A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 先进时空数据分析与学习

	A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process
	Chen, Keming 1,2; Zhou, Zhixin 2; Huo, Chunlei3 ; Sun, Xian 1; Fu, Kun 1
发表期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
	2013-03-01
卷号	10 期号:2 页码:236-240
文章类型	Article
摘要	In this letter, we propose a semisupervised contex-t-sensitive technique for change detection in high-resolution multitemporal remote sensing images. This is achieved by analyzing the posterior probability of probabilistic Gaussian process (GP) classifier within a Markov random field (MRF) model. In particular, the method consists of two steps: 1) A semisupervised initialization exploits both labeled and unlabeled data based on a probabilistic GP classifier, and 2) an MRF regularization aims at refining the posterior probability by employing the spatial context information. In particular, both edge information and high-order potential are utilized in MRF energy function formulation. Experimental results obtained on real remote sensing multitemporal imagery data sets confirm the effectiveness of the proposed approach.
关键词	Change Detection Gaussian Process (Gp) High-resolution (Hr) Image Markov Random Field (Mrf)
WOS标题词	Science & Technology ; Physical Sciences ; Technology
关键词[WOS]	UNSUPERVISED CHANGE DETECTION ; CLASSIFICATION ; IMAGES ; SVM
收录类别	SCI
语种	英语
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000310901600006
引用统计	被引频次：17[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3703
专题	多模态人工智能系统全国重点实验室_先进时空数据分析与学习
作者单位	1.Chinese Acad Sci, Inst Elect, Key Lab GeoSpatial Informat Proc & Applicat Syst, Beijing 100190, Peoples R China 2.Beijing Inst Remote Sensing, Beijing 100854, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Chen, Keming,Zhou, Zhixin,Huo, Chunlei,et al. A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2013,10(2):236-240.
APA	Chen, Keming,Zhou, Zhixin,Huo, Chunlei,Sun, Xian,&Fu, Kun.(2013).A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,10(2),236-240.
MLA	Chen, Keming,et al."A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 10.2(2013):236-240.

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