Reweighted sparse unmixing for hyperspectral images with noise level estimation

DOI10.1016/j.cam.2022.114843zbMath1503.94010OpenAlexW4296893008MaRDI QIDQ2095150

Yanyan Li

Publication date: 9 November 2022

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2022.114843

zbMATH Keywords

noise estimationspatial correlationhyperspectral imagessparse unmixingweighted regularizer

Mathematics Subject Classification ID

Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Enhancing sparsity by reweighted \(\ell _{1}\) minimization
• Bilateral filter based total variation regularization for sparse hyperspectral image unmixing
• Nonnegative matrix factorization for spectral data analysis
• A Novel Hierarchical Bayesian Approach for Sparse Semisupervised Hyperspectral Unmixing
• Framelet-Based Sparse Unmixing of Hyperspectral Images
• A Compressive Sensing and Unmixing Scheme for Hyperspectral Data Processing

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