Clustering Based Band Selection

Language: English

Published by LAP LAMBERT Academic Publishing Jun 2022, 2022

6204957244 / 9786204957241

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This item is printed on demand - Print on Demand Titel. Neuware -Hyperspectral Images (HSIs) are popular in diversified applications, such as; Geo-sciences, Biomedical imaging, Agriculture, and physics-related research. The rich spatial and spectral information of HSI are the key factors for robust representation of class-specific objects, in remote sensing applications. But these images often suffer from the Hughes effect. This demands a dimensionality reduction using feature selection. The feature selection process is commonly called Band Selection (BS) for the HS dataset. This Book is mainly focused on three proposed models, where, mostly the clustering based unsupervised strategies are adopted for BS. First, Derivative-based band clustering and multi-agent PSO optimization for optimal band selection (DBC_MAPSO) is proposed. But they are time consuming and the selected bands are not persistent for each evaluation, due to the random nature of the optimizers. To overcome this, Spatial residual clustering and entropy-based ranking (SRC_EBR) and Featured clustering and ranking based bad cluster removal (FC_RBCR) are proposed.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.…

Seller Inventory # 9786204957241

Title
Clustering Based Band Selection
Author
Kishore Raju Kalidindi
Publisher
LAP LAMBERT Academic Publishing Jun 2022
Publication year
2022
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6204957244
ISBN 13
9786204957241
Item weight
209 grams
Dimensions
220x150x8 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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