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
	Keming Chen 1,2; Zhixin Zhou,2; Chunlei Huo2
发表期刊	IEEE Geosci. Remote Sensing Lett
	2013
卷号	10 期号:2 页码:236-240
摘要	In this letter, we propose a semisupervised context-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	Gaussian Processes Markov Processes Geophysical Image Processing Image Resolution Image Sensors Pattern Classification Probability
收录类别	SCI
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10850
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
通讯作者	Keming Chen
作者单位	1.Institute of Electronics, Chinese Academy of Sciences 2.Beijing Institute of Remote Sensing 3.Institute of Automation, Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Keming Chen,Zhixin Zhou,,Chunlei Huo. A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process[J]. IEEE Geosci. Remote Sensing Lett,2013,10(2):236-240.
APA	Keming Chen,Zhixin Zhou,,&Chunlei Huo.(2013).A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process.IEEE Geosci. Remote Sensing Lett,10(2),236-240.
MLA	Keming Chen,et al."A Semisupervised Context-Sensitive Change Detection Technique via Gaussian Process".IEEE Geosci. Remote Sensing Lett 10.2(2013):236-240.

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