SMOOTH AND SPARSE HYPERSPECTRAL UNMIXING USING AN l0 PENALTY

被引：0
|
作者：
Sigurdsson, Jakob [1 ]
Ulfarsson, Magnus O. [1 ]
Sveinsson, Johannes R. [1 ]
机构：
[1] Univ Iceland, Dept Elect Engn, Reykjavik, Iceland
来源：
2013 5TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2013年
关键词：
blind signal separation; linear unmixing; l(0) penalty; roughness penalty; cyclic descent;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Hyperspectral unmixing is an important technique for analyzing hyperspectral remote sensing images. We propose an estimation algorithm that, simultaneously, encourages smoothness in the endmembers and sparseness in the abundances by using first order roughness and 10 penalties. The method is evaluated both on simulated data and a real hyperspectral image of an urban landscape.
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页数：4
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