Technical Framework of Feature Extraction Based on Pixel-Level SAR Image Time Series
文献类型：SCI/SSCI论文
| 作者 | Cheng L.; Wang, Y. F.; Zhong, L. S.; Du, P. J.; Li, M. C. |
| 发表日期 | 2015 |
| 关键词 | DTW feature extraction image registration pixel-level SAR image time series similarity measurement spatiotemporal analysis cover change detection land-cover china classification crop dynamics asar deformation vegetation similarity |
| 英文摘要 | This study proposes a novel technical framework of feature extraction based on pixel-level synthetic aperture radar (SAR) image time series, to exploit the application potential of SAR image data with low and medium spatial resolution. This framework comprises three key parts: 1) construction of the pixel-level SAR image time series using a new matching technique based on progressive binary partition; 2) pixel-level similarity measurement via dynamic time warping (DTW); and 3) a new spatiotemporal similarity analysis method that improves feature extraction by considering both the similarity of a feature's pixel-level time series and its spatial correlation. Two locations, covered by 31 low-resolution (150 m) and 26 medium-resolution (30 m) ENVISAT ASAR images, respectively, were selected as test cases to validate the proposed framework. Results show that the framework can identify features with a high level of accuracy, completeness, and correctness, outperforming methods using multitemporal images, as well as the time series-only (nonspatial) method, and other methods of spatiotemporal similarity analysis that use alternative similarity measures. |
| 出处 | Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| 卷 | 8 |
| 期 | 4 |
| 页 | 1665-1681 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1939-1404 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/38420]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Cheng L.,Wang, Y. F.,Zhong, L. S.,et al. Technical Framework of Feature Extraction Based on Pixel-Level SAR Image Time Series. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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