Knowledge Commons of Institute of Automation,CAS
A Novel Tensor-Based Feature Extraction Method for Polsar Image Classification | |
Huang, Xiayuan1; Nie, Xiangli1; Qiao, Hong1; Zhang, Bo2 | |
2019-11-14 | |
会议名称 | IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium |
会议日期 | 28 July-2 Aug. 2019 |
会议地点 | Yokohama, Japan, Japan |
摘要 | Spatial information helps improve the performance of polarimetric synthetic aperture radar (PolSAR) image classification. Some existing methods have combined the spatial information and polarimetric features by the third-order tensor representation for feature extraction. They describe a pixel with the patch centered on this pixel. But they neglect the spatial heterogeneity, which may influence the classification performance. Therefore, we firstly seek k nearest samples based on the polarimetric feature similarity for each pixel to construct the second-order tensor, whose first order denotes the nearest samples and the second order denotes the polarimetric features. Moreover, k nearest samples are searched in a spatial local region rather than the full image, which can exploit the spatial information and reduce the computational burden. Then we employ tensor principal component analysis (TPCA) to extract low-dimensional features. Experimental results demonstrate that the proposed method can improve the classification performance compared with other methods. |
收录类别 | EI |
七大方向——子方向分类 | 图像视频处理与分析 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/40602 |
专题 | 多模态人工智能系统全国重点实验室_机器人理论与应用 |
通讯作者 | Huang, Xiayuan |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.AMSS, Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Huang, Xiayuan,Nie, Xiangli,Qiao, Hong,et al. A Novel Tensor-Based Feature Extraction Method for Polsar Image Classification[C],2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
IGARSS2019.pdf(363KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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