Approximate Sparse Regularized Hyperspectral Unmixing
Joint Authors
Tian, Wei
Zhang, Yaning
Wang, Shengqian
Hu, Saifeng
Zhang, Shaoquan
Deng, Chengzhi
Wu, Zhaoming
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-17
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Sparse regression based unmixing has been recently proposed to estimate the abundance of materials present in hyperspectral image pixel.
In this paper, a novel sparse unmixing optimization model based on approximate sparsity, namely, approximate sparse unmixing (ASU), is firstly proposed to perform the unmixing task for hyperspectral remote sensing imagery.
And then, a variable splitting and augmented Lagrangian algorithm is introduced to tackle the optimization problem.
In ASU, approximate sparsity is used as a regularizer for sparse unmixing, which is sparser than l1 regularizer and much easier to be solved than l0 regularizer.
Three simulated and one real hyperspectral images were used to evaluate the performance of the proposed algorithm in comparison to l1 regularizer.
Experimental results demonstrate that the proposed algorithm is more effective and accurate for hyperspectral unmixing than state-of-the-art l1 regularizer.
American Psychological Association (APA)
Deng, Chengzhi& Zhang, Yaning& Wang, Shengqian& Zhang, Shaoquan& Tian, Wei& Wu, Zhaoming…[et al.]. 2014. Approximate Sparse Regularized Hyperspectral Unmixing. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-510480
Modern Language Association (MLA)
Deng, Chengzhi…[et al.]. Approximate Sparse Regularized Hyperspectral Unmixing. Mathematical Problems in Engineering No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-510480
American Medical Association (AMA)
Deng, Chengzhi& Zhang, Yaning& Wang, Shengqian& Zhang, Shaoquan& Tian, Wei& Wu, Zhaoming…[et al.]. Approximate Sparse Regularized Hyperspectral Unmixing. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-510480
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-510480