信阳师范学院学报（自然科学版）Issue(4)：587-591,5.DOI:10.3969/j.issn.1003-0972.2013.04.031
基于广义高斯模型的局部自适应遥感图像去噪研究
Locally Adaptive Image Denoising of Remote Sensing Image Based on Generalized Gaussian distribution
摘要
Abstract
Based on exploiting the correlations among the image wavelet decomposition coefficients in a sub -band, an adaptive statistical model for wavelet image coefficients was presented and applied to the image denoising of Remote Sensing Image .Each wavelet coefficient was firstly modeled as a random variable of a generalized Gaussian distribution ( GGD) ,then,based on the algorithm of the wavelet soft threshold denoising and according to the characteristics of spa -tial clustering of wavelet decomposition coefficients , a new local adaptive algorithm was proposed and applied to restore the noisy images by estimating the coefficients with maximum a posteriori probability rule ( MAP) .The algorithm was applied to denoise the noisy Remote Sensing Image of Maoergai area in the upper Minjiang where contains typical vege -tation and soil .Simulation results showed that the higher peak-signal to noise ratio and the better visual effects were ob-tained as compared to other image denoising methods .关键词
小波分析/自适应阈值/贝叶斯框架/广义高斯分布/图像去噪Key words
wavelet transform/adaptive threshold/Bayesian framework/GGD/image denoising分类
信息技术与安全科学引用本文复制引用
秦振涛,杨武年..基于广义高斯模型的局部自适应遥感图像去噪研究[J].信阳师范学院学报（自然科学版）,2013,(4):587-591,5.基金项目
国家自然科学基金项目（41071265）；高等学校博士学科点专项科研基金项目 （）
