Nonlinear hyperspectral unmixing based on sparse non-negative matrix factorization-Reference-Cited by-同舟云学术

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Nonlinear hyperspectral unmixing based on sparse non-negative matrix factorization

Published:2016-01-19 Issue:1 Volume:10 Page:015003
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:en
Short-container-title:J. Appl. Remote Sens

Author:

Li Jing¹,Li Xiaorun¹,Zhao Liaoying²

Affiliation:

1. Zhejiang University, College of Electrical Engineering, Room C421, Zhiquan Building, No. 38, Zheda Road, Xihu District, Hangzhou, Zhejiang Province, 310027, China

2. Hangzhou Dianzi University, Institute of Computer Application Technology, Hangzhou, Zhejiang 310018, China

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference39 articles.

1. Spectral unmixing

2. An overview on hyperspectral unmixing: geometrical, statistical, and sparse regression based approaches;Bioucas-Dias,2011

3. Foreword to the Special Issue on Spectral Unmixing of Remotely Sensed Data

4. Sparse Unmixing of Hyperspectral Data

5. Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander 1 Site

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Painting and calligraphy identification method based on hyperspectral imaging and convolution neural network;Spectroscopy Letters;2021-10-21

2. Modeling linear and intimate mixtures of materials in hyperspectral imagery with single-scattering albedo and kernel approaches;Journal of Applied Remote Sensing;2017-01-11

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