改进型ICA和SVM相结合的火山灰云遥感检测  

Remote Sensing Detection of Volcanic Ash Cloud Using Improved Independent Component Analysis and Support Vector Machine Algorithm

作　　者：刘岚[1] 雷咏梅[1] 尹京苑[1,2] 李成范[1] 赵俊娟[1] 

机构地区：[1]上海大学计算机工程与科学学院,上海200444 [2]上海市地震局,上海200062

出　　处：《电讯技术》2016年第1期88-92,共5页Telecommunication Engineering

基　　金：国家自然科学基金资助项目(41404024);上海市科技发展基金资助项目(14231202600);上海高校青年教师培养资助计划项目(2014-2016)~~

摘　　要：针对独立分量分析(ICA)模型在火山灰云遥感检测中的不足,提出了一种改进型ICA即变分贝叶斯ICA(VBICA)和支持向量机(SVM)相结合的火山灰云遥感检测算法,实现了火山灰云信息的近似分离。实验结果表明,所提算法能够从中分辨率成像光谱仪(MODIS)遥感图像中检测出火山灰云目标信息,且总检测精度和Kappa系数分别达到了88.4%和0.801 1,取得了较好的检测效果。For the deficiencies of Independent Component Analysis( ICA) model in volcanic ash cloud remote sensing detection,a remote sensing detection algorithm is proposed based on improved ICA( namely Variational Bayesian ICA,VBICA) and Support Vector Machine( SVM) to realize the approximate separation of volcanic ash cloud information. Test results show that the proposed method can detect the volcanic ash cloud information from the Moderate Resolution Imaging Spectradiometer( MODIS) remote sensing image,and the total detection accuracy and Kappa coefficient reaches 88. 4% and 0. 801 1 respectively. The detection result is satisfying.

关 键 词：火山灰云 遥感检测 独立分量分析 支持向量机 MODIS图像 贝叶斯网络 

分 类 号：TN911.73[电子电信—通信与信息系统]