Spatial–Spectral Feature Extraction With Local Covariance Matrix From Hyperspectral Images Through Hybrid Parallelization

Spatial–Spectral Feature Extraction With Local Covariance Matrix From Hyperspectral Images Through Hybrid Parallelization

This article presents the optimization and hybrid parallelization of a spatial–spectral feature extraction (FE) method from hyperspectral images (HSIs) using local covariance matrix (CM) representation, exploiting hybrid parallelism through multicore and manycore processors. The aim is to...

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Bibliographic Details
Main Authors: Emanuele Torti, Elisa Marenzi, Giovanni Danese, Antonio J. Plaza, Francesco Leporati
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Covariance matrix (CM)
feature extraction (FE)
graphic processing unit (GPU)
hyperspectral imaging (HSI)
parallelization
Online Access:https://ieeexplore.ieee.org/document/10207835/

Internet

https://ieeexplore.ieee.org/document/10207835/

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