摘要
支持向量机(SVM)是统计学习理论的最新方法,在模式分类和回归分析中有广泛的应用。针对SAR图像解译,SVM在图像滤波、图像分割、目标识别与分类、极化数据分类等过程中有很好的处理能力。本文首先介绍了SVM的基本原理,然后综述SVM在SAR图像解译中的各方面研究进展。
Support Vector Machine （SVM） is the latest method of statistical learning theory, widely used in pattern classification and regression analysis. Aimed at SAR image interpretation, SVM shows good performance in image filtering, image segmentation, target discrimination and classification, as well as polarimetric SAR data classification. The paper first introduces the basic theory of SVM, then reviews the development of SVM in SAR image interpretation.
出处
《遥感信息》
CSCD
2009年第5期90-95,共6页
Remote Sensing Information
关键词
SAR
图像解译
支持向量机
SAR
image interpretation
support vector machine
