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	Technical Framework of Feature Extraction Based on Pixel-Level SAR Image Time Series
	Cheng L.; Wang, Y. F.; Zhong, L. S.; Du, P. J.; Li, M. C.
	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
内容类型	SCI/SSCI论文
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.

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