Reconstruction of Hyperspectral Images From Spectral Compressed Sensing Based on a Multitype Mixing Model
Hyperspectral compressed sensing (HCS) based on spectral unmixing technique has shown great reconstruction performance. In particular, the linear mixed model (LMM) has been widely used in HCS reconstruction. However, due to the complexity of environmental conditions, instrumental configurations, and...
Main Authors: | Zhongliang Wang, Mi He, Zhen Ye, Ke Xu, Yongjian Nian, Bormin Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9094327/ |
Similar Items
-
Spatial-Spectral Joint Compressed Sensing for Hyperspectral Images
by: Zhongliang Wang, et al.
Published: (2020-01-01) -
Distributed Compressed Hyperspectral Sensing Imaging Based on Spectral Unmixing
by: Zhongliang Wang, et al.
Published: (2020-04-01) -
Distributed Compressed Sensing of Hyperspectral Images According to Spectral Library Matching
by: Hua Xiao, et al.
Published: (2021-01-01) -
Spectral-Spatial Constrained Nonnegative Matrix Factorization for Spectral Mixture Analysis of Hyperspectral Images
by: Ge Zhang, et al.
Published: (2021-01-01) -
Collaborative Coupled Hyperspectral Unmixing Based Subpixel Change Detection for Analyzing Coastal Wetlands
by: Minghui Chang, et al.
Published: (2021-01-01)