Joint Processing of Spatial Resolution Enhancement and Spectral Unmixing for Hyperspectral Image

2021 ◽  
pp. 1-1
Author(s):  
Chen Yi ◽  
Ying Liu ◽  
Ling Zheng ◽  
Yuquan Gan
Keyword(s):  
Spatial Resolution ◽  
Hyperspectral Image ◽  
Resolution Enhancement ◽  
Spectral Unmixing ◽  
Joint Processing

Spatial Resolution Enhancement for Hyperspectral Image Using Gaussian Scale Mixtures

2015 ◽  
Vol 713-715 ◽  
pp. 1926-1930 ◽  
Author(s):  
Jie Liu ◽  
Yi Fan Zhang
Keyword(s):  
Spatial Resolution ◽  
Hyperspectral Image ◽  
Resolution Enhancement ◽  
Gaussian Model ◽  
Practical Implementation ◽  
Simulation Experiments ◽  
Gaussian Scale Mixture ◽  
Bayesian Fusion ◽  
Implementation Scheme ◽  
Fusion Framework

In this paper, a wavelet-based Bayesian fusion framework is presented, in which a low spatial resolution hyperspectral (HS) image is fused with a high spatial resolution multispectral (MS) image. Particularly, a multivariate model, Gaussian Scale Mixture (GSM) model, is employed, which is believed to be capable of modeling the distribution of wavelet coefficients more accurately. A practical implementation scheme is also presented for feasible calculations. The proposed approach is validated by simulation experiments for HS and MS image fusion. The experimental results of the proposed approach are also compared with its counterpart employing a Gaussian model for performance evaluation.

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