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Robust Hyperspectral Unmixing With Correntropy-Based Metric
Wang, Ying; Pan, Chunhong; Xiang, Shiming; Zhu, Feiyun
Source PublicationIEEE TRANSACTIONS ON IMAGE PROCESSING
2015-11-01
Volume24Issue:11Pages:4027-4040
SubtypeArticle
AbstractHyperspectral 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.
KeywordHyperspectral Unmixing Linear Mixture Model Non-negative Matrix Factorization Robust Estimation Correntropy Based Metric
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TIP.2015.2456508
WOS KeywordNONNEGATIVE MATRIX FACTORIZATION ; HALF-QUADRATIC MINIMIZATION ; CONSTRAINED LEAST-SQUARES ; ENDMEMBER EXTRACTION ; IMAGERY ; ALGORITHMS ; SIGNAL ; REPRESENTATION ; MODEL
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000359563500002
Citation statistics
Cited Times:18[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8915
Collection模式识别国家重点实验室_先进数据分析与学习
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
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.
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