测绘科学技术学报2016，Vol.33Issue(5)：507-512,6.DOI:10.3969/j.issn.1673-6338.2016.05.013
顾及分类器参数的全极化SAR图像特征选择与分类
Feature Selection and Classification of Fully Polarimetric SAR Images Considering Classifier Parameters
摘要
Abstract
The polarimetric synthetic aperture radar( PolSAR) images can provide more information than conven-tional SAR images. However, increasing the number of features does not always improve classification accuracy. It is very important to select an optimized feature set from fully polarimetric SAR images. In order to effectively and a-daptively select features, an improved feature selection and classification method considering classifier parameters is proposed in this paper. On the basis of the assessment of support vector number, the effective features are select-ed while the classifier parameters are optimized by using the genetic algorithm( GA) . Then, the optimized feature set and parameters are applied to classify the SAR image. To evaluate the performance and efficiency of the pro-posed method, the experiments have been carried out on two sets of PolSAR data. The classification results demon-strate that the proposed method is more accurate than conventional methods, which can not only reduce the effect caused by classifier parameters, but also obtain high classification accuracy with less number of features.关键词
极化SAR/特征选择/支持向量机/分类/参数优化Key words
polarimetric synthetic aperture radar( PolSAR)/feature selection/support vector machine( SVM)/classification/parameters optimization分类
天文与地球科学引用本文复制引用
袁春琦,徐佳,程圆娥,许康..顾及分类器参数的全极化SAR图像特征选择与分类[J].测绘科学技术学报,2016,33(5):507-512,6.基金项目
国家自然科学基金项目(41301449) （41301449）
江苏省测绘地理信息科研项目(JSCHKY201501) （JSCHKY201501）
地理空间信息工程国家测绘地理信息局重点实验室基金项目(201324). （201324）
