Spectral-spatial-sparse unmixing with superpixel-oriented graph Laplacian-Reference-Cited by-同舟云学术

Spectral-spatial-sparse unmixing with superpixel-oriented graph Laplacian

Published:2023-04-18 Issue:8 Volume:44 Page:2573-2589
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Li Zhi¹,Feng Ruyi¹^ORCID,Wang Lizhe¹,Zeng Tieyong²

Affiliation:

1. Hubei Key Laboratory of Regional Development and Environmental Response, College of Computer Science, China University of Geosciences, Wuhan, Hubei, China

2. Department of Mathematics, Chinese University of Hong Kong, Hong Kong, P. R. China

Funder

National Natural Science Foundation of China

Hong Kong Scholars Program

National Key Technology Research and Development Program of the Ministry of Science and Technology of China Under Grant

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2204198

Reference23 articles.

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

2. A graph Laplacian regularization for hyperspectral data unmixing

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

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

5. Combining low-rank constraint for similar superpixels and total variation sparse unmixing for hyperspectral image

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2. Spatial-Spectral Attention Bilateral Network for Hyperspectral Unmixing;IEEE Geoscience and Remote Sensing Letters;2023