山东农业大学学报（自然科学版）2012，Vol.43Issue(1)：90-94,5.
一种Contourlet域高斯混合模型降噪方法
IMAGE DE-NOISING ALGORITHM USING GAUSSIAN MIXTURE MODEL BASED ON CONTOURLET TRANSFORM
褚衍彪1
作者信息
- 1. 中国矿业大学理学院,江苏徐州221116;枣庄学院数学与统计学院,山东枣庄277160
- 折叠
摘要
Abstract
A new method for image de -noising using Gaussian mixture model based on Contourlet transform and translation invariance was presented. A pixel - adaptive Gaussian mixture model was proposed in which each coefficient was a mixture of two normal distributions with the same zero mean value and different variance. Contour-let coefficients were classified into two categories using local Bayesian threshold, and the model parameters such as large and small variances, related probabilities, could be estimated from the information of the two classified coefficients in a neighboring window. The experimental results indicate that the method can get better visual effect and PSNR value compared with the methods like wavelet and contourlet image denoising using the translation invariance.关键词
Contourlet变换/图像去噪/高斯混合模型/平移不变Key words
Contourlet transform/image denoise/gaussian mixture model/Translation invariance分类
信息技术与安全科学引用本文复制引用
褚衍彪..一种Contourlet域高斯混合模型降噪方法[J].山东农业大学学报（自然科学版）,2012,43(1):90-94,5.
