哈尔滨工程大学学报2018，Vol.39Issue(6)：973-983,11.DOI:10.11990/jheu.201704074
SVM在高光谱图像处理中的应用综述
A review on the application of SVM in hyperspectral image processing
摘要
Abstract
Hyperspectral remote sensing has become a foremost technology in remote sensing,and it plays an impor-tant role in military and national economy. Support vector machine (SVM) has unique advantages in solving the problems of small sample size, nonlinearity, and high-dimensional modes; therefore, it is widely used in hyper-spectral data processing. Because of its advantages,SVM model has been applied widely in fields of hyperspectral imaging,such as band selection,classification,endmember selection,spectral unmixing,sub-pixel mapping,and anomaly detection. In this paper,the features of hyperspectral images are analyzed,and the development of hyper-spectral imaging across various fields as well as its main processing methods are summarized. The applications and advantages of SVM method in those fields are also discussed.关键词
高光谱/支持向量机/分类/端元选择/光谱解混/亚像元定位/异常检测Key words
hyperspectral/support vector machine (SVM)/classification/endmember selection/spectral unmix-ing/sub-pixel mapping/anomaly detection分类
信息技术与安全科学引用本文复制引用
王立国,赵亮,刘丹凤..SVM在高光谱图像处理中的应用综述[J].哈尔滨工程大学学报,2018,39(6):973-983,11.基金项目
国家自然科学基金项目(61675051) （61675051）
黑龙江省自然科学基金项目(F201409). （F201409）
