N-PSO: endmember extraction using advance particle swarm optimization for NLMM

DOI10.1007/S12046-018-0839-5zbMath1402.90217OpenAlexW2883353183WikidataQ129517774 ScholiaQ129517774MaRDI QIDQ1628278

Deepti Shrimankar, Omprakash Tembhurne

Publication date: 4 December 2018

Published in: Sādhanā (Search for Journal in Brave)

Full work available at URL: https://www.ias.ac.in/describe/article/sadh/043/09/0141

zbMATH Keywords

particle swarm optimization (PSO)remote sensingspectral unmixingendmember extraction algorithms (EEA)minimum volume simplex analysisnonlinear mixing model (NLMM)

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59)

Cites Work

• Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization
• Nonlinear Unmixing of Hyperspectral Data With Vector-Valued Kernel Functions
• Supervised Nonlinear Spectral Unmixing Using a Postnonlinear Mixing Model for Hyperspectral Imagery

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