智能系统学报Issue(1)：62-67,6.DOI:10.3969/j.issn.1673-4785.201403066
一种基于二维 GARCH 模型的图像去噪方法
A method of image deno ising based on two-dimension al GARCH model
摘要
Abstract
An image denoising method based on the statistical model for wavelet coefficients is proposed .It uses a two-dimensional Generalized Autoregressive Conditional Heteroscedasticity (2D-GARCH) model for modeling the wavelet coefficients .A novel wavelet coefficients model is also used to make better use of the important characteris -tics of wavelet coefficients such as "sharp peak and heavy tailed"marginal distribution and the dependencies be-tween the coefficients .It utilizes maximum likelihood estimation based on fruit fly optimization algorithm ( ML Esti-mation based on FOA) to estimate the model parameters instead of using traditional linear programming in order to improve the accuracy of the modeling .The minimum mean square error estimation ( MMSE Estimation ) is applied to estimating the parameters of the wavelet coefficients of the original image that is not affected by noise .Experimental results showed that compared to the present widely-used denoising methods the proposed method is more effective in image denoising , and it may achieve higher peak signal-to-noise ratio ( PSNR) and good visuality .关键词
小波变换/统计建模/二维GARCH模型/果蝇优化算法/图像去噪Key words
wavelet transform/statistical modeling/two-dimensional GARCH model/FOA/image denoising分类
信息技术与安全科学引用本文复制引用
李俊泽,袁小芳,张振军,王耀南,王国锋..一种基于二维 GARCH 模型的图像去噪方法[J].智能系统学报,2015,(1):62-67,6.基金项目
国家“863”计划资助项目（2012AA112312）． （）
