A spatial-spectral clustering-based algorithm for endmember extraction and hyperspectral unmixing-Reference-Cited by-同舟云学术

A spatial-spectral clustering-based algorithm for endmember extraction and hyperspectral unmixing

Published:2020-12-20 Issue:5 Volume:42 Page:1948-1972
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Cheng Xiaoyu¹,Cai Zhouyin¹,Li Jia¹,Wen Maoxing²,Wang Yueming²^ORCID,Zeng Dan¹

Affiliation:

1. Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai Institute of Advanced Communication and Data Science, Shanghai University, Shanghai, China

2. Key Laboratory of Space Active Opto-Electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China

Funder

National Natural Science Foundation

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2020.1849851

Reference40 articles.

1. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods

2. A variable splitting augmented Lagrangian approach to linear spectral unmixing

3. Hyperspectral Subspace Identification

4. Hyperspectral Remote Sensing Data Analysis and Future Challenges

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