Robust Linear Unmixing for Hyperspectral Remote Sensing Imagery Based on Enhanced Constraint of Classification-Reference-Cited by-同舟云学术

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Robust Linear Unmixing for Hyperspectral Remote Sensing Imagery Based on Enhanced Constraint of Classification

Published:2022-07-17 Issue: Volume: Page:
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Container-title:IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Chi Jinxue¹,Shen Xueji¹,Yu Haoyang¹,Shang Xiaodi¹,Chanussot Jocelyn²,Shi Yimin¹

Affiliation:

1. Center of Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University,Dalian,China,116026

2. Grenoble Institut polytechnique de Grenoble,Grenoble Images Parole Signal Automatique Laboratory,Department Image and Signal,France,38402

Funder

Chinese Academy of Sciences

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9883023/9883024/09883935.pdf?arnumber=9883935

Reference7 articles.

1. End-member extraction for hyperspectral image analysis

2. A Quantitative and Comparative Analysis of Endmember Extraction Algorithms From Hyperspectral Data

3. Robust Linear Spectral Unmixing Using Anomaly Detection

4. Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery

5. Residual Component Analysis of Hyperspectral Images—Application to Joint Nonlinear Unmixing and Nonlinearity Detection

Cited by 1 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. Hyperspectral image classification Based on weakened Laplacian pyramid and guided filtering;International Journal of Remote Sensing;2023-09-02

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