Robust Hyperspectral Unmixing With Correntropy-Based Metric

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	Robust Hyperspectral Unmixing With Correntropy-Based Metric
	Wang, Ying; Pan, Chunhong; Xiang, Shiming; Zhu, Feiyun
刊名	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2015-11-01
卷号	24 期号:11 页码:4027-4040
关键词	Hyperspectral unmixing linear mixture model non-negative matrix factorization robust estimation correntropy based metric
英文摘要	Hyperspectral unmixing is one of the crucial steps for many hyperspectral applications. The problem of hyperspectral unmixing has proved to be a difficult task in unsupervised work settings where the endmembers and abundances are both unknown. In addition, this task becomes more challenging in the case that the spectral bands are degraded by noise. This paper presents a robust model for unsupervised hyperspectral unmixing. Specifically, our model is developed with the correntropy-based metric where the nonnegative constraints on both endmembers and abundances are imposed to keep physical significance. Besides, a sparsity prior is explicitly formulated to constrain the distribution of the abundances of each endmember. To solve our model, a half-quadratic optimization technique is developed to convert the original complex optimization problem into an iteratively reweighted nonnegative matrix factorization with sparsity constraints. As a result, the optimization of our model can adaptively assign small weights to noisy bands and put more emphasis on noise-free bands. In addition, with sparsity constraints, our model can naturally generate sparse abundances. Experiments on synthetic and real data demonstrate the effectiveness of our model in comparison to the related state-of-the-art unmixing models.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	NONNEGATIVE MATRIX FACTORIZATION ; HALF-QUADRATIC MINIMIZATION ; CONSTRAINED LEAST-SQUARES ; ENDMEMBER EXTRACTION ; IMAGERY ; ALGORITHMS ; SIGNAL ; REPRESENTATION ; MODEL
收录类别	SCI
语种	英语
WOS记录号	WOS:000359563500002
公开日期	2015-12-24
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/8915]
专题	自动化研究所_模式识别国家重点实验室_遥感图像处理团队
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Wang, Ying,Pan, Chunhong,Xiang, Shiming,et al. Robust Hyperspectral Unmixing With Correntropy-Based Metric[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(11):4027-4040.
APA	Wang, Ying,Pan, Chunhong,Xiang, Shiming,&Zhu, Feiyun.(2015).Robust Hyperspectral Unmixing With Correntropy-Based Metric.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(11),4027-4040.
MLA	Wang, Ying,et al."Robust Hyperspectral Unmixing With Correntropy-Based Metric".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.11(2015):4027-4040.