An Efficient and Adaptive Reconstructive Homogeneous Block-Based Local Tensor Robust PCA for Feature Extraction of Hyperspectral Images

An Efficient and Adaptive Reconstructive Homogeneous Block-Based Local Tensor Robust PCA for Feature Extraction of Hyperspectral Images

Model-driven tensor robust principal component analysis (TRPCA) has been widely applied to feature extraction of hyperspectral images (HSIs) and successfully protected two-dimensional spectral contextual information. Nevertheless, the current TRPCA-based feature extraction methods still destroy the...

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Bibliographic Details
Main Authors: Longxia Qian, Xianyue Wang, Mei Hong, Hongrui Wang, Yongchui Zhang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Feature extraction
hybrid spatial–spectral frontal slice
hyperspectral image (HSI)
reconstructive homogeneous block
tensor robust principal component analysis (TRPCA)
Online Access:https://ieeexplore.ieee.org/document/10409499/

Internet

https://ieeexplore.ieee.org/document/10409499/

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