A Distributed N-FINDR Cloud Computing-Based Solution for Endmembers Extraction on Large-Scale Hyperspectral Remote Sensing Data

A Distributed N-FINDR Cloud Computing-Based Solution for Endmembers Extraction on Large-Scale Hyperspectral Remote Sensing Data

In this work, we introduce a novel, distributed version of the N-FINDR endmember extraction algorithm, which is able to exploit computer cluster resources in order to efficiently process large volumes of hyperspectral data. The implementation of the distributed algorithm was done by extending the In...

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Bibliographic Details
Main Authors: Victor Andres Ayma Quirita, Gilson Alexandre Ostwald Pedro da Costa, César Beltrán
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Remote Sensing
Subjects:
cloud computing
hyperspectral image processing
endmember extraction
unmixing
remote sensing
large-scale hyperspectral data
Online Access:https://www.mdpi.com/2072-4292/14/9/2153

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