DOI: 10.1080/01431161.2019.1708507
论文题名: A hierarchical spatial-temporal graph-kernel for high-resolution SAR image change detection
作者: Jia L. ; Wang J. ; Ai J. ; Jiang Y.
刊名: International Journal of Remote Sensing
ISSN: 1431161
出版年: 2020
卷: 41, 期: 10 语种: 英语
Scopus关键词: Support vector machines
; Synthetic aperture radar
; Change detection
; Complex structure
; Global structure
; Hierarchical graph model
; High resolution synthetic aperture radar images
; High-resolution SAR
; Spatial temporals
; Structural information
; Radar imaging
; data set
; graphical method
; hierarchical system
; image resolution
; radar imagery
; spatial analysis
; support vector machine
; synthetic aperture radar
; temporal analysis
英文摘要: Effective utilization of structural information is important for high-resolution synthetic aperture radar (SAR) image change detection. For comprehensively utilizing the local and global structures in SAR images, a hierarchical spatial-temporal graph kernel (STGK) method is proposed in this paper for high-resolution SAR image change detection. First, the bi-temporal hierarchical graph models are constructed for extracting the local-global structures in the bi-temporal SAR images. Then, a STGK function, which measures the spatial and temporal similarities between the local-global structures, is constructed for indicating the change levels between the bi-temporal images. Finally, a support vector machine (SVM) is implemented with the STGK function for producing the final change detection results. Experimental results on real GaoFen-3 SAR data sets demonstrate the effectiveness of the proposed method, and prove that the STGK method is capable of detecting changed areas with relatively complex structures. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158194
Appears in Collections: 气候变化与战略
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作者单位: School of Computer and Information, Hefei University of Technology, Hefei, China
Recommended Citation:
Jia L.,Wang J.,Ai J.,et al. A hierarchical spatial-temporal graph-kernel for high-resolution SAR image change detection[J]. International Journal of Remote Sensing,2020-01-01,41(10)