Robust Hyperspectral Unmixing With Correntropy-Based Metric
文献类型：期刊论文
| 作者 | Wang, Ying ; Pan, Chunhong; Xiang, Shiming; Zhu, Feiyun
|
| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
 |
| 出版日期 | 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 |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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