太阳成8722(中国)有限公司-GREEN NO.1

标题：Polarimetric-Spatial Classification of SAR Images Based on the Fusion of Multiple Classifiers作者：Ma, Xiaoshuang; Shen, Huanfeng; Yang, Jie; Zhang, Liangpei; Li,Pingxiang

来源出版物：IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 卷：7 期：3 页：961-971 DOI：10.1109/JSTARS.2013.2265331 出版年：MAR 2014

摘要：Traditional image classification methods are undertaken using the pixel as the research unit. These methods cannot use semantic information, and their classification results may not always be satisfactory. To solve this problem, objected-oriented methods have been widely investigated to classify remote sensing images. In this paper, we propose an innovative objected-oriented technique that combines pixel-based classification and a segmentation approach for the classification of polarimetric synthetic aperture radar (PolSAR) images. In the process of the pixel-based classification, a soft voting strategy is utilized to fuse multiple classifiers, which can, to some extent, overcome the drawback of majority voting. The experimental results are presented for two quad-polarimetric SAR images. The proposed classification scheme improves the classification accuracies after assembling the multiple classifiers, and provides the classification maps with more homogeneous regions by integrating the spatial information, when compared with pixel-based classification. By deploying multi-scale segmentation, we get a series of classification results, which again show that our method is superior to the conventional object-oriented methods.

入藏号：WOS:000335387900027

文献类型：Article

语种：English

作者关键词：Object-oriented, polarimetric-spatial classification, polarimetric synthetic aperture radar, voting

扩展关键词：LAND-COVER CLASSIFICATION; SUPPORT VECTOR MACHINES; UNSUPERVISED CLASSIFICATION; ALGORITHM; RECOGNITION; DECOMPOSITION; INFORMATION

通讯作者地址：Shen, Huanfeng; Wuhan Univ, Dept Resource & Environm Sci, Wuhan 430072, Peoples R China.

电子邮件地址：mxs.88@whu.edu.cn; shenhf@whu.edu.cn; yangjie@lmars.whu.edu.cn; zlp62@lmars.whu.edu.cn; pxli@lmars.whu.edu.cn

地址：

[Ma, Xiaoshuang; Shen, Huanfeng] Wuhan Univ, Dept Resource & Environm Sci, Wuhan 430072, Peoples R China.

[Yang, Jie; Zhang, Liangpei; Li, Pingxiang]Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Peoples R China.

研究方向：Engineering; Physical Geography; Remote Sensing; Imaging Science & Photographic Technology

ISSN：1939-1404