Hyperspectral Unmixing in the Presence of Mixed Noise Using Joint-Sparsity and Total Variation-Reference-Cited by-同舟云学术

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Hyperspectral Unmixing in the Presence of Mixed Noise Using Joint-Sparsity and Total Variation

Published:2016-09 Issue:9 Volume:9 Page:4257-4266
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Aggarwal Hemant Kumar,Majumdar Angshul

Funder

TCS Research Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/7581005/07414394.pdf?arnumber=7414394

Cited by 49 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. Space object identification and classification from hyperspectral material analysis;Scientific Reports;2024-01-18

2. Toward Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain Regularization;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. Sparse Unmixing in the Presence of Mixed Noise Using ℓ₀-Norm Constraint and Log-Cosh Loss;IEEE Transactions on Geoscience and Remote Sensing;2024

4. Multi and hyperspectral image unmixing with spatial coherence by extended blind end-member and abundance extraction;Journal of the Franklin Institute;2023-10

5. A Coarse-to-Fine Hyperspectral Target Detection Method Based on Low-Rank Tensor Decomposition;IEEE Transactions on Geoscience and Remote Sensing;2023

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