The Tensor Discriminant Ridge Regression Model With Extreme Learning Machine for Hyperspectral Image Classification
Multivariate ridge regression (MR), linear discriminant analysis (LDA) and extreme learning machine (ELM) have been widely used in hyperspectral image (HSI) classification. However, these methods do not consider the influence of noise in HSIs, spatial information, and the internal relationship betwe...
Main Authors: | Xinpeng Wang, Bingo Wing-Kuen Ling, Huimin Zhao, Shaopeng Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10227511/ |
Similar Items
-
PSSA: PCA-Domain Superpixelwise Singular Spectral Analysis for Unsupervised Hyperspectral Image Classification
by: Qiaoyuan Liu, et al.
Published: (2023-02-01) -
Linear vs. Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Images
by: Faxian Cao, et al.
Published: (2017-11-01) -
Spectral denoising in hyperspectral imaging using the discrete wavelet transform
by: Rafael Iván Rincón-Fonseca, et al.
Published: (2021-08-01) -
Deep Tensor Attention Prior Network for Hyperspectral Image Denoising
by: Weilin Shen, et al.
Published: (2023-01-01) -
An Efficient and Adaptive Reconstructive Homogeneous Block-Based Local Tensor Robust PCA for Feature Extraction of Hyperspectral Images
by: Longxia Qian, et al.
Published: (2024-01-01)