Hyperspectral Endmember Extraction by (μ + λ) Multiobjective Differential Evolution Algorithm Based on Ranking Multiple Mutations

Endmember extraction (EE) plays a crucial part in the hyperspectral unmixing (HU) process. To obtain satisfactory EE results, the EE can be considered as the multiobjective optimization problem to optimize the volume maximization (VM) and root-mean-square error (RMSE) simultaneously. However, it is...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 59; H. 3; S. 2352 - 2364
Hauptverfasser:	Tong, Lyuyang, Du, Bo, Liu, Rong, Zhang, Liangpei, Tan, Kay Chen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	(<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">μ + <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">λ ) selection strategy Algorithms Crossovers Endmember extraction (EE) Evolutionary algorithms Evolutionary computation Genetic crosses Hyperspectral imaging Indexes multiobjective differential evolution (DE) Multiple objective analysis Mutants Mutation Offspring Operators (mathematics) Optimization Ranking ranking multiple mutations Root-mean-square errors Scaling Scaling factors Sociology Sorting Statistics Vectors
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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