Chance-Constrained Robust Minimum-Volume Enclosing Simplex Algorithm for Hyperspectral Unmixing

Author:

Ambikapathi ArulMurugan,Chan Tsung-Han,Ma Wing-Kin,Chi Chong-Yung

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Cited by 65 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. A new convex model for linear hyperspectral unmixing;Journal of Computational and Applied Mathematics;2024-05

2. An initially robust minimum simplex volume-based method for linear hyperspectral unmixing;International Journal of Remote Sensing;2024-02-02

3. Locally-Rank-One-Based Joint Unmixing and Demosaicing Methods for Snapshot Spectral Images. Part I: A Matrix-Completion Framework;IEEE Transactions on Computational Imaging;2024

4. Deep Learning from Noisy Labels via Robust Nonnegative Matrix Factorization-Based Design;2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP);2023-12-10

5. Geometrical Methods – Illustration with Hyperspectral Unmixing;Source Separation in Physical‐Chemical Sensing;2023-10-13

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