussian mixture model Expectation-Maximization (EM).
摘要
提出一种估计图像噪声的方法,该方法用混合高斯概率密度模型拟合图像的小波系数中最高频率子带的直方图,用EM算法估计模型的参数,选取其中最小的标准方差作为图像噪声标准方差.用该方法能准确地估计图像高斯噪声的标准方差,尤其当图像的噪声比较弱时,该方法比传统方法更准确.
Abstract
A new method was proposed to estimate noisy image’s quality. This approach uses Gaussian mixture model to simulate the histogram of the highest subband’s coefficients in the wavelet domain. The parameters of this model can be calculated by EM algorithm. The smallest deviation of the Gaussian mixture model is selected as the noise deviation. The authors' proposed method can provide better result than the other traditional ones.
林哲民, 康学雷, 张立明. 在小波域中进行图像噪声方差估计的EM方法[J]. 红外与毫米波学报, 2001, 20(3): 199. 林哲民, 康学雷, 张立明. EM ALGORITHM FOR ESTIMATING THE NOISE DEVIATION OF THE IMAGE IN THE WAVELET DOMAIN[J]. Journal of Infrared and Millimeter Waves, 2001, 20(3): 199.