电子学报2011，Vol.39Issue(7)：1563-1568,6.
基于正态逆高斯模型的非下采样Contourlet变换图像去噪
Using Normal Inverse Gaussian Model for Image Denoising in NSCT Domain
摘要
Abstract
A novel non-subsampled Contourlet transform denoising scheme based on the normal inverse Gaussian prior (NIG) and Bayesian estimation has been proposed. Normal inverse Gaussian model is used to describe the distributions of the image coefficients of each subband in non-subsampled Contourlet transform domain, corresponding threshold function is derived from the model using Bayesian maximum a posteriori probability estimation theory. This scheme achieves enhanced estimation results for images that are corrupted with additive Gaussian noise over a wide range of noise variance.The simulation results indicate that the proposed method can remove Gaussian white noise effectively, improve the peak signal-to-noise ratio of the image, and keep better visual result in edges information reservation as well.关键词
去噪/非下采样Contourlet变换/正态逆高斯模型/Bayesian估计Key words
denoising/non-subsampled Contourlet transform/normal inverse Gaussian model/Bayesian estimation分类
信息技术与安全科学引用本文复制引用
贾建,陈莉..基于正态逆高斯模型的非下采样Contourlet变换图像去噪[J].电子学报,2011,39(7):1563-1568,6.基金项目
基金项目:国家自然科学基金(No.60703117,No.60703109,No.61075050,No.11071281) （No.60703117,No.60703109,No.61075050,No.11071281）
陕西省教育厅自然科学基金(No.2010JK865) （No.2010JK865）
西北大学科学研究基金(No.NC0921) （No.NC0921）
