Hyperspectral Image Classification with Spatial Filtering and \(l_{(2,1)}\) Norm
Recently, the sparse representation based classification methods have received particular attention in the classification of hyperspectral imagery. However, current sparse representation based classification models have not considered all the test pixels simultaneously. In this paper, we propose a h...
Main Authors: | Hao Li, Chang Li, Cong Zhang, Zhe Liu, Chengyin Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/17/2/314 |
Similar Items
-
Hyperspectral Image Denoising Based on Nonlocal Low-Rank and TV Regularization
by: Xiangyang Kong, et al.
Published: (2020-06-01) -
ADMM-Net for Beamforming Based on Linear Rectification with the Atomic Norm Minimization
by: Zhenghui Gong, et al.
Published: (2023-12-01) -
Robust AOA-Based Target Localization for Uniformly Distributed Noise via <i>ℓ<sub>p</sub></i>-<i>ℓ</i><sub>1</sub> Optimization
by: Yanping Chen, et al.
Published: (2022-09-01) -
Hessian Free Convolutional Dictionary Learning for Hyperspectral Imagery With Application to Compressive Chromo-Tomography
by: Xuesong Zhang, et al.
Published: (2020-01-01) -
Foreground-Background Separation via Generalized Nuclear Norm and Structured Sparse Norm Based Low-Rank and Sparse Decomposition
by: Yongpeng Yang, et al.
Published: (2020-01-01)