Supervised Polarimetric SAR Image Classification Using Tensor Local Discriminant Embedding
Huang, Xiayuan1; Qiao, Hong1,2,3; Zhang, Bo4,5; Nie, Xiangli1
2018-06-01
发表期刊IEEE TRANSACTIONS ON IMAGE PROCESSING
卷号27期号:6页码:2966-2979
文章类型Article
摘要Feature extraction is a very important step for polarimetric synthetic aperture radar (PolSAR) image classification. Many dimensionality reduction (DR) methods have been employed to extract features for supervised PolSAR image classification. However, these DR-based feature extraction methods only consider each single pixel independently and thus fail to take into account the spatial relationship of the neighboring pixels, so their performance may not be satisfactory. To address this issue, we introduce a novel tensor local discriminant embedding (TLDE) method for feature extraction for supervised PolSAR image classification. The proposed method combines the spatial and polarimetric information of each pixel by characterizing the pixel with the patch centered at this pixel. Then each pixel is represented as a third-order tensor of which the first two modes indicate the spatial information of the patch (i.e., the row and the column of the patch) and the third mode denotes the polarimetric information of the patch. Based on the label information of samples and the redundance of the spatial and polarimetric information, a supervised tensor-based DR technique, called TLDE, is introduced to find three projections which project each pixel, that is, the third-order tensor into the low-dimensional feature. Finally, classification is completed based on the extracted features using the nearest neighbor classifier and the support vector machine classifier. The proposed method is evaluated on two real PolSAR data sets and the simulated PolSAR data sets with various number of looks. The experimental results demonstrate that the proposed method not only improves the classification accuracy greatly but also alleviates the influence of speckle noise on classification.
关键词Land Cover Classification Dimensionality Reduction Feature Extraction Spatial Information Polarimetric Signature Tensor Local Discriminant Embedding Plosar Image
WOS标题词Science & Technology ; Technology
DOI10.1109/TIP.2018.2815759
关键词[WOS]LAND-COVER CLASSIFICATION ; DIMENSIONALITY REDUCTION ; WISHART DISTRIBUTION ; DECOMPOSITION ; RECOGNITION
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61602483 ; China Postdoctoral Science Foundation(2017M620953) ; Strategic Priority Research Program of the CAS(XDB02080003) ; Beijing Natural Science Foundation(4174107) ; 61627808 ; 91648205 ; 61379093)
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000428930600006
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/21715
专题复杂系统管理与控制国家重点实验室_复杂系统研究
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Inst Appl Math, LSEC, AMSS, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Huang, Xiayuan,Qiao, Hong,Zhang, Bo,et al. Supervised Polarimetric SAR Image Classification Using Tensor Local Discriminant Embedding[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2018,27(6):2966-2979.
APA Huang, Xiayuan,Qiao, Hong,Zhang, Bo,&Nie, Xiangli.(2018).Supervised Polarimetric SAR Image Classification Using Tensor Local Discriminant Embedding.IEEE TRANSACTIONS ON IMAGE PROCESSING,27(6),2966-2979.
MLA Huang, Xiayuan,et al."Supervised Polarimetric SAR Image Classification Using Tensor Local Discriminant Embedding".IEEE TRANSACTIONS ON IMAGE PROCESSING 27.6(2018):2966-2979.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
2018-HXY-TIP-supervi(6075KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Huang, Xiayuan]的文章
[Qiao, Hong]的文章
[Zhang, Bo]的文章
百度学术
百度学术中相似的文章
[Huang, Xiayuan]的文章
[Qiao, Hong]的文章
[Zhang, Bo]的文章
必应学术
必应学术中相似的文章
[Huang, Xiayuan]的文章
[Qiao, Hong]的文章
[Zhang, Bo]的文章
相关权益政策
暂无数据
收藏/分享
文件名: 2018-HXY-TIP-supervised PolSAR classification.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。