基于变分贝叶斯ICA的火山灰云检测研究  

Volcanic Ash Cloud Detection Based on Variational Bayesian ICA

作　　者：沈迪[1] 李成范[1] 赵俊娟[1] 尹京苑[1] 

机构地区：[1]上海大学计算机工程与科学学院,上海200444

出　　处：《红外技术》2014年第2期120-124,共5页Infrared Technology

基　　金：国家自然科学基金项目;编号:41172303

摘　　要：热红外遥感能够准确、快速地检测出火山灰云信息。针对热红外遥感数据和火山灰云检测特点,提出了基于变分贝叶斯ICA的火山灰云检测算法,通过引入贝叶斯网络的条件独立性准则和近似变分算法,将源信号后验概率分布的计算转化为更容易处理的负变自由能,去逼近真实后验概率分布的最佳近似值。实验表明该方法取得了85.25%的光谱匹配度,检测精度较高。The thermal infrared remote sensing can be used to accurately and quickly monitor the volcanic ash cloud information. Aiming at the characteristics of thermal infrared remote sensing data and volcanic ash cloud detection, this study proposes a volcanic ash cloud detection method on the basis of variational Bayesian ICA, which proves that with the addition of the independence standards and the variational approximate algorithm of Bayesian networks being put into the Bayesian framework, the computation of posterior probability distribution of source signal can be turned into negative free energy and approach the optimal approximation of real posterior probability distribution. The results indicate that the proposed method has a spectral match of 85.25%and high detection accuracy.

关 键 词：热红外遥感 火山灰云 MODIS图像 变分贝叶斯 独立分量分析 INDEPENDENT component analysis(ICA) 

分 类 号：TN219[电子电信—物理电子学]