Hyperspectral Unmixing VIA L1/4 Sparsity-Constrained Multilayer NMF

Zihan Zhang, Qi Wang, Yuan Yuan

科研成果: 书/报告/会议事项章节会议稿件同行评审

7 引用 (Scopus)

摘要

Hyperspectral unmixing, by extracting the fractional abundances of endmembers from the hyperspectral image (HSI), has raised wide attention in recent years. In last decade, nonnegative matrix factorization (NMF) have been intensively studied for solving spectral unmixing problem. In this paper, we extend the multilayer NMF method by incorporating the L1/4 sparsity constraint, named L1/4-MLNMF. The L1/4 regularizer induces sparsity effectively. We propose an iterative estimation algorithm for L1/4-MLNMF, which provides sparser and more accurate results than MLNMF. Experiments on a synthetic dataset and a real dataset show that the prposed method outperforms the similar competitors.

源语言英语
主期刊名2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
2143-2146
页数4
ISBN(电子版)9781538691540
DOI
出版状态已出版 - 7月 2019
活动39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, 日本
期限: 28 7月 20192 8月 2019

出版系列

姓名International Geoscience and Remote Sensing Symposium (IGARSS)

会议

会议39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
国家/地区日本
Yokohama
时期28/07/192/08/19

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