A novel measurement matrix optimization approach for hyperspectral unmixing

DOI10.1155/2017/8471024zbMath1437.94029OpenAlexW2726215905WikidataQ59145640 ScholiaQ59145640MaRDI QIDQ1794237

Su Xu, Xi-Ping He

Publication date: 15 October 2018

Published in: Journal of Control Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/8471024

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• A simple proof of the restricted isometry property for random matrices
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Optimized Projections for Compressed Sensing
• On Projection Matrix Optimization for Compressive Sensing Systems
• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Compressive Sensing of Sparse Tensors
• Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit
• Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization
• Variable Density Compressed Image Sampling
• Kronecker Compressive Sensing
• Compressed sensing

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