Tucker tensor decomposition with rank estimation for sparse hyperspectral unmixing-Reference-Cited by-同舟云学术

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Tucker tensor decomposition with rank estimation for sparse hyperspectral unmixing

Published:2024-06-16 Issue:12 Volume:45 Page:3992-4022
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wu Ling¹,Huang Jie¹^ORCID,Zhu Zi-Yue¹

Affiliation:

1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, PR China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of Chin

Sichuan Science and Technology Program

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2357841

Reference61 articles.

1. Alternating direction algorithms for constrained sparse regression: Application to hyperspectral unmixing

2. Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

3. Boardman, J. W. 1993. “Automating Spectral Unmixing of AVIRIS Data Using Convex Geometry Concepts.” Proceedings Summaries Annual JPL Airborne Geosci. Workshop, Pasadena, Calif. 11–14.

4. Atomic Decomposition by Basis Pursuit

5. Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

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